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Title:
The relationship between continuing professional development and demographic characteristics, professional practices, and employment conditions of school psychologists
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Book
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English
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Lopez, Alana D
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University of South Florida
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Tampa, Fla
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School psychology
National survey
Professional issues
Supervision
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Dissertations, Academic -- School Psychology -- Specialist -- USF   ( lcsh )
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bibliography   ( marcgt )
theses   ( marcgt )
non-fiction   ( marcgt )

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Abstract:
ABSTRACT: Multiple issues that impact service delivery, such as changing student demographic characteristics, educational law and policy, and an increased focus on accountability for services, require school psychologists to adapt and acquire new professional skills in order to meet the needs of students and families. Continuing professional development (CPD) could help school psychologists expand their repertoire of professional skills so that they can engage in effective service delivery. The present study examined the CPD subject areas endorsed by practicing school psychologists and the relationship of those areas with selected demographic characteristics, professional practices, and employment conditions. Secondary analyses were performed using the existing 2004-2005 National Association of School Psychologists (NASP) national database. The total sample size included the responses from 1,155 practitioners.^ ^^^^Descriptive analyses revealed that the most commonly endorsed CPD subject areas were behavioral interventions and standardized psychoeducational assessment. Logistic regression analyses indicated that selected demographic characteristic variables helped to predict participation in academic interventions and consultation/problem-solving CPD subject areas. However, no one demographic characteristic variable made a significant unique contribution to either model. Selected professional practice variables helped to predict participation in standardized psychoeducational assessment, social/emotional interventions, consultation/problem-solving, and response to intervention CPD subject areas. School psychologists who engaged in non-traditional CPD subject areas (i.e., social/emotional interventions, consultation/problem-solving, and response to intervention) were less likely to engage in professional practices related to special education (i.e., initial evaluations).^ Selected employment condition variables helped to predict participation in academic screening/progress monitoring and social/emotional interventions CPD subject areas. School psychologists who reported lower ratios were more likely to participate in social/emotional interventions CPD as compared to those who reported higher ratios. A statistically significant association was found between region and participation in academic screening/progress monitoring, behavioral assessment, social/emotional assessment, social/emotional intervention, response to intervention, and crisis intervention CPD. Implications of the findings are discussed within the context of previous research. Suggestions are offered for areas of future study related to the CPD activities of school psychologists.
Thesis:
Thesis (Ed.S.)--University of South Florida, 2007.
Bibliography:
Includes bibliographical references.
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System Details:
Mode of access: World Wide Web.
Statement of Responsibility:
by Alana D. Lopez.
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Title from PDF of title page.
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Document formatted into pages; contains 211 pages.

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aleph - 001927937
oclc - 192074402
usfldc doi - E14-SFE0001933
usfldc handle - e14.1933
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PAGE 1

The Relationship between Continuing Professional De velopment and Demographic Characteristics, Professional Practices, and Employ ment Conditions of School Psychologists by Alana D. Lopez A thesis submitted in partial fulfillment of the requirements for the degree of Education Specialist Department of Psychological and Social Foundations College of Education University of South Florida Major Professor: Michael J. Curtis, Ph.D. George M. Batsche, Ed.D. Jeffrey D. Kromrey, Ph.D. Date of Approval: March 22, 2007 Keywords: school psychology, national survey, prof essional issues, supervision, roles Copyright 2007, Alana D. Lopez

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i Table of Contents List of Tables iii List of Figures vi Abstract vii Chapter One: Introduction 1 Continuing Professional Development and School Psyc hology 3 Developmental View of Continuing Profes sional Development 5 School Psychologists as Adult Learners 7 Purposes of Continuing Professional Development 8 Support for Continuing Professional Development 8 Summary of the Research Literature 11 Purpose of the Study 12 Research Questions 12 Significance of Study 14 Chapter Two: Review of the Literature 16 History of Continuing Professional Development in Psychology 17 Federal Support for Continuing Professional Develo pment 19 Factors in School Psychology that Impact Continuin g 20 Professional Development Legislative Changes 21 Demographic Changes 23 Professional Organizations and Continuing Professi onal Development 24 The Nationally Certified School Psychologist Continuing Professional Development Progr am 26 The National Staff Development Council’s Stan dards for Staff Development 27 Empirical Support for National Staff Development Council Standards 36 Practices and Perceptions of Continuing Profession al Development by School Psychologists 42 Continuing Professional Development Practices 42 Perceptions of Continuing Professional Developmen t 47 Supervision 49 Conclusion 55

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ii Chapter Three: Method 57 Purpose of the Study 57 Creation of the National Database 58 Participants 58 Ethical Considerations 59 Historical Background of the National Database 59 Procedure for Creation of the Database 61 Description of the Current Study 63 Data Analysis 64 Chapter Four: Results 71 Description of the Sample 71 Demographic Characteristics, Professional Practic es, and Employment Conditions of Respondents 74 Research Questions 79 Research Question 1 79 Research Question 2 82 Research Question 3 102 Research Question 4 124 Research Question 5 147 Chapter Five: Discussion 151 Summary of the Findings 151 Demographic Characteristics 157 Professional Practices 159 Employment Conditions 163 Regional Differences 170 Limitations of the National Database 17 3 Implications for Practice and Future Research 175 Conclusion 180 References 181 Appendices 198 Appendix A: Comparison of 2005 NASP Membership to 2004-2005 National Database Respondents 199 Appendix B: 2004-2005 National Association of Schoo l Psychologists Demographic Character istics, Employment Co nditions, and Professional Practices Survey 200 Appendix C: National Survey Cover Letter 205 Appendix D: Minimum and Maximum Values for Select ed Variables 206 Appendix E: United States Geographic Regions 211

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iii List of Tables Table 1 Framework Used to Acquire Data from Multiple Sou rces 32 Table 2 Descriptive Statistics for Responders and N on-Responders 73 Table 3 Number of CPD Subject Areas Endorsed by Res pondents 74 Table 4 Age and Years of Experience in School Psych ology 75 Table 5 Gender, Ethnicity, and Highest Degree Earne d, and National Certification in School Psychology (NCSP) Credentia l Held 75 Table 6 Percentage of Total Work Time in Activities Related to Special Education, Number of Psychoeducational Evaluations Completed Relating to Initial Determination of Special Educa tion Eligibility, and Number of Special Education Reevaluations Compl eted 76 Table 7 Ratio of Individual Psychologists to Studen ts 77 Table 8 School Setting, Supervision Received in Pra ctice, Clinical Supervisor’s Degree Area, and Clinical Supervisor’s Degree Level 78 Table 9 Frequencies, Percentages, Proportions, and 95% Confidence Intervals for Each CPD Subject Area 80 Table 10 Phi Correlation Coefficients among Depende nt Variables 81 Table 11 Correlation Coefficients among Dependent a nd Independent Variables 83 Table 12 Correlation Coefficients among Independent Variables 83 Table 13 Logistic Regression Analysis: Standardize d Psychoeducational Assessment 85 Table 14 Logistic Regression Analysis: Academic S creening/Progress Monitoring 87 Table 15 Logistic Regression Analysis: Academic In terventions 89

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iv Table 16 Logistic Regression Analysis: Be havioral Assessment 90 Table 17 Logistic Regression Analysis: Behavioral Interventions 92 Table 18 Logistic Regression Analysis: Social/Emot ional Assessment 93 Table 19 Logistic Regression Analysis: So cial/Emotional Interventions 95 Table 20 Logistic Regression Analysis: Consultatio n/Problem-Solving 97 Table 21 Logistic Regression Analysis: Response to Intervention 98 Table 22 Logistic Regression Analysis: Crisis Inte rvention 100 Table 23 Logistic Regression Analysis: Other 101 Table 24 Correlation Coefficients among Dependent a nd Independent Variables 103 Table 25 Correlation Coefficients among Independent Variables 103 Table 26 Logistic Regression Analysis: Standardize d Psychoeducational Assessment 106 Table 27 Logistic Regression Analysis: Academic S creening/Progress Monitoring 109 Table 28 Logistic Regression Analysis: Academic In terventions 110 Table 29 Logistic Regression Analysis: Behavioral Assessment 111 Table 30 Logistic Regression Analysis: Behavioral Interventions 113 Table 31 Logistic Regression Analysis: Social/Emot ional Assessment 114 Table 32 Logistic Regression Analysis: Social/Emot ional Interventions 116 Table 33 Logistic Regression Analysis: Consultatio n/Problem-Solving 119 Table 34 Logistic Regression Analysis: Response to Intervention 121 Table 35 Logistic Regression Analysis: Crisis Inte rvention 123 Table 36 Logistic Regression Analysis: Other 124

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v Table 37 Correlation Coefficients among Dependent a nd Independent Variables 127 Table 38 Correlation Coefficients among Independent Variables 128 Table 39 Logistic Regression Analysis: Standardize d Psychoeducational Assessment 130 Table 40 Logistic Regression Analysis: Academic S creening/Progress Monitoring 132 Table 41 Logistic Regression Analysis: Academic In terventions 133 Table 42 Logistic Regression Analysis: Behavioral Assessment 135 Table 43 Logistic Regression Analysis: Behavioral Interventions 136 Table 44 Logistic Regression Analysis: Social/Emot ional Assessment 138 Table 45 Logistic Regression Analysis: Social/Emot ional Interventions 140 Table 46 Logistic Regression Analysis: Consultatio n/Problem-Solving 142 Table 47 Logistic Regression Analysis: Response to Intervention 143 Table 48 Logistic Regression Analysis: Crisis Inte rvention 145 Table 49 Logistic Regression Analysis: Other 146 Table 50 Frequency Counts and Percentages for Each Region 147

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vi List of Figures Figure 1. Probability Plot: Initial*Standardized Psychoeducational 107 Assessment CPD Figure 2. Probability Plot: % of Total Time *Stand ardized Psychoeducational Assessment CPD 107 Figure 3. Probability Plot: Initial*Social/Emotion al Intervention CPD 117 Figure 4. Probability Plot: % of Total Time*Consul tation/ Problem-Solving CPD 120 Figure 5. Probability Plot: % of Total Time*Respon se to Intervention CPD 122 Figure 6. Probability Plot: Ratio*Social/Emotional Interventions CPD 141

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vii The Relationship between Continuing Professional De velopment and Demographic Characteristics, Professional Practices, and Employ ment Conditions of School Psychologists Alana D. Lopez ABSTRACT Multiple issues that impact service delivery, such as changing student demographic characteristics, educational law and po licy, and an increased focus on accountability for services, require school psychol ogists to adapt and acquire new professional skills in order to meet the needs of s tudents and families. Continuing professional development (CPD) could help school ps ychologists expand their repertoire of professional skills so that they can engage in e ffective service delivery. The present study examined the CPD subject areas en dorsed by practicing school psychologists and the relationship of those areas w ith selected demographic characteristics, professional practices, and employ ment conditions. Secondary analyses were performed using the existing 2004-2005 Nationa l Association of School Psychologists (NASP) national database. The total s ample size included the responses from 1,155 practitioners. Descriptive analyses revealed that the most commonl y endorsed CPD subject areas were behavioral interventions and standardize d psychoeducational assessment. Logistic regression analyses indicated that selecte d demographic characteristic variables helped to predict participation in academic interve ntions and consultation/problemsolving CPD subject areas. However, no one demograp hic characteristic variable made a

PAGE 9

viii significant unique contribution to either model. Se lected professional practice variables helped to predict participation in standardized psy choeducational assessment, social/emotional interventions, consultation/proble m-solving, and response to intervention CPD subject areas. School psychologist s who engaged in non-traditional CPD subject areas (i.e., social/emotional intervent ions, consultation/problem-solving, and response to intervention) were less likely to engag e in professional practices related to special education (i.e., initial evaluations). Sele cted employment condition variables helped to predict participation in academic screeni ng/progress monitoring and social/emotional interventions CPD subject areas. S chool psychologists who reported lower ratios were more likely to participate in soc ial/emotional interventions CPD as compared to those who reported higher ratios. A sta tistically significant association was found between region and participation in academic screening/progress monitoring, behavioral assessment, social/emotional assessment, social/emotional intervention, response to intervention, and crisis intervention C PD. Implications of the findings are discussed within the context of previous research. Suggestions are offered for areas of future study related to the CPD activities of schoo l psychologists.

PAGE 10

1 Chapter One Introduction The school psychology literature has included calls for professional role change for nearly 50 years (Bradley-Johnson & Dean, 2000; Reschly & Ysseldyke, 2002). The first major proposal for a paradigm shift for the f ield emerged from the Thayer Conference in 1954 (Bradley-Johnson & Dean, 2000; F agan & Wise, 2000; Lambert, 1993). This conference focused on the training, cr edentialing, and professional practices of school psychologists (Fagan & Wise, 2000) and re sulted in a call for the profession to move beyond the traditional gatekeeping role of ass essment for special education eligibility (Bradley-Johnson & Dean, 2000). Recent calls for role change have emphasized the need for school psychologists to eng age in problem-solving, consultation, health promotion, prevention practices, indirect se rvice delivery, systems-level change, and other practices that extend beyond traditional testing and assessment to meet the diverse needs of children and families (Curtis & St ollar, 2002; Franklin & Duley, 2002; Harrison et al., 2003; Macklem, Kalinsky, & Corcora n, 2001; Tilly, 2002). The 2002 Multisite Conference on the Future of School Psycho logy specifically addressed the need for the field to adapt and respond to changes in or der to shape the future of the profession (Dawson et al., 2003). The conference emphasized th e need for professional role change in the midst of a school psychologist shortage and other contextual changes facing the field (e.g., changing student demographics, educati onal law and policy). Two major themes targeted for action by the conference includ ed: (a) an emphasis on systems-level

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2 change to best utilize limited resources to meet hi gh priority needs of children and families; and (b) a focus on pre-service and in-ser vice training to provide school psychologists with the necessary skills to practice effectively during a time of constant change and limited resources. Sheridan and Gutkin (2000) conceptualized a paradig m shift that may guide practice, training, and research in the field and a ddress the long standing call for role change. They proposed a paradigm shift from the tra ditional medical model toward an ecological framework for service delivery. An ecol ogical framework purports that the field focus on prevention, developing strong links with schools, families, and communities, utilizing evidence-based practices, ad vocating for systems-change, and addressing the multiple ecologies in which children and families function. The authors argued that school psychologists operating from an ecological framework are able to deliver more effective and efficient services to a wider range of systems, settings, and populations (Conoley & Gutkin, 1995; Sheridan & Gut kin, 2000). Role change and the associated skills necessary to facilitate this process are needed to adapt to the significant changes that hav e occurred in American schools, such as the rapidly changing demographic characteristics of the student population (Fowler & Harrison, 2001; Ysseldyke et al., 2006), an increas ing need for mental health services in schools (Adelman & Taylor, 2000; Furlong, Morrison, & Pavelski, 2000; Ysseldyke et al., 2006), and an emphasis on data-based decisionmaking to demonstrate accountability for services (Reschly & Ysseldyke, 2002). These rec ent changes in the educational system require school psychologists to master and a pply new skills to bridge the gap between old and new systems (Reschly & Ysseldyke, 2 002). To facilitate this transition,

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3 school psychologists may need to add skills related to systematic problem-solving, consultation, behavior change, instructional design and functional assessment to the knowledge and skill base they acquired during gradu ate training (Reschly & Ysseldyke, 2002). Despite these calls for role change and expansion, research indicates that many practitioners continue to engage in more traditiona l roles (Bramlett, Murphy, Johnson, & Wallingsford, 2002; Curtis, Grier, Abshier, Sutton, & Hunley, 2002; Curtis, Hunley, Walker, & Baker, 1999; Curtis, Lopez, Batsche, & Sm ith, 2006; Hosp & Reschly, 2002; Reschly, 2000). Challenges that confront the field of school psychology include providing effective services, demonstrating account ability for those services, and addressing the changing needs of children and famil ies in the twenty-first century (Bradley-Johnson & Dean, 2000; Ysseldyke et al., 20 06). Therefore, school psychologists must become lifelong learners and rei nvent and redefine their roles by refining, expanding, and acquiring new professional skills and competencies (Ysseldyke et al., 2006) in order to meet these challenges. Continuing Professional Development and School Psyc hology According to the American Psychological Association (APA) (2000), continuing professional development (CPD) is defined as an ong oing process consisting of formal learning activities that (a) are relevant to psycho logical practice, education, and science; (b) enable psychologists to keep pace with emerging issues and technologies; and (c) allow psychologists to maintain, develop, and incre ase competencies in order to improve services to the public and enhance contributions to the profession.

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4 Elman, Illfelder-Kaye, and Robiner (2005) detailed the 2002 Competencies Conference: Future Directions in Education and Cre dentialing in Professional Psychology, which was initiated by the Association of Psychology Postdoctoral and Internship Centers (APPIC). Conference participants identified professional development as one of eight core competency areas that provide a foundation for competent and professional psychology practice. A Professional De velopment Working Group (PDWG) was created to specifically address professional de velopment issues in the professional psychology field. This group consisted of members f rom various psychology backgrounds (e.g., school, clinical, and counseling ), and they collectively developed a definition of professional development base on rele vant research literature. The definition states the following, Professional development is the developmental proce ss of acquiring, expanding, refining, and sustaining knowledge, proficiency, sk ill, and qualifications for competent professional functioning that result in p rofessionalism. It comprises both (a) the internal task of clarifying profession al objectives, crystallizing professional identity, increasing self-awareness an d confidence, and sharpening reasoning, thinking, reflecting, and judgment and ( b) the social/contextual dimension of enhancing interpersonal aspects of pro fessional functioning and broadening professional autonomy (p. 368). The group deemed it important to create this workin g definition of professional development because efforts to define professional development as well as professionalism have been limited in the research l iterature (Elman et al., 2005). This definition encompasses more than formal learning ac tivities (APA, 2000) of

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5 psychologists and indicates that professional devel opment is determined by the professional’s developmental stage (e.g., pre-servi ce, practicing school psychologist) and the context in which learning occurs. This latter d efinition will be used as the foundational definition for the construct of CPD in this study. Developmental View of Continuing Professional Devel opment. The concept of CPD has been described as a continuous, life-long l earning process for professionals (Houle, 1980), and, more specifically, school psych ologists (Ysseldyke et al, 2006). Houle (1980) conceptualized CPD as occurring throug hout a professional’s lifespan. He suggested that each professional has a distinct and unique style of lifelong learning, which is influenced by that individual’s background character traits, and the immediate demands of the environment. Houle proposed a model of professional learning that included the following phases: (a) general educati on with an emphasis on the basic content required for specialization; (b) admission to the professional school; (c) preservice specialized education; (d) securing a crede ntial to practice; (e) entry into practice; and (f) professional practice. The professional pr actice phase is highly variable due to factors such as the age of the professional, differ ent work settings, and changes in career focus or path. Continuing professional development allows professionals to maintain and modernize their basic professional skills and compe tencies, which is a requirement unique to the professional practice phase. Fagan and Wise (2000) suggested that pre-service ed ucation provides the basic skills, theories, concepts, and experiences to begi n a career in a real life setting. The development and maintenance of professional skills and competencies begins at the preservice level (Curtis & Batsche, 1991). However, Fa gan and Wise (2000) noted that there

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6 is an expectation that professionals will engage in CPD because graduate training alone does not provide adequate preparation to address th e wide range of settings, clients, problems, and professional issues that will be enco untered throughout a career in school psychology. The National Association of School Psy chologists (NASP) (2000, 2003) indicated that it is the professional’s ethical res ponsibility to constantly engage in selfassessment and to identify those situations when th e knowledge and skills possessed are insufficient to meet clients’ needs. Furthermore, p rofessionals are required to obtain additional training and education to acquire or fur ther develop the knowledge and skills needed in order to provide the best services possib le. This developmental view of CPD is specifically reco gnized in the School Psychology: A Blueprint for Training and Practice III (Ysseldyke et al., 2006). The revised blueprint includes the following eight doma ins of competence: (a) Enhancing the Development of Cognitive and Academic Skills; (b) E nhancing the Development of Wellness, Social Skills, Mental Health, and Life Co mpetencies; (c) Data-Based Decision Making and Accountability; (d) Systems-Based Servic e Delivery; (e) Professional, Legal, Ethical, and Social Responsibility; (f) Technologic al Applications; (g) Diversity Awareness and Sensitive Service Delivery; and (h) I nterpersonal and Collaborative Skills. Ysseldyke et al. (2006) indicated that a ma jor change in this blueprint includes the recognition that school psychologists will develop competency in practice over time. For example, school psychology graduates are expected t o develop competency at the “novice” level in all domains at the time of gradua tion, be at a “competent” level in one domain following internship, and approach the “expe rt” level in one or two domains after 5-10 years in practice (p. 6, 11). It is not assume d that graduates will demonstrate

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7 competence in all domains, but, rather, competencie s and skills will develop over time. Ysseldyke et al. (2006) referred to this concept as “a continuum of skill development” (p. 11). This developmental view of school psychologist s’ competency and skill development supports the idea that CPD a lifelong p rocess that serves to enhance the individual practitioner as well as the services pro vided to children and families. School Psychologists as Adult Learners. It is critical to recognize professionals as adult learners as they progress through each profes sional learning phase (National Staff Development Council [NSDC], 2001; Sparks & Hirsh, 1 997). The nature of school psychology is to help clients become more effective and efficient learners through the use of evidence-based interventions, consultation, and systems-level change. However, the school psychologist also should be viewed as a lear ner within the context of his or her professional environment (e.g., school, administrat ive, or university setting) who requires support and the resources necessary to continually engage in lifelong learning. Krupp (1982) conceptualized the adult learner as proceedi ng through various stages of skill acquisition, which include awareness that a skill i s needed (or warrants refinement), awkward use of the skill, feeling phony when using the skill, skillful and deliberate use, masterful and automatic use, and, finally, innovati ve and creative use of the skill. This progression suggests that learning requires profess ionals to pass through various stages in order to acquire necessary skills and competencies that will allow them to remain professionally competent. The goal is for the learn er, or professional, to eventually take ownership in demonstrating and using newly acquired or refined skills. Krupp (1982) also suggested that it is critical to assess the st age, or step, at which adult learners are presently functioning in order to better meet their needs and to target appropriate and

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8 effective learning strategies. For example, a learn er who is only at the awareness level would be overwhelmed if presented with a plethora o f information and activities aimed at developing a new skill. Overall, individual adult l earners will vary in their professional development. In particular, school psychologists’ p rofessional development needs also may vary due to factors such as work setting, avail able resources, and number of other school psychologists employed (Chafouleas, Clonan, & Vanauken, 2002). Purposes of Continuing Professional Development. Additionally, it is important to consider the purpose of professional development The Professional Development Work Group (PDWG) noted that the nature of professi onal development is multi-faceted and may address one or more of the following goals: (a) developing skills/competencies; (b) refining skills; (c) attaining skills to preven t falling behind; (d) deepening/expanding existing skills/competencies; or (d) generalizing s kills/competencies to specific settings. These CPD goals may be achieved through a variety o f mechanisms such as workshops, classrooms, collaborative groups, formal CPD progra ms, training sessions, licensure/certification, reading, or mentoring (Elm an et al., 2005). The PDWG concluded that CPD is a broad and vague term that is applicab le to many types of professional development that occur under various conditions and settings (Elman et al., 2005). Overall, it is important to acknowledge the profess ional learning phase, characteristics of the adult learner, context of learning, and purpose of professional development when discussing CPD in the field of school psychology. Support for Continuing Professional Development. National and state school psychology associations have recognized the importa nce of CPD and created opportunities for school psychologists to develop, maintain, and enhance their

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9 professional skills (Fagan & Wise, 2000). In fact, CPD is one of the primary functions of such associations. Fagan and Wise (2000) indicated that the substantial growth of state school psychology associations, professional instit utes for school psychologists, and national associations (e.g., NASP, Division of Scho ol Psychology of the APA) has created many opportunities for CPD that include, bu t are not limited to, journals, professional conferences, and internet learning com munities. At the national level, the National School Psychology Certification System inc ludes one of the most organized CPD programs (Fagan & Wise, 2000), which requires t hat school psychologists complete and document 75 clock hours of CPD activities withi n a three-year period in order to renew their Nationally Certified School Psychologis t (NCSP) credential (NASP, 2003). The National Staff Development Council (NSDC) (2001 ) and others (e.g., Guskey & Sparks, 1996; Joyce and Showers, 1996; Kiernan, 2 004) conceptualized professional learning and development as far more than tradition al workshops, conferences, courses, and internet learning communities. Professional lea rning is defined as a means by which professionals acquire or enhance knowledge, skills, attitudes, and beliefs necessary to create high levels of learning for all students. Pr ofessional development is viewed as an on-going process that primarily occurs in the schoo l setting as professionals and teams collaborate, plan, and problem-solve on a regular b asis to best meet the needs of children and families. The process of professional developme nt can be used as a major driving force and catalyst for school improvement efforts ( Joyce & Showers, 1996). It is noted that obtaining information from sources outside the work setting, such as workshops and conferences, is also important to enhance professio nal learning. Joyce and Showers (1996) suggested that workshops or coursework, whic h are relevant to the specific school

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10 needs/context, are useful sources of information an d knowledge at the individual practitioner level. However, it is only one compone nt within the larger, multidimensional professional development system. The NSDC (2001) ar gued that if a great deal of professional development is received away from the work setting “it serves as a centrifugal force that leads to fragmentation and i ncoherent improvement efforts” (p. 12). Furthermore, Knight (2002) argued that “something t aught on an in-service course has a transfer value and a life expectancy directly propo rtional to its fit with the community of practice, which provided a way of understanding why CPD courses often have such limited influence on activity” (p. 232). Profession al development that occurs outside of the school setting has minimal impact on behavior c hange of individuals and the overall functioning of the system (NSDC, 2001). Knight (200 2) contended that it is important to realize that change is a slow process and that CPD needs to be considered in the context of the environment. The NSDC (2001) stated that professional developm ent may be viewed as either an investment that will pay off in the form of impr oved staff performance and student learning or as an expense that takes resources away from other priority budget areas. The former view of CPD advocates for meaningful profess ional growth that occurs primarily in the school setting, which ultimately will impact the main consumers of school psychologists’ knowledge (e.g., students, families) (Joyce & Showers, 1996). Professional development is envisioned as a goal-di rected means for improving service delivery, which, after all, is a paramount goal for the profession of school psychology.

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11 Summary of the Research Literature The need for school psychologists to engage in CPD is significant due to calls for role change and proposed paradigm shifts in the pro fession that will require knowledge and skills not included in the graduate-level prepa ration of many school psychologists (Chafouleas et al., 2002; Fagan & Wise, 2000; Sheri dan & Gutkin, 2000). These changes require that practitioners continually update their knowledge and skills and utilize the most current expertise available to serve children and families (Brown, 2002; NASP, 2003; Nastasi, 2000). The critical importance of CP D was specifically recognized at the 2002 Multisite Conference on the Future of School P sychology as one of the most pressing issues facing the field of school psycholo gy (Harrison, et al., 2003). It is argued that CPD has the potential to improve the quality a nd effectiveness of school psychological services (Chafouleas et al., 2002; Cr espi & Rigazio-Digilio, 1992), which can lead to improved outcomes for children and fami lies. There appears to be a void with regard to informati on about CPD relative to the profession of school psychology. Few studies have examined the CPD practices of school psychologists, despite the recognized import ance of CPD for the field (Chafouleas et al., 2002; Fowler & Harrison 2001; Lam & Yuen, 2 004). Little is known about the forms, frequency, quality, and popularity of CPD (L am & Yuen, 2004) as well as school psychologists’ perceptions of CPD (Guest, 2000). Li mited empirical research was found in which the relationship between the CPD of school psychologists and selected demographic characteristics, professional practices and employment conditions was examined (e.g., Fowler & Harrison, 2001). The limit ed research indicated few significant relationships among these variables.

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12 Furthermore, several studies have investigated supe rvision practices in the field (Chafouleas, et al., 2002; Fischetti & Crespi, 1999 ; Hunley et al., 2000; Ross & Goh, 1993; Zins, Murphy, & Wess, 1989). Some of these st udies have examined CPD of as a secondary area of interest (Ross & Goh, 1993; Watki ns, Tipton, Manus, & HuntonShoup, 1991). Supervision is viewed as a critical c omponent of professional development (Ross & Goh, 1993); however, it is just one form of CPD (Lam & Yuen, 2001). Therefore, it is important to examine professional development practices beyond supervision (Lam & Yuen, 2004). Additionally, data from national studies assessing the field of school psychology have revealed associatio ns and trends among selected demographic characteristics, professional practice, and employment condition variables; however, it is not clear how these relationships ar e associated with CPD practices and/or activities of school psychologists. Purpose of the Study Given the paucity of research on this topic, this s tudy was largely exploratory in nature. The purpose of this study was to identify t he CPD subject areas that school psychologists engage in and the relationship of tho se subject areas with selected demographic characteristics, professional practices and employment conditions. Additionally, the study investigated if participati on in CPD subject areas varied according to United States (U.S.) geographic region. Research Questions The following research questions were addressed in the present study.

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13 Research Question 1: What is the distribution of continuing profession al development subject areas among school psychologist s who are employed full-time in school settings? (Survey Item 35) Research Question 2: What is the direction and strength of the relation ship between selected demographic characteristics of sch ool psychologists and each continuing professional development subject area? a.) gender (Survey Items 1 and 35) b.) age (Survey Items 2 and 35) c.) years of experience in school psychology (Surve y Items 6 and 35) d.) highest degree earned (i.e., Masters, Masters p lus 30 semester hours/Educational Specialist, or Doctorate) (Survey Items 11 and 35) e.) Nationally Certified School Psychologist creden tial held (NCSP) (i.e., yes or no) (Survey Items 13 and 35) Research Question 3: What is the direction and strength of the relation ship between selected professional practices of school p sychologists and each continuing professional development subject area? a.) percentage of total work time in activities rel ated to special education (Survey Items 33 and 35) b.) number of psychoeducational evaluations complet ed relating to initial determination of special education eligibility (Sur vey Items 26 and 35) c.) number of special education reevaluations comp leted (Survey Items 27 and 35)

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14 Research Question 4: What is the direction and strength of the relatio nship between selected employment conditions of school ps ychologists and each continuing professional development subject area? a.) school setting (i.e., urban, suburban, rural) ( Survey Items 19 and 35) b.) ratio of individual students to school psycholo gist (Survey Items 23 and 35) c.) administrative supervision received in practice (Survey Items 36 and 35) d.) clinical supervision received in practice (Surv ey Items 37 and 35) d.) clinical supervisor’s degree area (i.e., school psychology, psychology, or other) (Survey Items 37 and 35) e.) clinical supervisor’s degree level (i.e., non-d octoral or doctoral) (Survey Items 37 and 35) Research Question 5: What is the relationship between the distribution of selected continuing professional development subjec t areas and geographic region? (Survey Items 35 and 10) Significance of the Study As indicated previously, few studies have examined the CPD practices of school psychologists (Chafouleas et al., 2002; Fowler & Ha rrison 2001; Lam & Yuen, 2004). Limited empirical research has examined the relatio nship between the CPD of school psychologists and selected demographic characterist ics, professional practices, and employment conditions. The literature on supervisio n has devoted little attention to CPD as well (Ross & Goh, 1993; Watkins, Tipton, Manus, & Hunton-Shoup, 1991). Data from national studies have revealed associations and tre nds among selected demographic characteristics, professional practice, and employm ent condition variables; however, it is

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15 unclear how these variables are associated with CPD practices and/or activities of school psychologists on a national level. The findings of this study could: (a) identify curr ent CPD trends in the field; (b) examine CPD trends in relationship to the current s tatus of the field; (c) provide information to trainers, researchers, practitioners and professional organizations about the CPD of school psychologists in the field; and ( d) inform future research and CPD initiatives and standards. Overall, the findings of the study could build upon and strengthen the existing literature base on CPD with in the field of school psychology.

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16 Chapter Two Review of the Literature The demand for continuing professional development (CPD) of school psychologists is significant due to proposed profes sional role changes (Ysseldyke et al, 2006), ever-changing needs of children and families (Bradl ey-Johnson & Dean, 2000; Chafouleas et al., 2002), and legal mandates focuse d on accountability of services (Individuals with Disabilities Improvement Act (IDE IA), 2004; No Child Left Behind Act (NCLB), 2001; Talley & Short, 1995). Furthermor e, it is likely that legislation will continue to be a major influence and shape school p sychology practice along with other factors such as economics, advances in technology a nd science, and increasing diversity in the United States (Jacob-Timm, 2000). These fact ors have impacted service delivery and transformed the role of the school psychologist (Sheridan & Gutkin, 2000). These changes require that practitioners continually upda te their knowledge and skills in order to effectively serve children and families (Fowler & Harrison, 2001; NASP, 2003). Continuing professional development is recognized a s an effective means to acquire and build on existing skills and competencies (Fowler & Harrison, 2001). Moreover, life-long learning is an essential component of professional practice and is the “cornerstone of psychology’s commitment to professional and social responsibility” (Belar et al., 2001, p. 4). School psychologists are challenged to go beyon d a written description of a school psychologist’s role or simply fulfilling predetermi ned certification and/or licensure

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17 requirements and to engage in authentic behavior ch ange that will lead to observable and positive outcomes for students (Aiga & Banta, 2003; Conoley & Gutkin, 1995). This chapter will examine CPD research in the field of school psychology. To date, the literature includes limited information o n the CPD practices of school psychologists and their relationship with selected demographic characteristic, professional practice, and employment condition var iables. Additionally, there is scant literature regarding school psychologists’ percepti ons of CPD. The information covered in this chapter includes: (a) the history of CPD i n psychology; (b) federal support for CPD; (c) factors in the field of school psychology that impact CPD; (c) professional organizations and CPD; (d) practices and perceptions of CPD by school psycholo gists; and (e) supervision. History of Continuing Professional Development in P sychology The concept of CPD evolved in the field of psychol ogy during the late 1960’s (Houle, 1980). This time period was characterized by the rapid development of new psychological techniques, methods, and orientations or a “knowledge explosion” (Ross, 1974, p. 122). Houle (1980) proposed a shift in th inking from professionalism to professionalization. Professionalism is focused on searching for absolutes or requirements that are used to define an occupation. It is a static concept that defines a profession, but it does not delineate the process t hrough which a profession continuously evolves and develops over time. However, profession alization is more focused on asking “what principles of action seem most significant to the members of a vocation as they seek to elevate and dignify its work so that it can became accepted by society as a profession” (p. 27). In summary, professionalizatio n is a dynamic conceptualization of a

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18 profession and, therefore, requires more active and on-going professional development of its members. In addition to this new conceptualization of a pro fession, pressures were exerted on health service providers to demonstrate greater accountability for the effectiveness and quality of their services in the 1970’s (Jones, 197 5). Jones (1975) noted that public dissatisfaction with methods of quality control in health care resulted in approximately 75 pieces of national health insurance legislation. Ma ny of these proposals included a review of professional standards and advocated for the est ablishment of formal CPD requirements. In fact, a United States Department o f Health, Education, and Welfare (1971) publication urged federal and state legislat ive efforts in health care credentialing to consider including mandatory continuing educatio n provisions. Jones (1975) noted that various professions such as medicine, psycholo gy, dentistry, and optometry, subsequently implemented continuing education requi rements. Additionally, legislative and regulatory boards of many professions began to specify continuing education as a requirement for license renewal in the 1970’s (Vand eCreek, Knapp, & Brace, 1990). Education also was developing the concept of profe ssional development for staff members during the 1960’s and 1970’s. Until the mid 1970’s, the term “in-service training” was used to refer to workshops conducted before school opened, state teachers’ conventions, weekend teacher institutes, or courses off campus (Dillon-Peterson, 1991). Dillon-Peterson (1991) reported that the term “staf f development” was not used until the mid 1970’s, and few school districts implemented sy stematic professional development programs. In fact, the National Staff Development C ouncil (NSDC) was not created until 1969. Since then, staff development has acquired po pularity in school districts throughout

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19 the U.S. and has been viewed as a vehicle through w hich to improve the educational system. Overall, CPD received increasing attention during the 1960’s and 1970’s and prompted professions as well as school districts to consider the importance of CPD for improving and enhancing service delivery. Federal Support for Continuing Professional Develop ment. The Eisenhower Professional Development Program (un der Title II, Part B of the 1994 reauthorization of Elementary and Secondary Ed ucation Act) was created as a federal grant program specifically intended to supp ort high-quality professional development that would provide teachers with the kn owledge and skills necessary to improve student learning (United States Department of Education, Office of the Under Secretary, Planning and Evaluation Service, Element ary and Secondary Education Division, 1999). Of note, this program was renamed the K-16 Professional Development Collaborative under Title II of the NCLB Act of 200 2. In 2000, the average amount of state grants awarded by this program was $6,352,000 (Eisenhower Professional Development Program, 2001). Through this program, m onies are available to state education agencies (SEA’s), local education agencie s (LEA’s), state agencies for higher education (SAHE’s), institutes of higher education (IHE’s), and nonprofit organizations (NPO’s) (United States Department of Education et a l., 1999). The funds are primarily used to target instruction in science and mathemati cs; however, funds also may be used to develop teachers’ skills in other academic content areas. The Eisenhower Professional Development Program advocates for high-quality prog rams that are coordinated and planned components of an on-going school district s ystem as opposed to short-term CPD methods, such as workshops.

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20 Furthermore, IDEIA (2004) provides support for oppo rtunities for professional development under Title I Part D (i.e., National Ac tivities to Improve the Education of Children with Disabilities) in order to improve edu cational outcomes of children with disabilities. The law specifically states, “high qu ality, comprehensive professional development programs are essential to ensure that t he persons responsible for the education or transition of children with disabiliti es possess the skills and knowledge necessary to address the educational and related ne eds of those children…Models of professional development should be scientifically b ased and reflect successful practices, including strategies for recruiting, preparing, and retaining personnel” (p. 118, Sec 650., 20 USC 1450). The law requires that 100% of all Sta te Improvement Grant (SIG) money be used to conduct professional development for bot h general and special education school personnel. For example, these funds may be u sed to develop mentoring programs for staff, train school personnel to conduct effect ive Individualized Education Plan (IEP) meetings, and create collaborative team problem-sol ving groups. Both the Eisenhower Professional Development Progra m and the National Activities to Improve the Education of Children wit h Disabilities provide school districts with the opportunity to implement high quality and comprehensive professional development practices. The allocation of these moni es speaks to the national recognition of CPD as a critical means for promoting successful student outcomes. Factors in School Psychology that Impact Continuing Professional Development School psychology has been recognized as a field th at has a special need for continuing professional development (Fowler & Harri son, 2001; Lam & Yuen, 2004). Hynd, Pielstick, and Schakel (1981) suggested that school psychologists may be required

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21 to update their skills every three to five years du e to the rapid changes in the field. Arguably, professional development should be viewed as an on-going process that takes place through collaboration and problem-solving wit h colleagues (NSDC, 2001). However, the main idea is that school psychologists function within a complex ecology that is greatly influenced by legal, social, profes sional, and economic factors (Sheridan & Gutkin, 2000). These ever-changing dynamics impact the profession and the manner in which services are provided (Bradley-Johnson & Dean 2000). Fagan and Wise (2000) noted that school psychologists in the 21st century do not operate the same way as school psychologists did in previous decades due to societ al changes that impact those who receive school psychological services and, in the p rocess, redefine the role of the school psychologist. School psychologists are challenged t o provide effective services and demonstrate accountability for those services in th e midst of constant societal change. Legislative changes. State and federal legislative mandates represent one salient factor that impacts the field of school psychology (Reschly, 2000). The NCLB Act (2001) requires schools to demonstrate accountabili ty for academic outcomes of all students, increased flexibility for states and scho ol districts in the use of federal education funds, the use of scientifically-based educational programs and practices, and more choice for parents. A major emphasis of NCLB is tha t schools demonstrate that all students are meeting rigorous academic standards. School districts must report Adequate Yearly Progress (AYP) data that are disaggregated b y specific student category. The categories include: (a) African American; (b) Asian /Pacific; (c) Caucasian; (d) Hispanic; (e) Native American; (f) Economically Disadvantaged ; (g) Student with Disabilities; and (h) English Language Learners. Each year schools mu st meet performance targets in

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22 reading and math in order to demonstrate that they are on track to meet 100% proficiency by the 2013-14 school year. This piece of legislati on has significant implications for student support services personnel, including schoo l psychologists, who are now required to demonstrate that programs, interventions, and se rvices delivered are linked to academic progress and the attainment of state and n ational standards. In alignment with NCLB, the reauthorization of the IDEA (1997), as well as the Individuals with Disabilities Education Improvement Act (IDEIA) (2004), maintained the basic structure of IDEA but included new requiremen ts regarding how schools can determine whether a child has a specific learning d isability. The IDEIA allows schools to use data-based evidence regarding how well a studen t responds to scientifically-based interventions (commonly referred to as Response to Intervention [RtI]) to decide on the presence or absence of a specific learning disabili ty (Brown-Chidsey, 2005). Response to Intervention was proposed as an alternative to wide ly used model that is based on documentation of a significant discrepancy between cognitive ability and academic achievement. Response to Intervention is an approac h to delivering services at increasing levels of intensity (Florida Department of Educatio n, 2005). Evidence-based interventions are continued, modified, or dropped b ased on the student’s data-based response to the intervention. One of the major goa ls of RtI is to assess whether students are being exposed to an effective curriculum and re ceiving adequate instruction, which will enable them to meet academic standards and ben chmarks. Response to Intervention is in alignment with NCLB (2001) and IDEIA (2004) b ecause it focuses on delivering effective instruction in the general education clas sroom, emphasizes the use of evidencebased interventions, uses data to make educational decisions, and de-emphasizes labeling

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23 students (Vaughn & Fuchs, 2003). In general, NCLB (2001) and IDEIA (2004) require that states and school districts demonstrate that t he services they provide lead to academic competence and achievement for all student s. School psychologists play a critical role in ensuring that schools are in compl iance with these laws, and, more importantly, that students receive appropriate serv ices that will help them academically succeed. For a thorough discussion of the impact of IDEA on school psychology see Reschly (2000). Demographic changes The Current Population Survey (CPS), conducted by the United States Census Bureau in 2003, indicated that more than one-fourth, or 74.9 million people, of the United States population age d 3 and older attended school (Shin, 2005). Between the years of 1983 and 2003, the num ber of children enrolled in elementary (Grades 1-8) and high school (Grades 9-1 2) increased by 8 million (i.e., from 41.2 to 49.6 million). Between the years 2001 and 2013, the National Center for Education Statistics (2003) projected a 5% increase in school enrollment in both public and private sectors. Factors that contribute to the se projections include internal migration, legal and illegal immigration, and the high level o f births in the 1990’s. The field of school psychology also is challenged t o meet the needs of an increasingly diverse student population. Shin (2005 ) reported that elementary and high school students are more diverse today as compared to the “baby boom” generation. In 1970, the United States student population was 79% non-Hispanic White, 14% Black, 6% Hispanic, 1% Asian/Pacific Islander and Other. In 2 003, data indicated that 60% were non-Hispanic White, 16% Black, 18% Hispanic, and 4% Asian. This trend in increasing percentages of racial/ethnic minority students is e xpected to continue in the future (Shin,

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24 2005). In fact, by 2025 it is estimated that one-qu arter of all United States public school students will be Latino (Gregory, 2003). It also is estimated that over 6 million children in the United States will be English Language Learn ers by the year 2020 (Ysseldyke et al., 2006). These demographic changes will require that school psychologists and the greater educational system implement culturally sen sitive instructional practices in schools (National Center for Culturally Responsive Educational Systems, 2005). Increases in student enrollment along with greater racial/ethnic and cultural diversity create a pressing need for school psychol ogical services that actively address this diversity. As Baker, Kamphaus, Horne, & Winsor (2006) indicated, the increasing diversity of the student population will result in variability in children’s academic performance and behavior in the classroom. School p sychologists should acquire skills and competencies that will enable them to adapt to these changing student enrollment conditions (Ysseldyke et al., 2006). Professional Organizations and Continuing Professio nal Development The need for CPD has been recognized by professiona l psychological associations. The NASP (2000), APA (1981), and Inte rnational School Psychology Association (ISPA) (Oakland, Goldman, & Bischoff, 1 997) have established guidelines and ethical principles for the delivery of psycholo gical services. These guidelines recommended that providers of psychological service s maintain professional competency in order to responsibly and ethically provide servi ces to clients. Each of these professional organizations included CPD as a core c omponent of competent and ethical practice. The NASP Guidelines for the Provision of School Psychological Services (2000) specifically delineated CPD as a central com ponent of ethical and professional

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25 conduct in the schools (as specified in Unit Guidel ine 5: Supervision and Unit Guideline 6: Professional Development and Recognition Systems ). The APA Specialty Guidelines for the Delivery of Services by School Psychologist s (1981) specifically required that school psychologists maintain current knowledge to preserve and enhance professional competence (Guideline 1.5). The Code of Ethics of t he ISPA identified professional growth (Professional Standard III) as a core value and principle of school psychology practice (Oakland et al., 1997). Furthermore, the School Psychology: A Blueprint for Training and Pr actice III (Ysseldyke et al., 2006) provided the field with a framework to guide training and practice in school psychology. The blueprint conten t was revised due to the numerous legislative changes, a need for a safer school clim ates and mental health services (e.g., as a result of school violence across the United State s), and the expanding role of school psychologists. The task force (Ysseldyke et al., 20 06) for the blueprint indicated that school psychology training and practice is focused on achieving two goals: (a) improving competencies and skills of all students; and (b) bu ilding capacity via systems change to create or improve systems that will most efficientl y and effectively serve students and families. Ysseldyke et al. (2006) suggested that th ese goals can be achieved as practitioners develop their skills and competencies and integrate them into daily practice. It is expected that school psychologists will conti nually work toward higher levels of competence during their careers. There are eight co mpetency domains (as stated previously in Chapter I) that are divided into foun dational (i.e., competencies/skills which are build upon in practice) and functional (i.e., c ompetencies/skills that are exercised in practice) competencies. Continuing professional dev elopment is specifically cited in the

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26 Professional, Legal, Ethnical, and Social Responsib ility foundational domain. This domain indicated that it is the school psychologist ’s ethical and professional responsibility to engage in CPD in order to stay cu rrent and adapt to the societal trends/movements that impact the field. More import antly, CPD is seen as a lifelong process in which the blueprint may be used to guide personal and systems-level professional development. Ysseldyke et al. (2006) s tated that the competencies should be viewed as an “integrated set of competencies that w ill require lifelong learning” (p. 2). This suggests that CPD is seen as more than just se parate, disjointed activities, but, rather, as a lifelong pursuit of knowledge that occ urs at both the individual and systems level. The Nationally Certified School Psychologist Contin uing Professional Development Program. According to NASP (2003), the current NASP Continui ng Professional Development Program provides all membe rs an opportunity to grow professionally through participation in a variety o f CPD activities. School psychologists are encouraged to develop a personal plan to guide the selection of CPD activities. Specifically, the program is targeted for those sch ool psychologists who hold the Nationally Certified School Psychologist (NCSP) cre dential. The CPD program requires the completion of 75 clock hours of CPD activities within a three-year period to renew the NCSP credential. Renewal of the NCSP requires the documentation and maintenance of records of CPD activities. Applicants who wish to renew their NCSP credential are subject to a random audit wherein they are required to provide documentation so that the National School Psychology Certification Board can verify the completion of the required CPD activities. The applicants who receiv e an audit have 60 calendar days from

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27 the date of notice to document the 75 CPD credits. Continuing professional development activities are recognized by the national certifica tion system according to the following categories: (a) Group A: Workshops, conferences, and in-service training; (b) Group B: College and university courses; (c) Group C: Teach ing and training activities; (d) Group D: Research and publications; (e) Group E: Superv ision of interns; (f) Group F: Postgraduate supervised experiences; (g) Group G: Program planning and evaluation; (h) Group H: Self study; and (i) Group I: Leadership i n professional organizations. A detailed explanation of CPD requirements, documenta tion procedures, and activities is provided in the NCSP Renewal Guidelines (NASP, 2003 ). The National Staff Development Council’s Standards for Staff Development. Although the NSDC standards for professional develo pment do not guide CPD initiatives or practices in the field of school psychology, the y provide a useful framework through which to view effective CPD. The NSDC “recognizes that sustained, intellectually rigorous staff development is essential for everyon e who affects student learning” (NSDC, 2001, p. 2). Presumably, this includes schoo l psychologists because they both directly (e.g., counseling services) and indirectly (e.g., consultation with teachers, system-level change) impact student learning. There fore, these standards are deemed appropriate for inclusion in a discussion of the fi eld of school psychology. One of the guiding principles of the NSDC is that “improvement is always unfinished” (p. 3). Therefore, individuals, groups, schools, and school districts can utilize these standards in an effort to continuously improve outcomes for stud ents. The NSDC (2001) advocated for comprehensive profess ional development that addresses the following three essential standards, which collectively can lead to student

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28 learning and improved outcomes: (a) context (e.g., resources available, incentives for school psychologists to participate in professional development, district leadership, and presence of problem-solving teams); (b) process (e.g., conditions under which learning occurs, collaboration, using student data to determ ine adult learning priorities, and strategies to engage school psychologists as adult learners); and (c) content (e.g., the skills and knowledge that professionals need in ord er to ensure successful student outcomes) (Guskey & Sparks, 1996). These three cor e standards are deemed essential for the creation of a social climate that promotes both individual and system-level professional development. Ryan and Deci (2000) argu ed that participation in social contexts, or climates, can promote active engagemen t that may lead to enhanced motivation and well-being. The authors contended th at these social contexts can be constructed in such a way as to facilitate positive outcomes for staff (e.g., intrinsic motivation, personal/professional development, and self-regulation of behavior). They provided evidence that indicated social contexts th at are: (a) supportive of professional autonomy; (b) provide opportunities for professiona ls to experience connectedness/relatedness to others; and (c) provid e the necessary supports to allow professionals to develop competence (e.g., assuring that professionals have the prerequisite skills to learn new material, providin g support via mentoring/coaching) are more likely to foster such positive outcomes for pr ofessionals and strengthen the working environment. As is illustrated below, the NSDC stan dards reflect these critical elements. The NSDC (2001) suggested that an effective context for professional development includes: (a) learning communities; (b ) leadership; and (c) resources. These three requirements are deemed necessary to create a climate that facilitates CPD. First,

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29 the creation of learning communities organizes staf f into teams that collaborate and meet on a regular basis to examine achievement standards /benchmarks, problem-solve issues related to student achievement, and determine profe ssional development needs. These learning communities are core problem-solving units that promote ongoing discussion and support regarding student learning and achievem ent. These communities provide an important opportunity for staff to interact with ea ch other on a frequent basis and create a sense of community, trust, and competence. Communit ies may consist of administrators, teachers, or other staff members. Second, leadership includes leaders at all levels ( e.g., district, school, and classroom) who guide the development and implementa tion of professional development initiatives. Moreover, leaders provide the necessar y guidance, vision, and support to see that CPD initiatives come to fruition. A systems-le vel vision is often required to implement successful professional development on a larger scale. School psychologists have been cited as potential leaders who can foster and develop CPD initiatives within the school system because they possess a diverse ra nge of knowledge and skills (Lau et al., 2006; Ross, Powell, & Elias, 2002). Youngs and King (2002) investigated the role of the principal’s leadership in the process of school -wide professional development and building the school’s capacity for change. Results from a multiyear, qualitative investigation of four urban public elementary schoo ls indicated that a strong principal leader can foster a capacity for change by encourag ing staff to establish shared goals for student learning, collaborate and problem-solve to reach decisions, and exert influence and/or control over their work. Schools whose CPD e fforts lead to improved academic outcomes all had principals who facilitated the cha nge process in the previously noted

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30 ways. Overall, the results suggested that the princ ipal can assume a leadership position that gradually builds a school’s capacity for chang e, which can indirectly impact student learning and adult professional development. Finally, the availability of resources (e.g., alloc ation of funds) is considered an integral component of CPD in order to support distr ict-wide professional development initiatives and action plans. The NSDC (2001) advoc ated that school districts allocate at least 10% of their budget to staff development and that at least 25% of time be devoted to professional learning and collaboration. However, N SDC reported that many schools actually allocate only 1% or less to professional d evelopment. Glickman, Gordon, and Ross-Gordon (2001) offered an analogy that illustra tes the commitment of school districts to CPD: When a customer purchases a new car costing upwards of $30,000, he or she brings it in every 5,000 miles for preventative mai ntenance and fine-tuning. The customer continues to put additional money into the car to prolong its life and performance. Simply to run the car into the ground would be a dumb way to protect such an investment! In education, the schoo l board is the customer, who purchases more than a new car with its $30,000 init ial investment—it purchases a living and breathing professional! Without resource s for maintaining, fine-tuning, and reinvigorating the investment, the district wil l run teachers [and arguably other school professionals] into the ground. This i s far more consequential than a neglected car. The district will lose teachers, phy sically and/or mentally. The real losers will be the students of these teachers (p. 3 60).

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31 However, Glickman et al. (2001) reported that state s have increased their expenditures on CPD in local school districts since the series of n ational reports regarding CPD in the mid-1980’s. Resources may be used to hire trainers, part-time coaches, external consultants, or substitute teachers (e.g., to fill in for teachers while they receive training) to facilitate the adult learning process. Additiona lly, resources can provide stipends to teachers who attend professional development traini ng. Overall, learning communities, leadership, and resources are three components that create an appropriate context for professional development. The NSDC (2001) advocated that the process of professional development incorporate the following components: (a) conduct d ata-driven assessment and evaluation; (b) evaluate the effectiveness of CPD e fforts; (c) apply research to the decision-making process; (d) utilize appropriate an d varied adult learning strategies; and (e) collaborate with colleagues. These elements des cribe best practice principles in how to conduct professional development in the school s etting. A brief description of each component is presented below. First, data-driven professional development entails using disaggregated student data (e.g., standardized tests, work samples, disci plinary action reports, grade retention statistics) to determine adult learning objectives and priorities. Student data are used to guide adult professional learning, as well as to as sess and evaluate professional development goals for summative and formative infor mation. Lastly, data may be used to motivate staff as they see that CPD efforts are pos itively impacting student performance. Second, effective professional development efforts utilize information from multiple sources in order to evaluate the quality a nd impact of CPD. The NSDC (2001)

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32 suggested that evaluation go beyond initial thought s and reactions to workshops and include assessments of skill acquisition (e.g., rou tine classroom observations, anecdotal information), examinations of student data (e.g., p rogress monitoring, tracking disciplinary records), or reviews of professional p ortfolios. Notably, the NSDC indicated that those receiving evaluation data (e.g., groups or individual teachers) need to have the prerequisite knowledge to interpret data. Lastly, t he NSDC stressed that different audiences will require varying forms/types of data in order to satisfy their specific concerns. They recommended that the following frame work be completed as a useful exercise to facilitate this process (p. 19). Table 1 Framework Used to Acquire Data from Multiple Source s ___________________________________________________ _____________________ Decision Makers Typical Questions Data Sources fo r Responses 1. School Board 2. Superintendent 3. Principals 4. Teacher Leaders 5. Parents 6. Business Partners Third, effective professional development requires that staff apply research to the decision-making process. Staff should critically ex amine the research and make informed decisions regarding practices that will promote stu dent achievement. For example,

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33 schools may invite researchers to present to school staff, forge university partnerships, or visit other model schools in order to create and su stain a culture of inquiry and research. The NSDC (2001) suggested that schools conduct pilo t studies to determine the effectiveness of research-based curricula or progra ms prior to large-scale implementation. Research is considered to be a staple of CPD effort s because it will inform and guide decision-making throughout the process. Fourth, effective CPD recognizes that adult learni ng strategies must be utilized in order to meet individual, group, and district goals The NSDC (2001) suggested the use of varied strategies to promote learning, such as c ollaboration with colleagues, study groups, professional associations, online support n etworks, internet-based learning, live/video modeling, or feedback sessions. The main goal is to use learning strategies that allow staff to gradually incorporate what they have learned on a routine basis. Adult learning strategies should entail more than one tim e workshop or presentations, but, rather, include a carefully selected combination of learning strategies that best fit the needs of the staff. The NSDC stated that adult lear ners must have a deep understanding of what they learn and that “such deeper understanding typically requires a number of opportunities to interact [and practice] with the i dea or procedure through active learning processes that promote reflection such as discussio n and dialogue, writing, demonstrations, practice with feedback, and group p roblem-solving” (p. 24). Joyce and Showers (1988, 2002) demonstrated that CPD for teac hers was most effective if training included information, theory, demonstration, practi ce feedback, and coaching. Collectively, all of these training elements lead t o greater transfer of skills in the classroom. Joyce and Showers (2002) argued that tra nsfer of training to the classroom is

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34 essential for CPD to have a direct and positive imp act on student outcomes. Furthermore, Lankard (1995) also argued that it is critical to p romote learning in the workplace via linking study to practice, providing opportunities for reflection, and programming for transfer of knowledge to different situations. Thes e methods of learning serve to enhance adult learning and, ultimately, the processes that impact student achievement. Lastly, the NSDC (2001) suggested that collaborati on with colleagues is one of the most important types of professional developmen t within the school setting. The goal of collaboration is to provide an interpersonal con text that is supportive and fosters a culture of problem-solving and data-based decisionmaking. The NSDC stated that CPD efforts should focus on arming staff with the appro priate knowledge (e.g., group processes, stages/phases of group development) and skills (e.g., conflict resolution, consensus building) in order to form and participat e in school-based teams. Teams may consist of administrators, teachers, or a combinati on of staff employees. Additionally, they noted that technology, such as the internet, l ist serves, and web conferences also may enhance collaboration among colleagues from var ying demographic regions. King (2002) demonstrated the importance of collective te acher inquiry, which occurs when teachers collaborate to systematically discuss and critique professional practices as they relate to student outcomes. More specifically, King stated that effective teams have “considerable control over process and content of C PD [and] critically discuss issues related to the school mission, curriculum, instruct ion, or student learning, address areas of disagreement and entertain diverse viewpoints, draw upon relevant data and research to inform deliberation, and sustain a focus on a topic or problem, and reach a collective decision” (p. 246). Arguably, school psychologists are an integral part of the collective

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35 inquiry process and can acquire CPD benefits from p articipation. The inquiry process should reflect the issues and norms specific to tha t local community (NCSD, 2001). Overall, data-driven assessment and evaluation, sum mative and formative evaluation of CPD efforts, application of research to the decisio n-making process, implementation of effective adult learning strategies, and collaborat ion are process-oriented components that can facilitate professional development in the scho ol setting. Finally, content is another necessary component of comprehensive pro fessional development. Content refers to what topics, issues, or learning objectives will be the focus of professional development efforts. This com ponent includes the following: (a) equity; (b) quality teaching; and (c) and family in volvement. Equity means that school personnel establish effective teaching practices (e .g., differentiating instruction, addressing students’ cultural backgrounds), create safe environments that foster socialemotional development, establish behavior managemen t practices that promote selfregulation/management, and communicate high expecta tions for all students. This may entail implementation of school-wide positive behav ioral support or evidenced-based curriculum program empirically tested with a divers e population of students. Second, successful professional development promote s quality teaching practices that include a deep understanding of subject area c ontent, use of appropriate and evidence-based instructional methods, and applicati on of multiple assessment strategies. Professional development for staff may include summ er institutes, university coursework, study groups, classroom coaching, or observations o f demonstration lessons. These learning strategies are specifically geared toward learning instructional methods and assessment tools that will allow students to meet a cademic standards. Additionally, the

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36 NSDC (2001) stated that instructional leaders (e.g. administrators) are responsible for aligning curriculum, instruction, and assessment st rategies as well as creating a culture of continuous learning and improvement. Lastly, meaningful family involvement requires th at administrators and staff actively engage both families and community members in efforts to improve student learning. For example, partnerships may be forged w ith parents, local businesses, or community agencies. It is essential that these part nerships establish mutual goals and communicate respect for different perspectives and/ or opinions. Overall, the NSDC (2001) deemed it important that the school, home, a nd community collectively support student learning while respecting the differences t hat may arise as these relationships are sustained over time. In summary, the NSDC (2001) presented three core st andards of context process and content necessary for effective professional development to improve student learning. These standards may be utilized by indivi duals, groups, schools, school districts, or state departments of education to gui de professional development efforts. The NSDC stated that professional development is no lon ger the sole responsibility of a designated “staff developer” or “professional devel opment coordinator”, but it is the responsibility of all those who impact student lear ning (p. 2). Empirical support for the National Staf f Development Council Standards. In reviewing the research literature on professional d evelopment from the 1970’s through the 1990’s, Glickman et al. (2001) identified the f ollowing characteristics of effective professional development programs:

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37 (a) involvement of participants in planning, implem enting, and evaluating programs (b) programs that are based on school-wide goals bu t that integrate individual and group goals with school goals (c) long range planning and development (d) programs that incorporate research and best pra ctice on school and instructional improvement (e) administrative support, including provision of time and other resources as well as involvement in program planning and delivery (f) adherence to the principles of adult learning (g) attention to the research on change, including the need to address individual concerns throughout the change process (h) follow-up and support for transfer of learning to the school or classroom (i) ongoing assessment and feedback (j) continuous professional development that become s part of the school culture (p. 363). Glickman et al. (2001) provided detailed case examp les of school districts that have incorporated these elements into successful compreh ensive CPD programs. Additionally, other studies have described CPD initiatives that h ave included many of these characteristics of effective CPD, which were found to be associated with positive outcomes, such as decreases in the percentage of st udents determined eligible for special education services (Lau et al., 2006) and increased knowledge and use of reading

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38 interventions by classroom teachers to improve stud ent learning outcomes (Truscott & Truscott, 2004). Support for the NSDC standards is offered by the Am erican Institutes for Research (AIR) based on their evaluation of the Dwi ght D. Eisenhower Professional Development Program (Garet et al., 1999). The AIR e valuated the program via intensive case studies of 10 school districts located in Ohio New York, Kentucky, Texas, and Washington, a national sampling of district Eisenho wer coordinators, directors, and teachers to assess the current status of the progra m (i.e., The National Profile), and a longitudinal study of science and mathematics teach er change from 30 schools (i.e., data collected from 1996 through 1999). Overall, the dat a suggested that the impact of CPD was stronger when district programs reflected the f ollowing six quality indicators: (a) utilized “reform” type of CPD (e.g., teacher networ k, study group, peer coaching) versus a traditional approach (e.g., workshop); (b) sustai ned CPD over time; (c) involved groups of teachers who collaborated from the same school, grade, and/or department; (d) incorporated active adult learning principles; (e) focused on specific content and effective teaching strategies; and (f) ensured that teachers’ CPD goals and activities were in alignment with building-wide, district, state, and national goals. These findings by the AIR were consistent with prev ious professional development research in that effective CPD is syste matic, goal directed, aligns with state and national standards, and meets the needs of both teachers and students. As a result of this research, the Eisenhower Professional Developm ent Program has emphasized its support for districts that systematically plan CPD that addresses both individual teachers (or school practitioners in general) and school-wid e goals designed to improve student

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39 learning. Undoubtedly, school psychologists are int egral school district employees who also would benefit from a comprehensive, adult lear ner centered CPD program. Research by Lowden (2005) provided additional suppo rt for the NSDC standards. The purpose of the study was to examine the charact eristics of professional development programs in K-12 public schools and how they relate d to teacher change. Participants included 250 teachers who represented 11 schools. P articipants completed and returned surveys via mail. Results indicated that effective professional development: (a) was linked district goals and school improvement; (b) w as aligned with teacher evaluation processes; (c) was offered during the school day; ( d) consisted of individual CPD plans, guided practice, reflection, mentoring, district cu rriculum development, peer study groups, and long-term courses with district support ; and (e) addressed content that was determined by school and community stakeholders. Th ose teachers who rated their professional development experiences as effective ( i.e., endorsed a majority of above characteristics) reported more satisfaction, learni ng, organizational support, positive change in knowledge and skills, positive teacher pe rceptions of student learning, and positive attitudes and beliefs as compared to those who reported participating in professional development characterized as ineffecti ve. Garet, Porter, Desimone, Birman, and Yoon (2001) pr ovided further support for the NSDC standards. They examined professional deve lopment factors that increased positive teacher self-reported outcomes. Participan ts included a national sample of 1,027 mathematics and science teachers who participated i n the Eisenhower Professional Development Program to compare selected characteris tics of professional development and their relationship with teacher self-reported l earning (i.e., increase in knowledge and

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40 skills and changes in classroom teaching practices) Teacher outcome measures included ratings on the impact that CPD had on their knowled ge and skills as well as the extent to which they perceived themselves changing their teac hing practices in six domains (e.g., instructional methods, use of technology to facilit ate student learning). Results indicated that a focus on specific content knowledge, opportu nities for active learning with colleagues, and CPD initiatives coherent with distr ict and state standards were necessary core conditions for effective professional developm ent. The combination of these core conditions and the following variables significantl y impacted teacher learning: (a) reform CPD activity (e.g., peer coaching as opposed to mor e traditional types of CPD); (b) collective participation for the same grade, school or subject; and (c) sustained CPD efforts (i.e., provided an opportunity for discussi on and debate and allowed teachers to practice what they learned). Overall, results indic ated that CPD that is sustained, intensive, focused on content knowledge, provides o pportunities for active learning, and is integrated into everyday practices in the school setting is more likely to result in enhanced knowledge and skills. Furthermore, results suggested that it may be important to concentrate on the core conditions (i.e., conten t, active learning, consensus on goals/vision), duration of CPD, and collective part icipation rather than focusing on the type (i.e., reformed versus traditional) of CPD act ivity. Milne et al. (2003) demonstrated that these core co nditions may be more influential than the actual type of CPD format or a ctivity. They investigated the effectiveness of an evidence-based staff training p rogram. Participants included mental health staff who worked in a residential setting fo r clients with severe mental health concerns. The participants were assigned to either a training group (n= 18) or control

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41 group (n=7). The 10-day experiential workshop cover ed the following topics: functional analysis, behavioral interventions, and staff selfregulation and support systems. Prior to training, participating staff were interviewed indi vidually to assess their attributions regarding challenging client behavior as well as pe er/management support needs. Outcome measures included eight instruments that we re used to evaluate the process, outcome, and organizational context of the training Results indicated: (a) significant improvement in participants’ knowledge and skills ( as evidenced by higher scores on the knowledge quiz and video-based exercise); and (b) s ignificantly more self-reported use by participants of the methods they learned six to nine months after the training as compared to prior to training. Facilitators of tran sfer of training included: (a) organizational support; (b) involvement of all staf f in the training; (c) consistent and onsite support from trainers; (d) continuity of the s taff; and (e) support from colleagues. Overall, transfer of training occurred because trai ning was integrated into participants’ daily routine. In summary, the NSDC (2001) provided a specific set of standards to help guide the development of comprehensive professional devel opment programs in school settings. These standards may be utilized by a wide range of individuals from state department administrators to individual school psyc hologists. The NSDC standards are supported by empirical research demonstrating that effective CPD efforts are characterized by specific elements. The presence or absence of these elements may influence the extent to which professional developm ent initiatives are actualized in practice.

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42 Practices and Perceptions of Continuing Professiona l Development by School Psychologists Continuing professional development is cited as cri tical in advancing the profession of school psychology to meet the increas ing needs of students and families (Chafouleas et al., 2002; Crepsi & Rigazio-Digilio, 1992; Dawson et al., 2003; Fowler & Harrison, 2001; Lam & Yuen, 2004; Macklem et al., 2 001; Murphy, 1981; Nastasi, 2000; Rosenfield, 1981; Swerdlik & French, 2000). However few empirically-based studies have solely investigated the CPD activities of scho ol psychologists, demographic characteristics, professional practice, or employme nt condition variables related to CPD, and perceptions of CPD by school psychologists (Fow ler & Harrison, 2001; Lam & Yuen, 2004). Numerous studies have examined supervi sion of school psychologists (Chafouleas et al., 2002; Fischetti & Crespi, 1999; Ross & Goh, 1993; Zins et al., 1989); however, supervision is only one type of CPD (Lam & Yuen, 2004). Additionally, some studies (Chafouleas et al., 2002; Reschly & Connoll y, 1990; Ross & Goh, 1993; Watkins et al., 1991) have examined CPD as a “by product” o f their primary subject of interest (Fowler & Harrison, 2001, p. 76). Overall, few stu dies have emerged in an effort to address the limited knowledge base. The following s ections will detail empirical studies of CPD in relation to demographic characteristics, professional practices, and employment conditions of school psychologists. Continuing professional development practices. Fowler and Harrison (2001) examined the CPD needs of 235 school psychologists and their relationship with demographic, preservice training, and incentive var iables. Furthermore, the study

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43 investigated the types, amount, and frequency of CP D activities, as well as the relationship between the CPD needs of school psycho logists and their actual engagement in CPD activities. Demographic variables examined i ncluded age, gender, professional credentials, marital status, parental status, and y ears of experience in school psychology. Preservice training variables included degree level recency of school psychology degree, preservice training program accreditation/approval, preservice training in CPD selfmanagement, and preservice training in aspects of C PD management (e.g., selecting and stating CPD goals, selecting learning options to me et CPD goals). Incentive variables included credentialing purposes, employer incentive s for engaging in CPD, and personal needs and interests (e.g., opportunity for self-ass essment of CPD needs, opportunity to practice new skills and receive feedback during CPD training). Participants worked in school settings and their characteristics were repo rted to be comparable to the 1994-1995 Regular NASP membership as reported by Curtis, Hunl ey, Walker, & Baker (1999). A survey was mailed to 500 Regular NASP members reque sting information relating to: (a) demographic characteristics; (b) preservice trainin g; (c) incentives for CPD; and (d) typical CPD activities completed. Participants also were asked to complete a rating scale of CPD needs based on the six areas of skill develo pment as delineated in the NASP Guidelines for the Provision of School Psychologica l Services (NASP, 1997). Frequency data indicated that the most commonly end orsed incentives for CPD included paid leave time for training and paid leav e with monetary reimbursement for CPD-related expenses. Participants rated personal C PD needs and interests as being likely to influence CPD involvement. Personal need s and interests included an opportunity to: (a) conduct a self-assessment of CP D needs; (b) provide input when

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44 developing CPD goals and objectives; (c) select lea rning options to meet personal CPD needs; (d) practice new skills and receive feedback during CPD training; and (e) evaluate CPD training and goal attainment. Participants mos t commonly reported engaging in self-study and attending workshops, institutes, and in-service training programs. More than 90% of respondents reported attending in-servi ce programs and workshops within the preceding year. Approximately 71% of the respon dents reported participating in CPD activities ranging from 21 to 41 or more clock hour s during the preceding year, with 43.2% engaging in CPD activities on a quarterly bas is and 27.8% on a monthly basis. Participants also identified their CPD needs using a 5-point Likert-format scale in the areas of assessment, consultation, direct servi ce, program planning and evaluation, research, and supervision (1 = no CPD needed; 5 = e xtensive CPD needed). Subscale mean scores indicated that school psychologists rat ed direct service (2.96) and consultation (2.94) as the areas of greatest CPD ne ed. Other areas included supervision (2.65), program planning and evaluation (2.57), res earch (2.54), with assessment being reported as the lowest area of need (2.49). Additio nally, respondents identified moderate to high levels of CPD need (i.e., defined as items rated by 50% or more of the sample as 3 or higher) within each area. Respondents rated a ll eight areas in the consultation subscale as reflecting moderate to high CPD needs. Behavioral consultation (77.4%) and educational consultation (70.2%) were identified as being moderate to high need areas most frequently. Six out of seven items in the dir ect service subscale were endorsed by respondents, wherein interventions for individuals (80.9%) and interventions for affective development (78.3%) were endorsed most frequently. Notably, no items on the supervision subscale were rated as moderate to high CPD need.

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45 Continuing professional development needs and their relationship with demographic, preservice training, and incentive var iables were examined using a oneway analysis of variance (ANOVA). Results indicated no significant relationship between any demographic variable and perceived CPD needs. In addition, no significant differences were found for CPD needs based on degre e level, training program accreditation/approval, recency of preservice train ing, credentialing, or employer incentives for CPD. However, significant group diff erences were found for one preservice training factor, perceived value of CPD management training in the areas of assessment, direct service, and research. On the ot her hand, most respondents (89.3%) reported that they had not received CPD management training in their graduate programs even though 83% of them expressed the belief that t his training has value. Interestingly, school psychology researchers have advocated for sc hool psychologists being taught how to create a self-managed CPD plan during graduate t raining since the 1980’s. For example, Rosenfield (1981) recommended that school psychologists should set clear CPD goals based on personal professional needs as o pposed to haphazardly selecting activities that are not a part of an integrated CPD plan. Fowler and Harrison (2001) also reported that their analyses indicated that numerous personal incentive items were related to p articipants’ reported CPD needs. Specifically, opportunity for self-assessment of CP D needs was found to be significantly related to perceived CPD needs in the area of super vision. Opportunity to practice new skills and receive feedback was significantly relat ed to perceived CPD needs in direct service and research areas. The opportunity to eval uate CPD training and goal attainment

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46 was significantly related to participants’ CPD need s in the areas of direct service and supervision. Furthermore, results revealed that school psycholog ists’ reported CPD needs in each skill area (i.e., direct service, consultation assessment, program planning and evaluation, supervision, and research) were signifi cantly related to the actual amount of CPD activity in which they engaged, with correlatio ns ranging from .16 to .23 (p < .001). However, Fowler and Harrison (2001) noted that thes e correlations were small and of little practical significance. Lastly, the particip ants perceived CPD needs were not related to frequency, amount, or type of CPD activity. The researchers speculated that this finding emerged because these particular school psy chologists engaged in frequent and large amounts of CPD that were similar in type (i.e ., workshops and in-services). Overall, participants reported frequently engaging in more traditional forms of CPD primarily in the areas of direct service, consu ltation, and assessment. For example, 90% of participants reported attending in-service t raining programs and workshop within the preceding year. The highest CPD needs in were found to be in the areas of consultation and direct service. Specifically, the highest needs were found in interventions for individuals, groups, and affectiv e development as well as in behavioral, mental health, and educational consultation. Few si gnificant relationships were found between CPD needs and demographic, preservice train ing, and incentive variables. However, significant differences were found for per ceived value of preservice CPD management training in the areas of assessment, dir ect service, and research despite the finding that few participants reported receiving tr aining in CPD management. This suggests that CPD training (e.g., goal setting, see king out CPD opportunities) may be an

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47 important component of preservice training in order to prepare professionals to address their future CPD needs in the workplace. Personal i ncentives for CPD were related to the CPD needs of participants. The opportunity for self -assessment was found to be related to supervision needs. The opportunity to practice new skills and receive feedback was related to direct service and research needs. The o pportunity to evaluate CPD training and goal attainment was related to needs in direct serv ice and supervision. These findings suggest that CPD may be more meaningful and effecti ve when school psychologists are actively engaged in planning their CPD and have mor e control and decision-making power over CPD activities. Perceptions of continuing professional development. Guest (2000) investigated the career development of school psychologists and their perceptions of CPD. Twentyfive structured interviews were conducted with scho ol psychologists from various racial/ethnic backgrounds. Results indicated that participants did not conceptualize or organize their careers in terms of distinct stages. The researchers hypothesized that school psychology is a unique profession due to env ironmental factors, such as legislation, changes in student demographic charact eristics, and national disasters that impact children and families. These factors contin ually change role demands and expectations of school psychologists. Therefore, school psychologists may not follow an orderly, projected career development path. The res earchers suggested that school psychologists’ careers may be a series of short “mi ni careers” (p. 251). This hypothesis received some support in that results indicated tha t more seasoned school psychologists reported role changes over time. They reported more emphasis on consultation during the 1960’s, followed by a transition to a more traditio nal assessment role during the 1970’s

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48 and 1980’s, and then a recent movement to an expand ed role (e.g., consultation, systems change). Participants identified CPD as being one o f the most significant influences on their professional growth. The participants reporte d engaging in workshops, in-service training programs, conferences, and personally guid ed professional reading. Many participants reported that non-traditional CPD acti vities, such as working in non-school settings or being trained in organizational develop ment, had a lasting and meaningful impact of their professional development. Results related to supervision indicated that 64% o f the respondents reported having one or more persons who they considered to b e mentors during their careers; however, 36% recalled no mentors, but indicated tha t mentors would have been helpful, if available, early in their career. Most of the m entoring experiences reported by participants were informal in nature. Many school psychologists reported that they were “thrust into the field on their own” (p. 245). Onl y 8% of the respondents reported having had a formal mentor assigned to them when they ente red the field. Those did not have a mentor assigned said they would have liked regular meetings with mentors, weekly meetings to discuss cases, and help with organizati onal facets of the job. It was important for the respondents to consult with other school psychologists concerning issues other than administrative issues (i.e., prof essional). In summary, this study revealed that these particul ar school psychologists believed CPD was an important component of their wo rk and that both traditional and non-traditional forms of CPD were important to thei r career development. However, nontraditional CPD had a greater impact on the partici pants’ professional growth. They perceived their career paths as being a series of “ mini careers” (p. 251) (as opposed to a

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49 fluid, straightforward process), which may suggest that school psychologists’ CPD needs are more contingent upon contextual factors and are changing and dynamic over time. Furthermore, this study revealed that participants received minimal supervision and career guidance. Supervision McIntosh and Phelps (2000) define supervision withi n the field of school psychology as, Supervision is an interpersonal interaction between two or more individuals for the purpose of sharing knowledge, assessing profess ional competencies, and providing objective feedback with the terminal goal s of developing new competencies, facilitating effective service delive ry of psychological services, and maintaining professional competencies (p. 33-34). Little attention has been given to supervision in t he school psychology literature. Bahr et al. (1996) conducted a literature search us ing the PSYLIT database over the 15 years between 1982 and 1996 and found 34 references relating to school psychology, as compared to 100 in counseling psychology, 125 in cl inical psychology, and 468 in counselor education references. Despite the limited research base, studies examining supervision are essential to the examination of CPD because supervision is essential to the professional development of school psychologist s (Chafouleas et al., 2002; NASP, 2000, APA, 1981; Murphy, 1981; Ross-Reynolds & Grim es, 1981). Supervision provides the opportunity for ongoing professional developmen t as the professional is ideally challenged to improve their practices and be held a ccountable for their work (Knoff, 1986; Knoff, Curtis, & Batsche, 1997). However, the bulk of supervisory activities is

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50 administrative rather than clinical in nature and i s not directly linked to the provision of effective services in the schools (Murphy, 1981). A s Murphy (1981) noted, “evaluation, of course, is not synonymous with supervision”, (p. 423) which means that supervision is far more comprehensive and complicated than yearly paper and pencil evaluations. Instead, supervision is a process that ideally fost ers and promotes the professional development of the supervisee. Supervisors are requ ired to fulfill numerous responsibilities such as the orientation and motiva tion of staff, the promotion of professional growth, the design and provision of in -service training, evaluation of staff performance, problem-solving with supervisees, and improving educational outcomes for students (Hunley et al., 2000; NASP, 2004). Most studies investigating supervision in school ps ychology have examined supervision as a unitary construct (e.g., Chafoulea s et al., 2002; Knoff, 1986; Ross & Goh, 1993; Williams, Williams, & Ryer, 1990; Zins e t al., 1989). However, an important distinction should be made between clinical and adm inistrative supervision. Administrative supervision focuses on the monitorin g and improvement of job duties, personnel issues, logistics of service delivery, an d consumer satisfaction (as opposed to the improvement and expansion of professional skill s and competencies) (NASP, 2004). The NASP (2004) acknowledged that administrative su pervision can be provided by individuals trained and credentialed in school admi nistration and not necessarily school psychology. Clinical, or professional, supervision focuses on supporting practices that are consistent with professional standards, promoting C PD, and developing evaluation systems that are consistent with professional stand ards (NASP, 2004). The NASP (2004) recommended that clinical/professional supervision be provided only by a credentialed

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51 school psychologist or someone holding an equivalen t title (e.g., school psychology specialist, school psychology service provider). Th e NASP stated that supervision should include both professional/clinical and administrati ve supervision. Also, NASP recommended that supervisors themselves engage in C PD to maintain their supervisory skills as well as to be evaluated on their supervis ion methods and skills. It is essential that all practicing school psych ologists have access to quality supervision because they can benefit from the proce ss regardless of level of experience (NASP, 2004). Supervisory techniques may include di dactic readings, modeling, roleplaying, direct observation, reviewing audiotapes a nd reports as well as alternative supervisory techniques such as peer mentoring, peer coaching, peer supervision, and video conferencing. In fact, group supervision (Bah r et al., 1996), and internet community support and networking (e.g., Global Scho ol Psychology Network) (Kruger, Shribert, Donovan, & Burgess, 1999; Macklem et al., 2001) have been cited as specific techniques that can be beneficial to the field of s chool psychology. Participants from several countries and over 30 states in the United States participate in the Global School Psychology Network (GSPN). The GSPN offers school p sychologists opportunities to engage in discussion groups, on-line study groups, live text-based chats and interviews, listservs, and community-wide discussion forums. T he GSPN provides school psychologists with professional support that is imp ortant considering factors such as professional isolation, insufficient or sporadic fe edback, and lack of supervision. Both NASP and APA delineated standards for the freq uency of supervision practices. The NASP (2000) stated that interns, fir st-year school psychologists, and others for whom supervision is necessary should receive at least two hours of supervision per

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52 week. Supervision and peer review should continue t o be available after the first year of professional practice to ensure continued professio nal development and provide support for challenging cases. The APA (1981) delineated mo re stringent criteria that require non-doctoral psychologists receive one hour of face -to-face supervision each week from a doctoral-level psychologist throughout one’s care er. However, in spite of the standards of these professional associations, research indica tes that many school psychologists in the United States (Chafouleas et al., 2002; Fischet ti & Crespi, 1999; Ross & Goh, 1993; Zins et al., 1989) and in other countries (Lam & Yu en, 2004) do not receive these recommended levels of supervision. Ross and Goh (1993) conducted a national survey to assess supervision practices for 331 NASP members. Results indicated that only 3 1.1% of respondents received supervision. Among those who received supervision, 69.1% reported receiving supervision on an “as needed” basis, 37.2% reported receiving four or more hours per month, and 34.3% reported receiving one hour or les s per month. Respondents receiving supervision rated feedback and evaluation as the mo st important aspects of supervision and endorsed supervision as an important CPD activi ty. Additionally, over half (58.8%) of participants reported that they would like to re ceive more supervision than was being provided. Participants reported engaging in supervi sion activities such as informal consultation (74.7%), reading books/articles (48%), and workshops/lectures (45.3%). Fischetti and Crespi (1999) examined responses from 323 NASP members to assess clinical supervision trends. Ninety-eight pe rcent of the sample was employed in a public school setting. For the purposes of their st udy, clinical supervision was defined as “direct, one-on-one efforts on the part of the supe rvisor to help improve professional

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53 skills of a school psychologist” (p. 279). Results indicated that 90% of the respondents were not receiving any clinical supervision; howeve r, 76% of participants perceived clinical supervision as helpful in increasing skill s associated with service delivery. Of those school psychologists who reported receiving c linical supervision, many reported receiving less supervision than they believed appro priate based on their years of experience. Additionally, about 80% of participants reported receiving less supervision than the levels recommended by NASP and APA. An exa mination of supervisor characteristics indicated that the majority of supe rvisors held the title of coordinator of psychological services (50%) followed by school/cli nical psychologist (23%). The majority (79%) of clinical supervisors held a docto ral-level degree, but only 53% held a degree in school psychology. Despite these data, 91 % of the participants believed that school psychologists should be supervised by those holding a school psychologist degree. Hunley et al. (2000) surveyed 107 NASP members who identified themselves as supervisors. Data indicated that 45% of the supervi sors held a doctoral-level degree, 17% held a specialist degree, and 39% held a masters de gree. Approximately 90% of the supervisors reported having little or no training i n school psychology supervision before becoming a supervisor, and of those supervisors, 83 % reported that they had received minimal additional training since becoming a superv isor. The majority (65%) of the supervisors indicated that they were responsible fo r between one to 30 personnel, 19% reported being responsible for 31 to 50 personnel, and 15% reported being responsible for 51 or more personnel. Results also revealed that th ese supervisors engaged in a variety of supervisory activities, such as program administrat ion (74%), personnel issues (63%), program development (58%), and individual supervisi on (46%). Finally, they expressed a

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54 need for CPD to help them become more knowledgeable of and competent in the use of supervision techniques and practices (e.g., listerv s, mentoring program). Chafouleas et al. (2002) conducted a national surve y of supervision and evaluation practices of 189 nationally certified sc hool psychologists. For the purposes of their study, supervision was defined as “the opport unity for direction and oversight of an individual’s professional development” (p. 321). Th e study found that participants’ satisfaction with the evaluation component of super vision was moderate, that evaluation was primarily conducted by an administrator unfamil iar with school psychology, and that evaluation was not viewed as an opportunity for CPD (but, rather, as a means to document work performance). Results indicated that 51% of the participants who had supervision available reported receiving it on an a s needed basis or receiving less than two hours per month. Approximately 10% of the parti cipants reported receiving 3 or more hours per month of supervision. Additionally, respondents indicated a preference for more contact with a supervisor as well as havin g a supervisor who was familiar with school psychology practice. Curtis et al. (2002) examined supervision received by school psychologists based on the 1999-2000 school year. Results indicated tha t 47.2% of school psychologists reported receiving no supervision. Of those school psychologists who received supervision, 21.9% were supervised by a professiona l who held a degree in school psychology, and 34.1% were supervised by a professi onal who held a doctoral degree. Of note, supervision was not differentiated between ad ministrative and clinical. Curtis et al. (2006) examined both clinical and administrative su pervision received based on the 2004-2005 school year. Results indicated that 48.7% of school psychologists reported

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55 receiving administrative supervision, and 12.1% rep orted receiving clinical supervision. Of the respondents who received administrative supe rvision, over half (65.6%) of their supervisors held a degree in administration followe d by 32.8% who held a degree in school psychology. Approximately 25% of the adminis trative supervisors held a doctoral degree, and 35% held a masters/specialist degree. O f the small percentage of school psychologists who received clinical supervision, 55 .2% of their supervisors held a degree in school psychology, and 62.2% held a doctoral deg ree. These results indicated that school psychologists continue to not receive the re commended levels of supervision. It is especially clear that school psychologists are lack ing clinical supervision on a national level. Overall, these studies reveal that many school psy chologists are not receiving the recommended levels of supervision delineated by APA and NASP, although the majority of respondents believed that supervision is an impo rtant professional practice. Also, data suggested that school psychologists are often not s upervised by those familiar with the field or who hold school psychology degrees. To dat e, no research was found that specifically examined the relationship between supe rvisors’ characteristics (e.g., supervisors’ degree area or degree level) in relati onship with CPD practices of school psychologists. Conclusion Few empirical studies have investigated CPD as it r elates to the field of school psychology. Limited evidence exists regarding the r elationship(s) between CPD activities and the demographic characteristics, professional p ractices, and employment conditions of school psychologists. Although few significant r elationships have been found among

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56 these variables, these studies have provided greate r insight regarding the CPD activities of school psychologists, their perceptions of CPD, and perceived relevance of CPD. Limitations of these studies include the use of a l imited range of areas as a focus for CPD (i.e., assessment, consultation, direct service, pr ogram planning and evaluation, research, and supervision). Few studies examined other areas of focus for CPD, such as curriculum-based measurement, crisis intervention, and progress monitoring. The broader literature base suggests that school p sychologists consider CPD an important and essential professional practice that can enhance their skills and the effectiveness of service delivery. Furthermore, CPD is recognized through federal programs and funding, by professional accreditation bodies, professional associations, and in the school psychology literature as imperati ve in advancing the field and promoting positive student outcomes. However, few s chool psychologists report receiving authentic CPD opportunities, especially c linical supervision. Finally, the literature has documented several elements essentia l for effective CPD; however, few studies have specifically assessed the presence of these elements in school-based settings.

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57 Chapter Three Method Purpose of the Study This study examined the continuing professional dev elopment (CPD) subject areas among school psychologists who are employed f ull-time in school settings and the relationship of those areas with selected demograph ic characteristics, professional practices, and employment conditions using data fro m the National Association of School Psychologists (NASP) national database. The data th at were analyzed represented information provided by practicing school psycholog ists based on the 2004-2005 school year. Demographic variables that were examined incl uded gender, age, years of experience in school psychology, and highest degree earned. Professional practice variables that were examined included percentage of total work time in activities related to special education, number of psycho-educational evaluations completed relating to initial determination of special education eligibil ity, and number of special education reevaluations conducted during the school year. Emp loyment condition variables that were examined included school setting, ratio of ind ividual students to school psychologist, whether or not administrative and/or clinical supervision was received, clinical supervisor’s degree area (i.e., school psy chology or other) and degree level (i.e., non-doctoral or doctoral), and geographic region of the United States. Data relating to these variables were used to perform secondary anal yses of the existing national database. This chapter includes two sections: (a) d escription of the national database

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58 utilized for the present study; and (b) data analys is procedures that were used to answer each research question. Creation of the National Database The following section describes participants, ethni cal considerations, historical background, and procedures relating to the 2004-200 5 national database. Participants The national database represents survey response s from 1,748 Regular members of NASP. Regular NASP members are t hose individuals who are (a) currently working or credentialed as a school psych ologist; (b) trained as a school psychologist and working as a consultant or supervi sor of psychological services; or (c) primarily engaged in the training of school psychol ogists at a college or university (NASP, http://www.nasponline .org/membership/faq.ht ml#6). Respondents represented all 50 states, the District of Columbia, and Puerto Rico. Data were not solicited from student and affiliate members. Of the 1,748 respond ents, 80.44% were practicing school psychologists, 6.04% were university faculty, 5.29% were administrators, 0.63% were state department employees, and 7.60% were working in other settings (e.g., district testing coordinator, behavioral specialist, educati onal consultant, guidance counselor, private consultant, and school adjustment counselor ). Demographic characteristics of this sample were com pared to the 2005 NASP membership data. Chi-square goodness of fit tests i ndicated that the 2004-2005 national database respondents were comparable to the 2005 NA SP membership for gender (1, 1748) = .22436, p = .63574 but not for ethnicity (5, 1748) = 36.3449, p = <.0001 (effect size = .14) or highest degree earned (3, 1748) = 197.704, p = <.0001 (effect

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59 size= 2.9). On average, the 2004-2005 national database respond ents were statistically significantly younger than the 2005 NASP membership (xbar = 4.7, 95% CI = 4.92-5.21). A comparison of 2005 NASP membership and 2004-2005 NASP database respondents is displayed in Appendix A. Only the responses of school psychologists whose pr imary employment was reported to be full-time in a public, private, or f aith-based preschool, elementary school, middle/junior high school, and/or high school were included for the purpose of this study. Participants whose responses comprise the database included both males and females who represent varying demographic characteristics ( e.g., age, ethnicity, geographic region, years of experience), professional practice s (e.g., activities related to special education), and employment conditions (e.g., ratio of students to school psychologist, amount of supervision received). Ethical considerations. The study through which the national database was created was approved by the University of South Flo rida Institutional Review Board (IRB) for the protection of human participants in t he social and behavioral sciences. The IRB process ensures that research protects the righ ts and welfare of the participants (University of South Florida Institutional Review B oard, http://www.research.usf.edu/cs/irb.htm). The proced ures used in the national database data collection preserved the confidentiality and p rivacy of each participant. Historical background of the national database Graden and Curtis (1991) detailed the creation of the NASP national database The NASP leadership determined that empirical investigations were needed to system atically monitor the field of school psychology over time. Consequently, NASP adopted a policy to create a national

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60 database that reflected information pertaining to t he demographic characteristics, training background, credentialing, and professional practic es of school psychologists across the United States. Furthermore, the policy required tha t a national study be conducted by the Research Committee every five years to maintain the currency of the database. In accordance with the policy, a survey was to be used to collect data from the association’s membership. The first draft of a survey instrument was examined by NASP leadership, and received a full review and feedback, which was used to modify the instrument. A pilot study also was conducted with five practicing school psychologists to elicit feedback on the clarity, structure, and response op tions for each question as well as on the ease of completion of the survey and amount of time required for survey completion. Feedback was collected and revisions were made acco rdingly. Subsequently, the survey instrument received approval from both the NASP Del egate Assembly and Executive Board in the spring of 1990. The first study using the survey was based on the 1 989-90 school year (Graden & Curtis, 1991); the second study was based on the 19 94-95 school year (Curtis et al., 1999); and the third study was based on the 1999-20 00 school year (Curtis et al., 2002). The current database represented the fourth wave of data collection and was based on the 2004-2005 school year. The Research Committee considered it important that major changes not be made to the instrument to allow for consistent and repea ted measurement over time of specific variables related to school psychology (Curtis et a l., 1999) as well as for the examination of historical trends in the field (Curtis et al., 2 002). Consequently, the survey content has remained highly consistent over time. Specific to t he current database, minor changes

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61 were incorporated into the 2004-2005 survey. Among these changes were the additions of a question (i.e., Item 35) pertaining to continuing professional development as well as more detailed questions regarding supervision (i.e. Items 36 and 37). The purpose of the most recent survey (see Appendix B) was to gain information regarding the demographic characteristics, employme nt conditions, and professional practices of school psychologists during the 2004-2 005 school year. The survey consisted of 38 items. All respondents were asked to complet e items 1 through 18, which pertained to demographic variables. Items 19 through 38 incl uded questions regarding professional practices and employment conditions and were comple ted only by school psychologists whose primary employment was full-time in a public, private, or faith-based preschool, elementary school, middle/junior high school, and/o r high school. Procedure for creation of the database. A computerized random selection of potential participants was conducted by the NASP ce ntral office. The resulting electronic file was then used to generate duplicate sets of ma iling labels. The survey initially was mailed to 2,998 Regular NASP members, which represe nted a 20% random selection by state. Participation in the study was voluntary and no information reported on the survey could be used to identify participants. These step s were taken to ensure the privacy and confidentiality of the participants. Each particip ant was assigned a code number that was written on a postage-paid pre-addressed return enve lope. This code number was assigned (a) to ensure that those participants who returned surveys were not included in subsequent mailings; and (b) to provide a mechanism through which participants who completed and returned surveys could be randomly se lected to receive incentive rewards.

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62 Participants were asked to return the survey within three weeks of receipt. A cover letter (see Appendix C) from Dr. Michael Curt is, Principle Investigator on behalf of the NASP Research Committee, provided a rational e for the study and explained the procedures to be used and the confidential nature o f the survey information. Data collection was initiated in July of 2005 and contin ued through November of 2005. Data collection included three complete mailings and one postcard reminder mailing. Participants initially were informed that 10 person s who completed and returned the survey would be randomly selected to receive 50 “NA SP Bucks” that could be used for such purposes as the purchase of publications or pa yment toward conference and/or workshop registration. In the fourth and final mail ing, participants were informed that, in addition, five persons would be randomly selected t o receive a free year of membership in NASP. The first three mailings included the offe r of the 50 “NASP Bucks” due to a NASP Executive Council budgetary decision. Informal feedback received during the data collection phase indicated that the 50 “NASP Bucks” reward was not an effective incentive. Therefore, a decision was made to reinst ate the original free year of NASP membership as an incentive. Notification of both t he free NASP membership and the 50 “NASP Bucks” was included in the fourth mailing. Ho wever, all participants were eligible to receive both incentive rewards regardle ss of when they returned the survey. Returned surveys were immediately removed from the return envelope to preserve the anonymity of the respondent. The respondent’s n ame was crossed off the mailing list and the return envelope with the code number was pl aced in an alternate location for the sole purpose of awarding the incentives for partici pation. Response data from the returned surveys were entered into an Excel databas e. A data entry check was conducted

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63 for 10% (n= 175) randomly selected surveys. The err or rate was found to be 0.18% (i.e., 12 errors out of 6,650 entries). Survey data were i mported into SAS software, Version 9.1 (SAS Institute, 2002-2003) for data analysis. SAS is a statistical package and data management system that can be used to describe data and produce a variety of statistical analyses (Cody & Smith, 2006). Subsequently, data w ere winzorized using SAS software in order to eliminate error introduced by extreme response outliers (Yuen, 1974). Specifically, parameters for acceptable resp onses were identified by examining box plots, means, and standard deviations calculate d for each survey item. Minimum and maximum values were set for selected demographic ch aracteristics, professional practices, and employment condition variables (see Appendix D). The four mailings resulted in a total return of 1,7 48 usable surveys for a 59.3% response rate. Reschly and Wilson (1995) suggested that return rates of less than 50% may limit the ability to make valid conclusions abo ut the population of interest. However, because there is no empirical basis to this suggest ion, demographic characteristics of the sample in the database will be compared to the tota l NASP membership data to assess their degree of comparability. This procedure will be used to determine whether the sample used in the creation of the database demonst rates an acceptable comparison to the larger population of interest. Description of the Current Study This study examined the CPD subject areas endorsed by school psychologists employed full-time in school settings and the relat ionship of those areas with selected demographic characteristics, professional practices and employment conditions. Continuing professional development subject areas i ncluded: (a) standardized

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64 psychoeducational assessment; (b) academic screenin g/progress monitoring (e.g., curriculum-based assessment/measurement); (c) acade mic interventions; (d) behavioral assessment; (e) behavioral interventions; (f) socia l/emotional assessment; (g) social/emotional interventions; (h) consultation/pr oblem-solving; (i) response to intervention; and (j) crisis intervention. Responde nts were asked to select their top three subject areas of CPD during the 2004-2004 school ye ar. Data Analysis Each research question is stated below and the corr esponding survey items are identified in parentheses. Descriptive statistics w ere performed on all variables of interest. Data were subjected to the appropriate st atistical analyses for each research question as indicated below. Research Question 1: What is the distribution of continuing profession al development subject areas among school psychologist s who are employed full-time in school settings? (Survey Item 35) Frequency counts and percentages were calculated fo r each CPD subject area identified in survey Item 35. Percentages were conv erted to proportions, and 95% confidence intervals were calculated for each CPD s ubject area. Phi correlation coefficients were calculated to determine the relat ionship between each CPD subject area, using an alpha significance level of .005 (i.e., .0 5/11 continuing professional development subject areas). An 11 x 11 correlation matrix was used to display the results of the correlational analyses.

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65 Research Question 2 : What is the direction and strength of the relati onship between selected demographic characteristics of sch ool psychologists and each continuing professional development subject area? a.) gender (Survey Items 1 and 35) b.) age (Survey Items 2 and 35) c.) years of experience in school psychology (Surv ey Items 6 and 35) d.) highest degree earned (i.e., Masters, Masters p lus 30 semester hours/Educational Specialist, or Doctorate) (Survey Items 11 and 35) e.) Nationally Certified School Psychologist creden tial held (NCSP) (i.e., yes or no) (Survey Items 13 and 35) Various types of correlational analyses were calc ulated based on variable type. Phi correlation coefficients were calculated to det ermine relationship between gender and each CPD subject area and between NCSP held and eac h CPD subject area. A point biserial correlation coefficient was calculated for the variables of age and years of experience in school psychology. A rank biserial co rrelation coefficient was calculated for the variable of highest degree earned. Addition al correlations were calculated between each demographic characteristic variable to determi ne whether multicollinearity was present among the independent variables. All correl ations were conducted using an alpha significance level of .005. A logistic regression was performed in order to det ermine which demographic characteristic variables were most predictive of pa rticipation in each CPD subject area. Data were entered into a logistic regression model to examine the unique contribution of gender, age, years of experience in school psycholo gy, highest degree earned, and NCSP

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66 held with each subject area of CPD while holding al l other variables constant. The outcome variable, participation in a specified subj ect area of continuing professional development, was coded as 1=Yes and 0=No. Predictor variables were coded: gender was coded as 1=male and 0=female, with males as the ref erent; highest degree earned was dummy coded for Educational Specialist or equivalen t degree (1=Yes, 0=No) and Doctorate (1=Yes, 0=No), with Masters serving as th e referent; and NCSP was coded as 1=Yes and 0=No, with holding NCSP as the referent. Tests of significance included the likelihood ratio test, Hosmer and Lemeshow’s chi-square goodness of fit test, and Wald test. The likelihood ratio test and Hosmer and Lemeshow goodness of fit test examined the overall model fit. The Wald test indicated the significance of individual logistic regression coefficients for each independent variable. Analyses were conducted at the alpha .005 significance level. Odds ratios and 95% confidence intervals for the odds ratios were c alculated and reported. Measures of strength of association included an examination of odds ratios and the Pseudo-R-Squared statistic, which is an approximation to the Ordinar y Least Squares R-squared used in multiple regression analysis. Regression diagnostic s also were run for each logistic regression model in order to detect outliers and in fluential data points, or those cases which are poorly fitted by the model. Specifically, the Pearson and deviance residual (i.e., distance), hat matrix diagonal (i.e., leverage), df beta, and Cook’s D (i.e., influence) statistics were examined. Research Question 3: What is the direction and strength of the relatio nship between selected professional practices of school p sychologists and each continuing professional development subject area?

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67 a.) percentage of total work time in activities rel ated to special education (Survey Items 33 and 35) b.) number of psychoeducational evaluations complet ed relating to initial determination of special education eligibility (Sur vey Items 26 and 35) c.) number of special education reevaluations compl eted (Survey Items 27 and 35) Point biserial correlations were calculated to dete rmine the relationship between each professional practice variable and each CPD su bject area. Additional correlations were calculated between each professional practice variable to determine whether multicollinearity was present among the independent variables. All correlations were conducted using an alpha significance level of .005 A logistic regression was performed in order to det ermine which professional practice variables were most predictive of particip ation in CPD subject areas. Data were entered into a logistic regression model to examine the unique contribution of the percentage of total work time in activities related to special education, number of psychoeducational evaluations completed relating to initi al determination of special education eligibility, and number of special education reeval uations completed with each CPD subject area while holding all other variables cons tant. The outcome variable, participation in a specified subject area of contin uing professional development, was coded as 1 = Yes and 0 = No. Tests of significance included the likelihood ratio test, Hosmer and Lemeshow’s chi-square goodness of fit test, and Wald test. The likelihood ratio test and Hosmer and Lemeshow goodness of fit test examined the overall model fit. The Wald test indicated the significance of individual logistic regression coefficients for each independent

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68 variable. Analyses were conducted at the alpha .005 significance level. Odds ratios and 95% confidence intervals for the odds ratios were c alculated and reported. Measures of strength of association included an examination of odds ratios and the Pseudo-R-Squared statistic, which is an approximation to the Ordinar y Least Squares R-squared used in multiple regression analysis. Regression diagnostic s also were run for each logistic regression model in order to detect outliers and in fluential data points, or those cases which are poorly fitted by the model. Specifically, the Pearson and deviance residual (i.e., distance), hat matrix diagonal (i.e., leverage), df beta, and Cook’s D (i.e., influence) statistics were examined. Research Question 4: What is the direction and strength of the relatio nship between selected employment conditions of school ps ychologists and each continuing professional development subject area? a.) school setting (i.e., urban, suburban, rural) ( Survey Items 19 and 35) b.) ratio of individual students to school psycholo gist (Survey Items 23 and 35) c.) administrative supervision received in practice (Survey Items 36 and 35) d.) clinical supervision received in practice (Surv ey Items 37 and 35) d.) clinical supervisor’s degree area (i.e., school psychology, psychology, or other) (Survey Items 37 and 35) e.) clinical supervisor’s degree level (i.e., non-d octoral or doctoral) (Survey Items 37 and 35) Various types of correlational analyses were conduc ted based on variable type. Phi correlation coefficients were calculated for th e variables of school setting, supervision received in practice, clinical supervis or’s degree area, and clinical

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69 supervisor’s degree level and each CPD subject area A point biserial correlation was calculated for the variable of ratio of individual students to school psychologist. Additional correlations were calculated between eac h employment condition variable to determine whether multicollinearity was present amo ng the independent variables. All correlations were conducted using an alpha signific ance level of .005. A logistic regression was performed in order to det ermine which employment condition variables were most predictive of partici pation in CPD subject areas. Data were entered into a logistic regression model to examine the unique contribution of school setting, ratio of individual students to school psy chologist, administrative supervision received in practice, clinical supervision received in practice, clinical supervisor’s degree area, and clinical supervisor’s degree level with e ach subject area of continuing professional development while holding all other va riables constant. The outcome variable, participation in a specified subject area of continuing professional development, was coded as 1 = Yes and 0 = No. Predictor variable s were coded: school setting was dummy coded for urban (1=Yes, 0=No) and rural (1=Ye s, 0=No), with suburban as the referent; administrative supervision received in pr actice was coded as 1=Yes and 0=No, with receiving supervision as the referent; clinica l supervision received in practice was coded as 1=Yes and 0=No, with receiving supervision as the referent; clinical supervisor’s degree area as 1=Yes and 0=No, with ho lding a particular degree as the referent; clinical supervisor’s degree area as 1=Ye s and 0=No, with holding a degree in a particular area as the referent. Tests of significance included the likelihood ratio test, Hosmer and Lemeshow’s chi-square goodness of fit test, and Wald test. The likelihood ratio test and Hosmer and

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70 Lemeshow goodness of fit test examined the overall model fit. The Wald test indicated the significance of individual logistic regression coefficients for each independent variable. Analyses were conducted at the alpha .005 significance level. Odds ratios and 95% confidence intervals for the odds ratios were c alculated and reported. Measures of strength of association included an examination of odds ratios and the Pseudo-R-Squared statistic, which is an approximation to the Ordinar y Least Squares R-squared used in multiple regression analysis. Regression diagnostic s also were run for each logistic regression model in order to detect outliers and in fluential data points, or those cases which are poorly fitted by the model. Specifically, the Pearson and deviance residual (i.e., distance), hat matrix diagonal (i.e., leverage), df beta, and Cook’s D (i.e., influence) statistics were examined. Research Question 5: What is the relationship between the distribution of selected continuing professional development subjec t areas and geographic region? (Survey Items 35 and 10) Chi-square tests of independence were run to determ ine the relationship between geographic region (i.e., Northeast, Mid-Atlantic, S outh Atlantic, East South Central, East North Central, West South Central, West North Centr al, Mountain, and Pacific), as delineated by the United States Census (Hosp & Resc hly, 2002), and each subject area of continuing professional development at the alpha si gnificance level of .005. An index of effect size for significant chi-square tests of ass ociation was calculated to assess the practical significance of the relationship(s).

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71 Chapter Four Results This purpose of this study was to examine the conti nuing professional development (CPD) subject areas endorsed by school psychologists who were employed full-time in school settings and the relationship o f those areas with selected demographic characteristics, professional practices, and employ ment conditions using data from the National Association of School Psychologists (NASP) national database. The data analyzed represented information provided by practi cing school psychologists based on the 2004-2005 school year. This chapter begins with a description of the sample used in this study. Next, the results of the analyses are p rovided for each research question. The data were analyzed using SAS Version 9.1, and an al pha significance level of .005 was set for all statistical analyses. Description of the Sample The national database represented survey responses from 1,748 Regular members of NASP. Respondents represented all 50 states, the District of Columbia, and Puerto Rico. Of the 1,748 respondents, 80.44% were practic ing school psychologists, 6.04% were university faculty, 5.29% were administrators, 0.63% were state department employees, and 7.60% were working in other settings The total practitioner sample size in the database included responses from 1,398 pract icing school psychologists whose primary employment was reported to be full-time in a public, private, or faith-based preschool, elementary school, middle/junior high sc hool, and/or high school during the

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72 2004-2005 school year. Of the 1,398 practitioners, 1,155 (approximately 83%) provided responses to Item 35, which assessed CPD subject ar eas. Therefore, 1,155 practitioner responses comprised the total sample size used for the current study. Non-responders to the CPD item included 243 participants, which repre sented approximately 17% of the practicing school psychologists. Non-responders wer e those participants who did not complete the second portion of the survey (Items 118 were located on the front side of the survey and were to be completed by all particip ants including school psychologists who were not practitioners, while Items 19-38 were located on the back side) or completed only the first few items on the back side Appropriate statistical analyses were run to determine if there was statistically signifi cant relationship between response type (i.e., responders and non-responders) and selected demographic variables. Data indicated that was no statistically significant relationships between response type and ethnicity (3, 1363) = 4.2587, p = .2349. No statistically significant differences were found between responders and non-responders for age t (1384) = 1. 48, p = .1400. Statistically significant relationships were found between response type and the following variables: a) gender (1, 1397) = 9.4736, p = .0021 (Cramer’s V = .08); (b) highest degree ear ned (2, 1395) = 24.5264, p = <.0001 (Cramer’s V = .13); and (c) years of expe rience in school psychology t (1392) = 2.04, p = .0411. Notably, the effect size for years of expe rience was small (Cohen’s d = .14) (Cohen, 1992). Demographic statistics for r esponders and non-responders are presented in Table 2.

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73 Table 2 Descriptive Statistics for Responders and Non-Respo nders ___________________________________________________ _____________________ Variable Responders Non-Responders Gender* Female 80.82% 19.18% Male 88.24% 11.76% Ethnicity African American 92.86% 7.1 4% Caucasian 82.46% 17.54% Hispanic 76.92% 23.08% Other 75.00% 25.00% Highest Degree Earned* Masters 83.53% 1 6.47% Specialist 86.69% 13.31% Doctorate 73.90% 26.10% Age 45.03 46.19 Years of Experience* 13.74 15.0 7 p > .05. Respondents were asked to indicate the top three CP D subject areas that they addressed during the 2004-2005 school year; however of the 1,155 respondents, approximately 3% endorsed more than three CPD areas and approximately 5% of the respondents endorsed less than three CPD areas. The se results are presented in Table 3. The responses of those 8% of respondents who indica ted more or less than three CPD subject areas were included inthe analyses.

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74 Table 3 Number of CPD Subject Areas Endorsed by Respondents ___________________________________________________ _____________________ # of Categories Endorsed Total # of Respondent s Approximate % of Respondents ___________________________________________________ _____________________ 0 12 1.039 1 21 1.818 2 28 2.424 3a 1057 91.515 4 23 1.991 5 6 0.519 6 6 0.51 9 7 0 0.00 0 8 1 0.08 7 9 0 0.000 10 0 0.000 11 1 0.087 aNumber of CPD areas respondents were asked to indic ate on survey. Demographic characteristics, professional practices and employment conditions of respondents. The following tables provide descriptive statistic s on demographic characteristic, professional practice, and employme nt condition variables pertinent to the study. Data on ethnicity is presented solely for de scriptive purposes as this is not a variable that was specifically examined in the curr ent study. Demographic characteristics of those respondents who answered Item 35 are prese nted in Tables 4 and 5. Notably, the majority of school psychologists are female and Cau casian.

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75 Table 4 Age and Years of Experience in School Psychology ___________________________________________________ _____________________ Variable N Mean SD Skew ness Kurtosis ___________________________________________________ _____________________ Age 1148 45.037 1 0.975 -0.171 -1.171 Exp Psy 1151 13.739 9.251 0.437 -1.0 04 Table 5 Gender, Ethnicity, and Highest Degree Earned, and N ational Certification in School Psychology (NCSP) Credential Held ___________________________________________________ _____________________ Variable N % ___________________________________________________ _____________________ Gender 1 155 Male 285 24.68 Female 870 75.32 Ethnicity 1124 Caucasian 1041 92.62 African American 26 2.31 Hispanic 30 2.67 American Indian/Alaska Native 9 .80 Asian American/Pacific Islander 11 .98 Other 7 .62 Highest Degree 1152 Masters 417 36.20 Specialist 482 41.84 Doctorate 253 21.96 NCSP 1154 Yes 552 47.83 No 602 52.17

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76 Professional practice descriptive statistics are pr esented in Table 6. Distributions found to be non-normal are indicated by an asterisk The most significant illustration of non-normality was found for the “Number of Psychoed ucational Evaluations Completed Relating to Initial Determination of Special Educat ion Eligibility” and “Number of Special Education Reevaluations Completed” variable s. Employment condition descriptive statistics are presented in Table 7. No n-normality was found for the “Ratio of Individual Students to School Psychologist” variabl e as indicated in Table 7. Table 8 provides descriptive information on school setting and supervision. Notably, very few school psychologists reported receiving clinical su pervision (12.29%) and almost onehalf (47.74%) reported receiving no supervision of any kind. Table 6 Percentage of Total Work Time in Activities Related to Special Education, Number of Psychoeducational Evaluations Completed Relating to Initial Determination of Special Education Eligibility, and Number of Special Educat ion Reevaluations Completed ___________________________________________________ _____________________ Variable N Mean SD Skew ness Kurtosis ___________________________________________________ _____________________ % of Total Work Time 1114 80.433 21.177 -1.568 2.214 Initial Evaluations 1140 34.729 29.259 1.878 5.877* Reevaluations 1144 3 4.247 26.009 1.515 3.732* Note. Asterisk indicates non-normality.

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77 Table 7 Ratio of Individual Students to School Psychologist ___________________________________________________ _____________________ Variable N Mean SD Ske wness Kurtosis ___________________________________________________ _____________________ Ratio 972 1482.950 1028.607 2.289 9.908* Note. Asterisk indicates non-normality.

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78 Table 8 School Setting, Supervision Received in Practice, C linical Supervisor’s Degree Area, and Clinical Supervisor’s Degree Level ___________________________________________________ _____________________ Variable N % ___________________________________________________ _____________________ School Settinga Urban 298 21.32 Suburban 536 38.34 Rural 293 20.96 Supervision Received Administrative (Total) 1150 Yes 563 48.96 No 587 51.04 Clinical (Total) 1147 Yes 141 12.29 No 1006 87.71 Both Admin & Clinical 98 8.48 Neither Admin nor Clinical 549 47.53 Clinical Supervisor’s Degree Areab School Psychology 77 54.61 Psychology 53 37.59 Other 19 13.48 Clinical Supervisor’s Degree Levelc Doctoral 88 62.41 Masters/Specialist 18 12.77 aSome respondents reported working in more than one type of setting. For the purposes of the present study, random assignment was used to as sign respondents to only one setting. bSome respondents reported their clinical supervisor held a degree in more than one area. Percentages were calculated based on total number o f participants who received clinical supervision. cSome respondents reported their clinical supervisor held both a doctoral and master/specialist degree. For the purposes of the p resent study, highest degree earned was used to perform the analyses. Percentages were calc ulated based on total number of participants who received clinical supervision.

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79 Research Questions Research Question 1 : What is the distribution of continuing professio nal development subject areas among school psychologist s who are employed full-time in school settings? (Survey Item 35) Both frequency counts and percentages for each cont inuing professional development subject area identified in survey Item 35 were calculated. Percentages were converted to proportions, and 95% confidence interv als were calculated for each CPD subject area. These calculations are presented in T able 9. The two most commonly reported CPD subject areas were behavioral interven tions and standardized psychoeducational assessment. The two least commonl y endorsed subject areas included other and crisis intervention. The CPD areas most c ommonly reported for the other category included assessment and intervention of au tism and other low incidence disabilities, legal issues/compliance (e.g., IDEIA, NCLB), and neuropsychological assessment and intervention.

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80 Table 9 Frequencies, Percentages, Proportions, and 95% Conf idence Intervals for Each CPD Subject Area ___________________________________________________ _____________________ N % Proportion 95% CI ___________________________________________________ _____________________ Behavioral Interv 544 47.10% 4710 .4422-.4998 Stan Psychoed Assess 462 40.00% .4000 .3717-.4283 Acad Interv 381 32.99% .3299 .3027-.3570 Consult/Prob-solving 364 31.52 % .3152 .2883-.3420 Social/Emot Interv 331 28.66% .2866 .2605-.3127 Response to Interv 304 26.32% .2632 .2378-.2886 Behavioral Assess 247 21.39% .2139 .1902-.2375 Acad Scr/Prog Mon 238 20.61% .2061 .1827-.2294 Social/Emot Assess 194 16.80% .1 680 .1464-.1896 Crisis Interv 18 7 16.19% .1619 .1406-.1832 Other 173 14.98% .14 98 .1292-.1704 ___________________________________________________ _____________________ Phi correlation coefficients were calculated to det ermine the relationship between each continuing professional development subject ar ea. An 11 x 11 correlation matrix is presented in Table 10 to display the results of the correlational analyses. Notable correlation coefficients included the negative rela tionships between standardized psychoeducational assessment and response to interv ention ( r = -.20), academic screening/progress monitoring and behavioral interv ention ( r = -.21), and academic screening/progress monitoring and social/emotional intervention ( r = -.20), and the positive relationship between academic screening/pr ogress monitoring and response to intervention ( r = .28).

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81 Table 10 Phi Correlation Coefficients among Dependent Variab les ___________________________________________________ ________________________________________ 1 2 3 4 5 6 7 8 9 10 11 1. Stan Psychoed Assess ---2. Acad Scr/Prog Mon -.13* ---3. Acad Interv -.12* .08 ---4. Behavioral Assess .10* -.18* -.12* ---5. Behavioral Interv -.19* -.21* .0 0 -.04 ---6. Social/Emot Assess .13* -.18* -.1 8* .13* -.19* ---7. Social/Emot Interv -.17* -.20* -.1 8* -.15* .06 -.01 ---8. Consult/Prob-solving -.15* -.07 -.08 -.12* -.09* -.08 -.08 ---9. Response to Interv -.20* .28* .01 .16* -.15* -.14* -.16* -.06 ---10.Crisis Interv -.10* -.11* -.18* -.02 -.02 -.05 .09* -.05 -.15* ---11.Other -.05 .09* -.19* -.11* -.09* -.08 -.04 -.10* -.11* -.05 ---____________________ p < .005.

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82 Research Question 2: What is the direction and strength of the relatio nship between selected demographic characteristics of sch ool psychologists and each continuing professional development subject area? a.) gender (Survey Items 1 and 35) b.) age (Survey Items 2 and 35) c.) years of experience in school psychology (Surv ey Items 6 and 35) d.) highest degree earned (i.e., Masters, Masters p lus 30 semester hours/Educational Specialist, or Doctorate) (Survey Items 11 and 35) e.) Nationally Certified School Psychologist creden tial held (i.e., yes or no) (Items 11 and 35) Correlation coefficients were calculated to determi ne the relationship between the following independent variables and each CPD subjec t area: (a) gender; (b) age; (c) years of experience in school psychology; (d) highe st degree earned; and (e) Nationally Certified School Psychologist credential held. The results of these analyses are reported in Table 11. A notable correlation coefficient incl uded the negative relationship between age and response to intervention ( r = -.14). Additional correlation coefficients were calculated between each professional practice characteristic variable and tolerance stat istics were run to assess for multicollinearity. Table 12 indicates a statistical ly significant positive relationship between age and years of experience in school psych ology ( r =.73). Tolerance values for age (.46) and years of experience in school psychol ogy (.44) also indicated that some multicollinearity was present among independent var iables. This finding is not surprising considering that age and total years of experience data parallel each other and

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83 Table 11 Correlation Coefficients among Dependent and Indepe ndent Variables ___________________________________________________ _____________________ Age Gender Exp P sy MA EDS PHD NCSP 1. Stan Psychoed Assess .04 .00 .0 0 -.03 .00 .02 -.04 2. Acad Scr/Prog Mon -.07 .01 -.06 .01 .02 -.04 -.03 3. Acad Interv -.05 -.04 .04 -.04 .12* -.10* .03 4. Behavioral Assess .06 -.01 .01 -.01 .00 .01 -.08 5. Behavioral Interv -.10* -.04 .08* -.02 .04 -.02 .01 6. Social/Emot Assess .06 .02 .06 -.02 -.02 .05 .01 7. Social/Emot Interv .01 .00 -.00 -.05 -.05 .11* .03 8. Consult/Prob-solving .07 .06 .10* .08* -.06 -.02 .06 9. Response to Interv -.14* -.05 .08** -.02 .04 -.01 .03 10.Crisis Interv -.01 .04 .00 .00 -.02 .03 .01 11.Other .09* .01 .08 .00 -.05 .07 -.02 p < .005. ** p = .005. Table 12 Correlation Coefficients among Independent Variable s ___________________________________________________ _____________________ 1 2 3 4 5 6 7 1. Age ---2. Gender .16* ---3. Exp Psy .73* .19* ---4. MA .08 .02 .11 ---5. EDS -.23* -.11* -.25* -.64* ---6. PHD .19* .12* .17* -.4 0* -.45* ---7. NCSP .12* -.03 .22* -.07 .05 .02 ---____________ p < .005. indicate that practitioners continue to mature in a ge and experience (Curtis et al., 2004). Therefore, the variable of age was removed from the analysis in order to gain a more accurate estimation of each independent variable’s unique contribution to the prediction equation. Multicollinearity was reassessed via exam ination of the tolerance statistic for

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84 each independent variable. An examination of tolera nce statistics indicated that each independent variable was found to be within accepta ble limits (Berry, 1993). To determine which demographic characteristic varia bles were most predictive of participation in each continuing development subjec t area, data were subjected to a logistic regression analysis. Data were entered int o a logistic regression model to examine the unique contribution of gender, years of experience in school psychology, highest degree earned (i.e., MA, EDS, and PHD), and NCSP credential held with each CPD subject area while holding all other variables constant. The outcome variable, participation in a specified subject area of contin uing professional development, was treated as a dichotomous variable (Yes=1 and No=0). Five explanatory variables were entered into each model: (a) gender; (b) years of experience in school psychology; (c) highest degree earned (i.e., MA, EDS, and PHD); and (d) NCSP certification held. CPD Subject Area: Psychoeducational Standardized A ssessment. A total of 1150 observations were included in the analysis, and 5 o bservations were excluded due to missing data. A total of 461 observations were incl uded in the “1” category (i.e., yes for participation in psychoeducational standardized ass essment CPD subject area), and 689 were included in the “0” category (i.e., no for par ticipation). Results of the logistic regression analysis are shown in Table 13. An exami nation of regression diagnostics indicated that there were no significant outliers o r influential data points. The likelihood ratio test revealed that the model w ith the four factors in the equation was not found to be significantly differen t from the constant-only model (5, N=1150) = 3.5432, p = .6169, which indicates that the set of predictors did not reliably distinguish between those school psychologists who engaged in standardized

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85 psychoeducational assessment CPD and those who did not. The Wald and score tests also confirm this finding. The Hosmer-Lemeshow goodnessof-fit test was not significant. Table 13 Logistic Regression Analysis: Standardized Psychoeducational Assessment ___________________________________________________ _____________________ Predictor B SEB Wald’s df p Odds 95% CI Ratio ___________________________________________________ _____________________ Constant -0.4055 0.1472 7.5874 1 0.0059 NA Gender -0.0414 0.1434 0 .0833 1 0.7729 0.959 0.724-1.271 Exp Psy 0.0021 0.0071 0.0905 1 0.7636 1.002 0.988-1.016 Degree EDS 0.0930 0.1409 0 .4357 1 0.5092 1.097 0.833-1.446 PHD 0.1781 0.1634 1.1876 1 0.2758 1.195 0.867-1.646 NCSP -0.1965 0.1250 2.4 721 1 0.1159 0.822 0.643-1.050 ___________________________________________________ _____________________ Test df p ___________________________________________________ _____________________ Overall model evaluation Likelihood ratio test 3.5432 5 0.6169 Score test 3.5400 5 0.6173 Wald test 3.5318 5 0.6186 Goodness of fit test Hosmer & Lemeshow 5.2747 8 0.7279 ___________________________________________________ _____________________ Note. Cox and Snell R = .0031. p < .005. CPD Subject Area: Academic Screening/Progress Moni toring. A total of 1150 observations were included in the analysis, and 5 o bservations were excluded due to missing data. A total of 235 observations were incl uded in the “1” category, and 915 were included in the “0” category. Results of the l ogistic regression analysis are shown in

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86 Table 14. An examination of regression diagnostics indicated that there were no significant outliers or influential data points. The likelihood ratio test revealed that the model with the four factors in the equation was not found to be significantly differen t from the constant-only model (5, N=1150) = 5.9611, p = .3106, which indicates that the set of predictors did not reliably distinguish between those school psychologists who engaged in academic screening/progress monitoring CPD and those who did not. The Wald and score tests also confirm this finding. The Hosmer-Lemeshow goodnessof-fit test was not significant.

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87 Table 14 Logistic Regression Analysis: Academic Screening/Progress Monitoring ___________________________________________________ _____________________ Predictor B SEB Wald’s df p Odds 95% CI Ratio ___________________________________________________ _____________________ Constant -1.1305 0.1757 41.3887 1 <.0001* NA Gender 0.1086 0.1735 0 .3916 1 0.5315 1.115 0.793-1.566 Exp Psy -0.0152 0.0087 3.0397 1 0.0812 0.985 0.968-1.002 Highest Degree EDS 0.0307 0.1684 0 .0333 1 0.8552 1.031 0.741-1.435 PHD -0.1833 0.2069 0.7852 1 0.3756 0.833 0.555-1.249 NCSP -0.0608 0.1519 0.1 602 1 0.6890 0.941 0.679-1.267 ___________________________________________________ _____________________ Test df p ___________________________________________________ _____________________ Overall model evaluation Likelihood ratio test 5.9611 5 0.3106 Score test 5.8558 5 0.3205 Wald test 5.8188 5 0.3243 Goodness of fit test Hosmer & Lemeshow 8.1564 8 0.4183 ___________________________________________________ _____________________ Note. Cox and Snell R = .0052. p < .005. CPD Subject Area: Academic Interventions. A total of 1150 observations were included in the analysis, and 5 observations were e xcluded due to missing data. A total of 381 observations were included in the “1” category, and 769 were included in the “0” category (i.e., no for participation). Results of t he logistic regression analysis are shown in Table 15. An examination of regression diagnosti cs indicated that there were no outliers or influential data points.

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88 The likelihood ratio test revealed that the model w ith the four factors in the equation was found to be significantly different fr om the constant-only model (5, N=1150) = 22.0196, p = .0005, which indicates that the set of predictors reliably distinguished between those school psychologists wh o engaged in academic interventions CPD and those who did not. The Wald and score tests also confirm this finding. The Hosmer-Lemeshow goodness-of-fit test was not signif icant. This strength of the prediction was .0190 according to Cox’s and Snell’s R. However, the Wald chi-square statistic indicated that there were no individual p redictors that were statistically significant (see Table 15). Therefore, the full mod el with the four factors was statistically significant, but no one predictor could be identifi ed as making a significant unique contribution to the model.

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89 Table 15 Logistic Regression Analysis: Academic Interventions ___________________________________________________ _____________________ Predictor B SEB Wald’s df p Odds 95% CI Ratio ___________________________________________________ _____________________ Constant -0.7779 0.1551 25.1496 1 <.0001* NA Gender -0.1220 0.1531 0 .6351 1 0.4255 0.885 0.656-1.195 Exp Psy -0.0022 0.0074 0.0875 1 0.7674 0.998 0.983-1.012 Highest Degree EDS 0.3565 0.1449 6.0527 1 0.0139 1.428 1.015-1.898 PHD -0.3610 0.1827 3.9033 1 0.0482 0.697 0.487-0.997 NCSP 0.1053 0.1309 0. 6475 1 0.4210 1.111 0.860-1.436 ___________________________________________________ _____________________ Test df p ___________________________________________________ _____________________ Overall model evaluation Likelihood ratio test 22.0196 5 0.0005* Score test 21.6608 5 0.0006 Wald test 21.3132 5 0.0007 Goodness of fit test Hosmer & Lemeshow 6.5934 8 0.5811 ___________________________________________________ _____________________ Note. Cox and Snell R = .0190. p < .005. CPD Subject Area: Behavioral Assessment. A total of 1150 observations were included in the analysis, and 5 observations were e xcluded due to missing data. A total of 247 observations were included in the “1” category, and 903 were included in the “0” category. Results of the logistic regression analys is are shown in Table 16. An examination of regression diagnostics indicated tha t there were no outliers or influential data points.

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90 The likelihood ratio test revealed that the model w ith the four factors in the equation was not found to be significantly differen t from the constant-only model (5, N=1150) = 10.1554, p = .0709, which indicates that the set of predictors did not reliably distinguish between those school psychologists who engaged in behavioral assessment CPD and those who did not. The Wald and score tests also confirm this finding. The Hosmer-Lemeshow goodness-of-fit test was not signif icant. Table 16 Logistic Regression Analysis: Behavioral Assessment ___________________________________________________ _____________________ Predictor B SEB Wald’s df p Odds 95% CI Ratio ___________________________________________________ _____________________ Constant -1.2473 0.1753 50.6191 1 <.0001* NA Gender -0.1460 0.1737 0 .7064 1 0.4006 0.864 0.615-1.215 Exp Psy 0.0107 0.0085 1.6091 1 0.2046 1.011 0.994-1.028 Highest Degree EDS 0.0684 0.1686 0.1644 1 0.6852 1.071 0.769-1.490 PHD 0.0830 0.1950 0.1813 1 0.6703 1.087 0.741-1.592 NCSP -0.4626 0.1515 9. 3276 1 0.0023 0.630 0.468-0.847 ___________________________________________________ _____________________ Test df p ___________________________________________________ _____________________ Overall model evaluation Likelihood ratio test 10.1554 5 0.0709 Score test 10.0709 5 0.0733 Wald test 9.9789 5 0.0758 Goodness of fit test Hosmer & Lemeshow 3.6635 8 0.8861 ___________________________________________________ _____________________ Note. Cox and Snell R = .0088. p < .005.

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91 CPD Subject Area: Behavioral Interventions. A total of 1147 observations were included in the analysis, and 8 observations were e xcluded due to missing data. A total of 541 observations were included in the “1” category, and 606 were included in the “0” category. Results of the logistic regression analys is are shown in Table 17. An examination of regression diagnostics indicated tha t there were no outliers or influential data points. The likelihood ratio test revealed that the model with the four factors in the equation was not found to be significantly differen t from the constant-only model (5, N=1150) = 9.9247, p = .0774, which indicates that the set of predictors did not reliably distinguish between those school psychologists who engaged in behavioral interventions CPD and those who did not. The Wald and score tests also confirm this finding. The Hosmer-Lemeshow goodness-of-fit test was not signif icant.

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92 Table 17 Logistic Regression Analysis: Behavioral Interventions ___________________________________________________ _____________________ Predictor B SEB Wald’s df p Odds 95% CI Ratio ___________________________________________________ _____________________ Constant 0.0578 0.1445 0.1599 1 0.6893 NA Gender -0.0837 0.1413 0 .3511 1 0.5535 0.920 0.697-1.213 Exp Psy -0.0176 0.0070 6.3819 1 0.0115 0.983 0.969-0.996 Highest Degree EDS 0.0904 0.1381 0 .4287 1 0.5126 1.095 0.835-1.435 PHD 0.0043 0.1617 0.0007 1 0.9787 1.004 0.731-1.379 NCSP 0.1039 0.1230 0. 7137 1 0.3982 1.110 0.872-1.412 ___________________________________________________ _____________________ Test df p ___________________________________________________ _____________________ Overall model evaluation Likelihood ratio test 9.9247 5 0.0774 Score test 9.8779 5 0.078 8 Wald test 9.9075 5 0.080 9 Goodness of fit test Hosmer & Lemeshow 9.3278 8 0.3154 ___________________________________________________ _____________________ Note. Cox and Snell R = .0086. p < .005. CPD Subject Area: Social/Emotional Assessment. A total of 1150 observations were included in the analysis, and 5 observations w ere excluded due to missing data. A total of 194 observations were included in the “1” category, and 956 were included in the “0” category. Results of the logistic regression an alysis are shown in Table 18. An examination of regression diagnostics indicated tha t there were no outliers or influential data points.

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93 The likelihood ratio test revealed that the model w ith the four factors in the equation was not found to be significantly differen t from the constant-only model (5, N=1150) = 5.5706, p = .3503, which indicates that the set of predictors did not reliably distinguish between those school psychologists who engaged in social/emotional assessment CPD and those who did not. The Wald and score tests also confirm this finding. The Hosmer-Lemeshow goodness-of-fit test w as not significant. Table 18 Logistic Regression Analysis: Social/Emotional Assessment ___________________________________________________ _____________________ Predictor B SEB Wald’s df p Odds 95% CI Ratio ___________________________________________________ _____________________ Constant -1.8794 0.1984 89.7563 1 <.0001* NA Gender 0.0127 0.1850 0 .0047 1 0.9453 1.013 0.705-1.455 Exp Psy 0.0156 0.0091 2.9051 1 0.0883 1.016 0.998-1.034 Highest Degree EDS 0.0547 0.1881 0 .4287 1 0.7710 1.056 0.731-1.527 PHD 0.2634 0.2072 1.6160 1 0.2036 1.301 0.867-1.953 NCSP -0.0496 0.1638 0. 0919 1 0.7618 0.952 0.690-1.312 ___________________________________________________ _____________________ Test df p ___________________________________________________ _____________________ Overall model evaluation Likelihood ratio test 5.5706 5 0.3503 Score test 5.6850 5 0.338 1 Wald test 5.6486 5 0.341 9 Goodness of fit test Hosmer & Lemeshow 3.9261 8 0.8637 ___________________________________________________ _____________________ Note. Cox and Snell R = .0048. p < .005.

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94 CPD Subject Area: Social/Emotional Interventions. A total of 1150 observations were included in the analysis, and 5 o bservations were excluded due to missing data. A total of 329 observations were incl uded in the “1” category, and 821 were included in the “0” category. Results of the l ogistic regression analysis are shown in Table 19. An examination of regression diagnostics indicated that there were no outliers or influential data points. The likelihood ratio test revealed that the model w ith the four factors in the equation was not found to be significantly differen t from the constant-only model (5, N=1150) = 14.7602, p = .0114, which indicates that the set of predictors did not reliably distinguish between those school psychologists who engaged in social/emotional interventions CPD and those who did not. The Wald a nd score tests also confirm this finding. The Hosmer-Lemeshow goodness-of-fit test was not si gnificant.

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95 Table 19 Logistic Regression Analysis: Social/Emotional Interventions ___________________________________________________ _____________________ Predictor B SEB Wald’s df p Odds 95% CI Ratio ___________________________________________________ _____________________ Constant -1.0085 0.1618 38.8385 1 <.0001* NA Gender -0.0198 0.1560 0 .0161 1 0.8890 0.980 0.722-1.331 Exp Psy -0.0070 0.0077 0.8485 1 0.3570 0.993 0.978-1.008 Highest Degree EDS -0.0461 0.1565 0 .0869 1 0.7681 0.955 0.703-1.298 PHD 0.5418 0.1724 9.8775 1 0.0017 1.719 1.226-2.410 NCSP 0.1767 0.1359 1. 6889 1 0.1937 1.193 0.914-1.558 ___________________________________________________ _____________________ Test df p ___________________________________________________ _____________________ Overall model evaluation Likelihood ratio test 14.7602 5 0.0114 Score test 15.2216 5 0.0095 Wald test 15.0021 5 0.0104 Goodness of fit test Hosmer & Lemeshow 6.5870 8 0.5807 ___________________________________________________ _____________________ Note. Cox and Snell R = .0128. p < .005. CPD Subject Area: Consultation/Problem-Solving. A total of 1150 observations were included in the analysis, and 5 observations w ere excluded due to missing data. A total of 363 observations were included in the “1” category, and 787 were included in the “0” category. Results of the logistic regression an alysis are shown in Table 20. An examination of regression diagnostics indicated tha t there were no outliers or influential data points.

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96 The likelihood ratio test revealed that the model w ith the four factors in the equation was found to be significantly different fr om the constant-only model (5, N=1150) = 21.6815, p = .0006, which indicates that the set of predictors reliably distinguished between those school psychologists wh o engaged in consultation/problemsolving CPD and those who did not. The Wald and sco re tests also confirm this finding. The Hosmer-Lemeshow goodness-of-fit test was not si gnificant. This strength of the prediction was .02 according to Cox’s and Snell’s R. However, the Wald chi-square statistic indicated that there were no individual p redictors that were statistically significant (see Table 20). Therefore, the full mod el with the four factors was statistically significant, but no one predictor could be identifi ed as making a significant unique contribution to the model.

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97 Table 20 Logistic Regression Analysis: Consultation/Problem-Solving ___________________________________________________ _____________________ Predictor B SEB Wald’s df p Odds 95% CI Ratio ___________________________________________________ _____________________ Constant -0.9640 0.1556 38.3621 1 <.0001* NA Gender 0.2266 0.1488 2 .3187 1 0.1278 1.254 0.937-1.679 Exp Psy 0.0175 0.0074 5.6178 1 0.0178 1.018 1.003-1.032 Highest Degree EDS -0.3299 0.1484 4 .7354 1 0.0295 0.724 0.541-0.968 PHD -0.3755 0.1734 4.6922 1 0.0303 0.687 0.489-0.965 NCSP 0.2000 0.1328 2. 2687 1 0.1320 1.221 0.942-1.584 ___________________________________________________ _____________________ Test df p ___________________________________________________ _____________________ Overall model evaluation Likelihood ratio test 21.6815 5 0.0006* Score test 21.8380 5 0.0006 Wald test 21.4510 5 0.0007 Goodness of fit test Hosmer & Lemeshow 5.5012 8 0.7029 ___________________________________________________ _____________________ Note. Cox and Snell R = .0187. p < .005. CPD Subject Area: Response to Intervention. A total of 1150 observations were included in the analysis, and 5 observations were e xcluded due to missing data. A total of 302 observations were included in the “1” category, and 848 were included in the “0” category. Results of the logistic regression analys is are shown in Table 21. An examination of regression diagnostics indicated tha t there were no outliers or influential data points.

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98 The likelihood ratio test revealed that the model w ith the four factors in the equation was not found to be significantly differen t from the constant-only model (5, N=1150) = 12.8994, p = .0243, which indicates that the set of predictors did not reliably distinguish between those school psychologists who engaged in response to intervention CPD and those who did not. The Wald and score tests also confirm this finding. The Hosmer-Lemeshow goodness-of-fit test was not signif icant. Table 21 Logistic Regression Analysis: Response to Intervention ___________________________________________________ _____________________ Predictor B SEB Wald’s df p Odds 95% CI Ratio ___________________________________________________ _____________________ Constant -0.8346 0.1636 26.0287 1 <.0001* NA Gender -0.2005 0.1658 1 .4616 1 0.2267 0.818 0.591-1.133 Exp Psy -0.0222 0.0081 7.6067 1 0.0058 0.978 0.963-0.994 Highest Degree EDS 0.0644 0.1569 0 .1686 1 0.6813 1.067 0.784-1.450 PHD 0.0810 0.1860 0.1898 1 0.6631 1.084 0.753-1.561 NCSP 0.2043 0.1394 2. 1493 1 0.1426 1.227 0.933-1.612 ___________________________________________________ _____________________ Test df p ___________________________________________________ _____________________ Overall model evaluation Likelihood ratio test 12.8994 5 0.0243 Score test 12.6499 5 0.0269 Wald test 12.5022 5 0.0285 Goodness of fit test Hosmer & Lemeshow 4.3020 8 0.8289 ___________________________________________________ _____________________ Note. Cox and Snell R = .0112. p < .005.

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99 CPD Subject Area: Crisis Intervention. A total of 1150 observations were included in the analysis, and 5 observations were e xcluded due to missing data. A total of 186 observations were included in the “1” category, and 964 were included in the “0” category. Results of the logistic regression analys is are shown in Table 22. An examination of regression diagnostics indicated tha t there were no outliers or influential data points. The likelihood ratio test revealed that the model w ith the four factors in the equation was not found to be significantly differen t from the constant-only model (5, N=1150) = 3.3060, p = .6529, which indicates that the set of predictors did not reliably distinguish between those school psychologists who engaged in crisis intervention CPD and those who did not. The Wald and score tests als o confirm this finding. The HosmerLemeshow goodness-of-fit test was not significant.

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100 Table 22 Logistic Regression Analysis: Crisis Intervention ___________________________________________________ _____________________ Predictor B SEB Wald’s df p Odds 95% CI Ratio ___________________________________________________ _____________________ Constant -1.6862 0.1960 74.0109 1 <.0001* NA Gender 0.2639 0.1832 2 .0751 1 0.1497 1.302 0.909-1.864 Exp Psy -0.0049 0.0094 0.2713 1 0.6025 0.995 0.977-1.014 Highest Degree EDS -0.0703 0.1892 0 .1382 1 0.7101 0.932 0.643-1.351 PHD 0.1354 0.2121 0.4074 1 0.5233 1.145 0.756-1.735 NCSP 0.0739 0.1661 0. 1661 1 0.6565 1.077 0.778-1.491 ___________________________________________________ _____________________ Test df p ___________________________________________________ _____________________ Overall model evaluation Likelihood ratio test 3.3060 5 0.6529 Score test 3.3863 5 0.640 7 Wald test 3.3717 5 0.642 9 Goodness of fit test Hosmer & Lemeshow 5.2980 8 0.7253 ___________________________________________________ _____________________ Note. Cox and Snell R = .0029. p < .005. CPD Subject Area: Other. A total of 1155 observations were included in the analysis, and 5 observations were excluded due to m issing data. A total of 172 observations were included in the “1” category, and 978 were included in the “0” category. Results of the logistic regression analys is are shown in Table 23. An examination of regression diagnostics indicated tha t there were no outliers or influential data points.

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101 The likelihood ratio test revealed that the model w ith the four factors in the equation was not found to be significantly differen t from the constant-only model (5, N=1150) = 11.7408, p = .0385, which indicates that the set of predictors did not reliably distinguish between those school psychologists who engaged in other CPD and those who did not. The Wald and score tests also confirm this finding. The Hosmer-Lemeshow goodness-of-fit test was not significant. Table 23 Logistic Regression Analysis: Other ___________________________________________________ _____________________ Predictor B SEB Wald’s df p Odds 95% CI Ratio ___________________________________________________ _____________________ Constant -2.0261 0.2086 94.3395 1 <.0001* NA Gender -0.0931 0.1963 0 .2250 1 0.6352 0.911 0.620-1.339 Exp Psy 0.0235 0.0096 6.0247 1 0.0141 1.024 1.005-1.043 Highest Degree EDS -0.0332 0.2000 0 .0276 1 0.8680 0.967 0.654-1.432 PHD 0.3335 0.2129 2.4550 1 0.1171 1.396 0.920-2.119 NCSP -0.2055 0.1732 1. 4083 1 0.2353 0.814 0.580-1.143 ___________________________________________________ _____________________ Test df p ___________________________________________________ _____________________ Overall model evaluation Likelihood ratio test 11.7408 5 0.0385 Score test 11.9948 5 0.0349 Wald test 11.8175 5 0.0374 Goodness of fit test Hosmer & Lemeshow 2.3949 8 0.9665 ___________________________________________________ _____________________ Note. Cox and Snell R = .0102. p < .005.

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102 Research Question 3: What is the direction and strength of the relatio nship between selected professional practices of school p sychologists and each continuing professional development subject area? a.) percentage of total work time in activities rel ated to special education (Survey Items 33 and 35) b.) number of psychoeducational evaluations complet ed relating to initial determination of special education eligibility (Sur vey Items 26 and 35) c.) number of special education reevaluations comp leted (Survey Items 27 and 35) Correlation coefficients were calculated to determi ne the relationship between the following independent variables and each subject ar ea of continuing professional development: (a) total work time in activities rel ated to special education; (b) number of psychoeducational evaluations completed relating to initial determination of special education eligibility; and (c) number of special ed ucation reevaluations completed. The results of these analyses are reported in Table 24. Notable correlation coefficients included the positive relationship between standard ized psychoeducational assessment CPD and the percentage of total work time related t o special education ( r = .14) and initial evaluations ( r = .16) as well as the negative relationship between social/emotional interventions CPD and initial evaluations ( r = -.15).

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103 Table 24 Correlation Coefficients among Dependent and Indepe ndent Variables ___________________________________________________ _____________________ % of Total Initia l Eval Reevaluations Time 1. Stan Psychoed Assess .14* .16* .00 2. Acad Scr/Prog Mon -.01 .06 .01 3. Acad Intervent -.05 -. 01 .02 4. Behavioral Assess .08 .02 .00 5. Behavioral Interv .04 -.0 6 -.04 6. Social/Emot Assess .02 .08* .01 7. Social/Emot Interv -.05 -.15* -.08 8. Consult/Prob-solving -.11* -.04 -.02 9. Response to Interv -.11* .00 .04 10.Crisis Interv -.06 -.09* .01 11.Other .02 .03 .01 ______ p < .005. Additional correlation coefficients were calculated between each professional practice characteristic variable and tolerance stat istics were run to assess for multicollinearity. Table 25 indicates that no corre lations were of such significance to warrant removal from the analyses. An examination o f tolerance statistics indicated that each independent variable was found to be within ac ceptable limits (Berry, 1993). Table 25 Correlation Coefficients among Independent Variable s ___________________________________________________ _____________________ 1 2 3 1. % of Total Time --2. Initial Eval .16* --3. Reevaluations .22* .02 --__________________ p < .005.

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104 To determine which professional practice variables are most predictive of participation in each continuing development subjec t area, data were subjective to a logistic regression analysis. Data were entered int o a logistic regression model to examine the unique contribution of total work time in activities related to special education, number of psychoeducational evaluations completed relating to initial determination of special education eligibility, and number of special education reevaluations completed with each subject area of c ontinuing professional development while holding all other variables constant. The out come variable, participation in a specified subject area of continuing professional d evelopment, was treated as a dichotomous variable (Yes=1 and No=0). Five explana tory variables were entered into each model: (a) total work time in activities relat ed to special education; (b) number of psychoeducational evaluations completed relating to initial determination of special education eligibility; and (c) number of special ed ucation reevaluations completed. CPD Subject Area: Standardized Psychoeducational A ssessment. A total of 1101 observations were included in the analysis, and 54 observations were excluded due to missing data. A total of 444 observations were incl uded in the “1” category, and 657 were included in the “0” category. Results of the l ogistic regression analysis are shown in Table 26. An examination of regression diagnostics indicated that there were no outliers or influential data points. The likelihood ratio test revealed that the model w ith the three factors in the equation was found to be significantly different fr om the constant-only model (3, N=1101) = 45.3643, p < .0001, which indicates that the set of predictors reliably distinguished between those school psychologists wh o engaged in standardized

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105 psychoeducational assessment CPD and those who did not. The Wald and score tests also confirm this finding. The Hosmer-Lemeshow goodness-of-fit test was not si gnificant. This strength of the prediction was .04 according t o Cox’s and Snell’s R. The Wald chisquare statistic indicated that initial evaluations completed (1, N=1101) = 20.0379, p <.0001 and total percentage of time in activities r elated to special education (1, N=1101) = 16.1285, p < .0001 each made a statistically significant uniqu e contribution while holding all other variables constant (see Tab le 26). Those school psychologists who reported completing a greater number of initial eva luations were more likely to participate in standardized psychoeducational asses sment CPD as compared to those who reported completing a fewer number of initial evalu ations (OR= 1.010, 95% CI = 1.0061.014). Those school psychologists who reported spe nding a greater percentage of time in activities related to special education were more l ikely to participate in standardized psychoeducational assessment CPD as compared to tho se who reported spending a less percentage of time in activities related to special education (OR= 1.013, 95% CI= 1.0071.020). Figures 1 and 2 display a probability plot of the interaction between number of initial evaluations and total percentage of time in activities related to special education each with participation in standardized psychoeduca tional assessment CPD.

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106 Table 26 Logistic Regression Analysis: Standardized Psychoe ducational Assessment ___________________________________________________ _____________________ Predictor B SEB Wald’s df p Odds 95% CI Ratio ___________________________________________________ _____________________ Constant -1.7650 0.2776 40.4238 1 <.0001* NA Initial Eval 0.0099 0.0022 20.037 9 1 <.0001* 1.010 1.006-1.014 Reevaluations -0.0019 0.0025 0.5502 1 0.4582 0.998 0.993-1.003 % of Total Time 0.0134 0.0033 16.12 85 1 <.0001* 1.013 1.007-1.020 ___________________________________________________ _____________________ Test df p ___________________________________________________ _____________________ Overall model evaluation Likelihood ratio test 45.3643 3 <.0001* Score test 44.1388 3 <.0001* Wald test 41.1915 3 <.0001* Goodness of fit test Hosmer & Lemeshow 7.4694 8 0.4869 ___________________________________________________ _____________________ Note. Cox and Snell R = .0404. p < .005.

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107 Figure 1 Probability Plot: Initial*Standardized Psychoeduca tional Assessment CPD 0 0.1 0.2 0.3 0.4 0.5 0.6 111213141516171819110111112113114115116117118119120 1 Number of Initial Evaluations CompletedProbability of CPD Participation Figure 2 Probability Plot: % of Total Time *Standardized Ps ychoeducational Assessment CPD ___________________________________________________ ____________________ 0 0.1 0.2 0.3 0.4 0.5 110192837465564738291100 Total % Time Spent in Activities Related to Special EducationProbability of CPD Participation

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108 CPD Subject Area: Academic Screening/Progress Moni toring. A total of 1101 observations were included in the analysis, and 54 observations were excluded due to missing data. A total of 229 observations were incl uded in the “1” category, and 872 were included in the “0” category. Results of the l ogistic regression analysis are shown in Table 27. An examination of regression diagnostics indicated that there were no outliers or influential data points. The likelihood ratio test revealed that the model w ith the three factors in the equation was not found to be significantly differen t from the constant-only model (3, N=1101) = 4.3890, p = .2224, which indicates that the set of predictors did not reliably distinguish between those school psychologists who engaged in academic screening/progress monitoring CPD and those who did not. The Wald and score tests also confirm this finding. The Hosmer-Lemeshow goodnessof-fit test was not significant.

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109 Table 27 Logistic Regression Analysis: Academic Screening/P rogress Monitoring ___________________________________________________ _____________________ Predictor B SEB Wald’s df p Odds 95% CI Ratio ___________________________________________________ _____________________ Constant -1.3984 0.2952 22.4432 1 <.0001* NA Initial Eval 0.0050 0.0024 4.30 22 1 0.0381 1.005 1.000-1.010 Reevaluations 0.0015 0.0029 0.2733 1 0.6011 1.002 0.996-1.007 % of Total Time -0.0021 0.0036 0.33 89 1 0.5604 0.998 0.991-1.005 ___________________________________________________ _____________________ Test df p ___________________________________________________ _____________________ Overall model evaluation Likelihood ratio test 4.3890 3 0.2224 Score test 4.5782 3 0.205 4 Wald test 4.5301 3 0.209 6 Goodness of fit test Hosmer & Lemeshow 10.7229 8 0.2179 ___________________________________________________ _____________________ Note. Cox and Snell R = .0040; p < .005. CPD Subject Area: Academic Interventions. A total of 1101 observations were included in the analysis, and 54 observations were excluded due to missing data. A total of 366 observations were included in the “1” catego ry, and 735 were included in the “0” category. Results of the logistic regression analys is are shown in Table 28. An examination of regression diagnostics indicated tha t there were no outliers or influential data points. The likelihood ratio test revealed that the model w ith the three factors in the equation was not found to be significantly differen t from the constant-only model (3,

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110 N=1101) = 4.4281, p = .2188, which indicates that the set of predictors did not reliably distinguish between those school psychologists who engaged in academic interventions CPD and those who did not. The Wald and score tests also confirm this finding. The Hosmer-Lemeshow goodness-of-fit test was not signif icant. Table 28 Logistic Regression Analysis: Academic Interventio ns ___________________________________________________ _____________________ Predictor B SEB Wald’s df p Odds 95% CI Ratio ___________________________________________________ _____________________ Constant -0.3310 0.2500 1.7527 1 0.1855 NA Initial Eval -0.0002 0.0022 0.01 16 1 0.9144 1.000 0.995-1.004 Reevaluations 0.0032 0.0025 1.6082 1 0.2047 1.003 0.998-1.008 % of Total Time -0.0058 0.0031 3.55 17 1 0.0595 0.994 0.988-1.000 ___________________________________________________ _____________________ Test df p ___________________________________________________ _____________________ Overall model evaluation Likelihood ratio test 4.4281 3 0.2188 Score test 4.4795 3 0.214 1 Wald test 4.4515 3 0.216 7 Goodness of fit test Hosmer & Lemeshow 15.8838 8 0.0441 ___________________________________________________ _____________________ Note. Cox and Snell R = .0040. p < .005. CPD Subject Area: Behavioral Assessment. A total of 1101 observations were included in the analysis, and 54 observations were excluded due to missing data. A total of 234 observations were included in the “1” catego ry, and 867 were included in the “0” category. Results of the logistic regression analys is are shown in Table 29. An

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111 examination of regression diagnostics indicated tha t there were no outliers or influential data points. The likelihood ratio test revealed that the model w ith the three factors in the equation was not found to be significantly differen t from the constant-only model (3, N=1101) = 8.3570, p =. 0392, which indicates that the set of predictors did not reliably distinguish between those school psychologists who engaged in behavioral assessment CPD and those who did not. The Wald and score tests also confirm this finding. The Hosmer-Lemeshow goodness-of-fit test was not signif icant. Table 29 Logistic Regression Analysis: Behavioral Assessmen t ___________________________________________________ _____________________ Predictor B SEB Wald’s df p Odds 95% CI Ratio ___________________________________________________ _____________________ Constant -2.1536 0.3371 40.8109 1 <.0001* NA Initial Eval 0.0011 0.0025 0.19 80 1 0.6564 1.001 0.996-1.006 Reevaluations -0.0020 0.0030 0.4537 1 0.5006 0.998 0.992-1.004 % of Total Time 0.0107 0.0040 6.9 845 1 0.0082 1.011 1.003-1.019 ___________________________________________________ _____________________ Test df p ___________________________________________________ _____________________ Overall model evaluation Likelihood ratio test 8.3570 3 0.0392 Score test 7.8654 3 0.048 9 Wald test 7.7533 3 0.051 4 Goodness of fit test Hosmer & Lemeshow 4.4308 8 0.8163 ___________________________________________________ _____________________ Note. Cox and Snell R = .0076. p < .005.

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112 CPD Subject Area: Behavioral Interventions. A total of 1101 observations were included in the analysis, and 54 observations were excluded due to missing data. A total of 519 observations were included in the “1” catego ry, and 582 were included in the “0” category. Results of the logistic regression analys is are shown in Table 30. An examination of regression diagnostics indicated tha t there were no outliers or influential data points. The likelihood ratio test revealed that the model w ith the three factors in the equation was not found to be significantly differen t from the constant-only model (3, N=1101) = 8.5576, p = .0358, which indicates that the set of predictors did not reliably distinguish between those school psychologists who engaged in behavioral interventions CPD and those who did not. The Wald and score tests also confirm this finding. The Hosmer-Lemeshow goodness-of-fit test was not signif icant.

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113 Table 30 Logistic Regression Analysis: Behavioral Intervent ions ___________________________________________________ _____________________ Predictor B SEB Wald’s df p Odds 95% CI Ratio ___________________________________________________ _____________________ Constant -0.3079 0.2449 1.5805 1 0.2087 NA Initial Eval -0.0048 0.0021 4.930 9 1 0.0264 0.995 0.991-0.999 Reevaluations -0.0033 0.0024 1.8164 1 0.1777 0.997 0.992-1.001 % of Total Time 0.0058 0.0030 3.73 07 1 0.0534 1.006 1.000-1.012 ___________________________________________________ _____________________ Test df p ___________________________________________________ _____________________ Overall model evaluation Likelihood ratio test 8.5576 3 0.0358 Score test 8.4815 3 0.037 0 Wald test 8.3800 3 0.038 8 Goodness of fit test Hosmer & Lemeshow 9.2635 8 0.3206 ___________________________________________________ _____________________ Note. Cox and Snell R = .0077. p < .005. CPD Subject Area: Social/Emotional Assessment. A total of 1101 observations were included in the analysis, and 54 observations were excluded due to missing data. A total of 186 observations were included in the “1” category, and 915 were included in the “0” category. Results of the logistic regression an alysis are shown in Table 31. An examination of regression diagnostics indicated tha t there were no outliers or influential data points. The likelihood ratio test revealed that the model w ith the three factors in the equation was not found to be significantly differen t from the constant-only model (3,

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114 N=1101) = 6.7518, p = .0113, which indicates that the set of predictors did not reliably distinguish between those school psychologists who engaged in social/emotional assessment CPD and those who did not. The Wald and score tests also confirm this finding. The Hosmer-Lemeshow goodness-of-fit test w as not significant. Table 31 Logistic Regression Analysis: Social/Emotional Ass essment ___________________________________________________ _____________________ Predictor B SEB Wald’s df p Odds 95% CI Ratio ___________________________________________________ _____________________ Constant -1.9551 0.3348 34.1057 1 <.0001* NA Initial Eval 0.0064 0.0025 6.410 5 1 0.0113 1.006 1.001-1.011 Reevaluations 0.0001 0.0032 0.0008 1 0.9772 1.000 0.994-1.006 % of Total Time 0.0016 0.0041 0.14 33 1 0.7050 1.002 0.994-1.010 ___________________________________________________ _____________________ Test df p ___________________________________________________ _____________________ Overall model evaluation Likelihood ratio test 6.7518 3 0.0113 Score test 7.2558 3 0.977 2 Wald test 7.0979 3 0.705 0 Goodness of fit test Hosmer & Lemeshow 3.4323 8 0.9044 ___________________________________________________ _____________________ Note. Cox and Snell R = .0061. p < .005. CPD Subject Area: Social/Emotional Interventions. A total of 1101 observations were included in the analysis, and 54 observations were excluded due to missing data. A total of 316 observations were included in the “1” category, and 785 were included in the “0” category. Results of the logistic regression an alysis are shown in Table 32. An

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115 examination of regression diagnostics indicated tha t there were no outliers or influential data points. The likelihood ratio test revealed that the model w ith the four factors in the equation was found to be significantly different fr om the constant-only model (3, N=1101) = 32.5575, p < .0001, which indicates that the set of predictors reliably distinguished between those school psychologists wh o engaged in social/emotional interventions CPD and those who did not. The Wald a nd score tests also confirm this finding. The Hosmer-Lemeshow goodness-of-fit test was not si gnificant. This strength of the prediction was .03 according to Cox’s and Snell ’s R. The Wald chi-square statistics indicated that initial evaluations completed (1, N=1101) = 21.0972, p <.0001 made a statistically significant unique contribution while holding all other variables constant (see Table 32). Those school psychologists who reported completing fewer initial evaluations were more likely to participate in social/emotional interventions CPD as compared to those who reported completing a greater number of i nitial evaluations (OR= 0.987, 95% CI= 0.982-0.993). Figure 3 displays a probability p lot of the interaction between number of initial evaluations and participation in social/ emotional interventions CPD.

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116 Table 32 Logistic Regression Analysis: Social/Emotional Int erventions ___________________________________________________ _____________________ Predictor B SEB Wald’s df p Odds 95% CI Ratio ___________________________________________________ _____________________ Constant -0.2124 0.2636 0.6495 1 0.4203 NA Initial Eval -0.0130 0.0028 21.0972 1 <.0001* 0.987 0.982-0.993 Reevaluations -0.0067 0.0029 5.5674 1 0.0183 0.993 0.992-1.001 % of Total Time -0.0007 0.0032 0.049 5 1 0.8240 0.999 1.000-1.012 ___________________________________________________ _____________________ Test df p ___________________________________________________ _____________________ Overall model evaluation Likelihood ratio test 32.5575 3 <.0001* Score test 29.5461 3 <.0001 Wald test 28.5757 3 <.0001 Goodness of fit test Hosmer & Lemeshow 12.9478 8 0.1137 ___________________________________________________ _____________________ Note. Cox and Snell R = .0291. p < .005.

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117 Figure 3 Probability Plot: Initial*Social/Emotional Interve ntion CPD ___________________________________________________ _____________________ 0 0.1 0.2 0.3 0.4 0.5 111213141516171819110111112113114115116117118119120 1 Number of Initial Evaluations CompletedProbability of CPD Participation CPD Subject Area: Consultation/Problem-Solving. A total of 1101 observations were included in the analysis, and 54 observations were excluded due to missing data. A total of 346 observations were included in the “1” category, and 755 were included in the “0” category. Results of the logistic regression an alysis are shown in Table 33. An examination of regression diagnostics indicated tha t there were no outliers or influential data points. The likelihood ratio test revealed that the model w ith the four factors in the equation was found to be significantly different fr om the constant-only model (3, N=1101) = 12.8619, p = .0049, which indicates that the set of predictors reliably distinguished between those school psychologists wh o engaged in consultation/problemsolving CPD and those who did not. The Wald and sco re tests also confirm this finding. The Hosmer-Lemeshow goodness-of-fit test was not si gnificant. This strength of the

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118 prediction was .01 according to Cox’s and Snell’s R. The Wald chi-square statistics indicated that total percentage of time in activiti es related to special education (1, N=1101) = 8.8580, p = .0029 made a statistically significant unique con tribution while holding all other variables constant (see Table 33) Those school psychologists who reported a less total percentage of time in activit ies related to special education were more likely to participate in consultation/problemsolving CPD as compared to those who reported a greater total percentage of time (OR= 0 .991, 95% CI= 0.985-0.997). Figure 4 displays a probability plot of the interaction betw een total percentage of time in activities related to special education and participation in c onsultation/problem-solving CPD.

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119 Table 33 Logistic Regression Analysis: Consultation/Problem -Solving ___________________________________________________ _____________________ Predictor B SEB Wald’s df p Odds 95% CI Ratio ___________________________________________________ _____________________ Constant 0.0695 0.2497 0.0774 1 0.7808 NA Initial Eval -0.0032 0.0024 1.774 1 1 0.1829 0.997 0.992-1.001 Reevaluations -0.0003 0.0026 0.0112 1 0.9158 1.000 0.995-1.005 % of Total Time -0.0092 0.0031 8.858 0 1 0.0029* 0.991 0.985-0.997 ___________________________________________________ _____________________ Test df p ___________________________________________________ _____________________ Overall model evaluation Likelihood ratio test 12.8619 3 0.0049* Score test 13.1040 3 0.0044 Wald test 12.8532 3 0.0050 Goodness of fit test Hosmer & Lemeshow 6.5109 8 0.5902 ___________________________________________________ _____________________ Note. Cox and Snell R = .0116. p < .005.

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120 Figure 4 Probability Plot: % of Total Time*Consultation/Pro blem-Solving CPD ___________________________________________________ _______________ 0 0.1 0.2 0.3 0.4 0.5 0.6 110192837465564738291100 Total % of Time Spent in Activities Related to Spec ial EducationProbability of CPD Participation ______ CPD Subject Area: Response to Intervention. A total of 1101 observations were included in the analysis, and 54 observations were excluded due to missing data. A total of 292 observations were included in the “1” catego ry, and 809 were included in the “0” category. Results of the logistic regression analys is are shown in Table 34. An examination of regression diagnostics indicated tha t there were no outliers or influential data points. The likelihood ratio test revealed that the model w ith the four factors in the equation was found to be significantly different fr om the constant-only model (3, N=1101) = 16.4787, p = .0009, which indicates that the set of predictors reliably distinguished between those school psychologists wh o engaged in response to intervention CPD and those who did not. The Wald an d score tests also confirm this finding. The Hosmer-Lemeshow goodness-of-fit test w as not significant. This strength of the prediction was .01 according to Cox’s and Snell ’s R. The Wald chi-square statistics

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121 indicated that total percentage of time in activiti es related to special education (1, N=1101) = 14.4634, p = .0001 made a statistically significant unique con tribution while holding all other variables constant (see Table 34) Those school psychologists who reported a less total percentage of time in activit ies related to special education were more likely to participate in response to intervent ion CPD as compared to those who reported a greater total percentage of time (OR= 0. 988, 95% CI= 0.982-0.994). Figure 5 displays a probability plot of the interaction betw een total percentage of time in activities related to special education and participation in r esponse to intervention CPD. Table 34 Logistic Regression Analysis: Response to Interven tion ___________________________________________________ _____________________ Predictor B SEB Wald’s df p Odds 95% CI Ratio ___________________________________________________ _____________________ Constant -0.3301 0.2563 1.6590 1 0.1977 NA Initial Eval 0.0021 0.0024 0.793 6 1 0.3730 1.002 0.997-1.007 Reevaluations 0.0061 0.0026 5.4180 1 0.0199 1.006 1.001-1.011 % of Total Time -0.0123 0.0032 14.4634 1 0.0001* 0.988 0.982-0.994 ___________________________________________________ _____________________ Test df p ___________________________________________________ _____________________ Overall model evaluation Likelihood ratio test 16.4787 3 0.0009* Score test 16.9821 3 0.0007 Wald test 16.5681 3 0.0009 Goodness of fit test Hosmer & Lemeshow 6.0581 8 0.6407 ___________________________________________________ _____________________ Note. Cox and Snell R = .0149. p < .005.

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122 Figure 5 Probability Plot: % of Total Time*Response to Inte rvention CPD ___________________________________________________ __________________ 0 0.1 0.2 0.3 0.4 0.5 110192837465564738291100 Total % of Time in Activities Related to Special Ed ucationProbability of CPD Participation ______ CPD Subject Area: Crisis Intervention. A total of 1101 observations were included in the analysis, and 54 observations were excluded due to missing data. A total of 181 observations were included in the “1” catego ry, and 920 were included in the “0” category. Results of the logistic regression analys is are shown in Table 35. An examination of regression diagnostics indicated tha t there were no outliers or influential data points. The likelihood ratio test revealed that the model w ith the four factors in the equation was not found to be significantly differen t from the constant-only model (5, N=1101) = 12.5974, p = .0056, which indicates that the set of predictors did not reliably distinguish between those school psychologists who engaged in crisis intervention CPD and those who did not. The Wald and score tests als o confirm this finding. The HosmerLemeshow goodness-of-fit test was not significant.

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123 Table 35 Logistic Regression Analysis: Crisis Intervention ___________________________________________________ _____________________ Predictor B SEB Wald’s df p Odds 95% CI Ratio ___________________________________________________ _____________________ Constant -0.9099 0.3033 9.0023 1 0.0027* NA Initial Eval -0.0095 0.0034 7.828 7 1 0.0051 0.991 0.984-0.997 Reevaluations 0.0008 0.0032 0.0563 1 0.8124 1.001 0.994-1.007 % of Total Time -0.0055 0.0038 2.143 5 1 0.1432 0.994 0.987-1.002 ___________________________________________________ _____________________ Test df p ___________________________________________________ _____________________ Overall model evaluation Likelihood ratio test 12.5974 3 0.0056 Score test 11.5848 3 0.0089 Wald test 11.4329 3 0.0096 Goodness of fit test Hosmer & Lemeshow 11.7086 8 0.1647 ___________________________________________________ _____________________ Note. Cox and Snell R = .0114. p < .005. CPD Subject Area: Other. A total of 1101 observations were included in the analysis, and 54 observations were excluded due to missing data. A total of 165 observations were included in the “1” category, and 936 were included in the “0” category. Results of the logistic regression analys is are shown in Table 36. An examination of regression diagnostics indicated tha t there were no outliers or influential data points. The likelihood ratio test revealed that the model w ith the three factors in the equation was not found to be significantly differen t from the constant-only model (3,

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124 N=1101) = 1.4933, p = .6838, which indicates that the set of predictors did not reliably distinguish between those school psychologists who engaged in social/emotional assessment CPD and those who did not. The Wald and score tests also confirm this finding. The Hosmer-Lemeshow goodness-of-fit test w as not significant. Table 36 Logistic Regression Analysis: Other ___________________________________________________ _____________________ Predictor B SEB Wald’s df p Odds 95% CI Ratio ___________________________________________________ _____________________ Constant -1.9365 0.3498 30.6507 1 <.0001* NA Initial Eval 0.0020 0.0028 0.4 991 1 0.4799 1.002 0.997-1.007 Reevaluations -0.0027 0.0035 0.5942 1 0.4408 0.997 0.991-1.004 % of Total Time 0.0027 0.0043 0.40 81 1 0.5229 1.003 0.994-1.011 ___________________________________________________ _____________________ Test df p ___________________________________________________ _____________________ Overall model evaluation Likelihood ratio test 1.4933 3 0.6838 Score test 1.4966 3 0.68 31 Wald test 1.4940 3 0.68 36 Goodness of fit test Hosmer & Lemeshow 6.4533 8 0.5966 ___________________________________________________ _____________________ Note. Cox and Snell R = .0014. p < .005. Research Question 4: What is the direction and strength of the relatio nship between selected employment conditions of school ps ychologists and each continuing professional development subject area? a.) school setting (i.e., urban, suburban, rural) ( Survey Items 19 and 35)

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125 b.) ratio of individual students to school psycholo gist (Survey Items 23 and 35) c.) supervision received in practice (i .e., administrative only, clinical only, both administrative and clin ical, and no administrative or clinical supervision) (Survey Items 36, 37, and 35) d.) clinical supervisor’s degree area (i.e., school psychology, psychology, or other) (Survey Item 37 and 35) e.) clinical supervisor’s degree level (i.e., non-d octoral or doctoral) (Survey Item 37 and 35) Correlation coefficients were calculated to determi ne the relationship between the following independent variables and each subject ar ea of continuing professional development: (a) school setting; (b) ratio of indiv idual students to school psychologist; (c) supervision received in practice; (d) clinical supervisor’s degree area; (e) clinical supervisor’s degree level. The results of these ana lyses are reported in Table 37. Notable correlation coefficients included the negative rela tionship between social/emotional interventions CPD and ratio of individual students to school psychologist ( r = -.11). Additional correlation coefficients were calculated between each professional practice characteristic variable and tolerance stat istics were run to assess for multicollinearity. Table 38 indicates a statistical ly significant positive relationship between receiving clinical supervision and clinical supervisor degree in school psychology ( r =.72), receiving clinical supervision and clinical supervisor holding a Ph.D. degree, ( r =.77), and clinical supervisor holding a Ph.D. and clinical supervisor degree in psychology ( r =.64). The tolerance values for these four variable s were as follows: receiving clinical supervision (.15), clinical supe rvisor degree in school psychology (.42);

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126 clinical supervisor holding a Ph.D. (.29), and clin ical supervisor degree in psychology (.52). These data indicated that multicollinearity was present among independent variables. As a result, both the clinical superviso r’s degree area and clinical supervisor’s degree level variables were dropped from the analys is. This decision was made because one of the aims of the current study is to differen tiate between administrative and clinical supervision and how each uniquely related to CPD. T he alternative solution would have been to combined clinical supervision, clinical sup ervisor’s degree area, and clinical supervisor’s degree level into one composite variab le, which would not allow one to determine the unique contribution of clinical super vision to CPD. Therefore, the following analyses were conducted with only the fol lowing three independent variables: (a) school setting; (b) ratio of individual student s to school psychologist; and (c) supervision received in practice. Multicollinearity was reassessed via examination of the tolerance statistic. An examination of tolerance st atistics indicated that each independent variable was found to be within acceptable limits ( Berry, 1993).

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127 Table 37 Correlation Coefficients among Dependent and Indepe ndent Variables __________________________ Urban Suburb Rural Ratio Admin Clin SP Psy Oth MA/EDS PHD 1. Stan Psychoed Assess .05 .01 -.04 03 -.02 .01 -.01 -.02 -.04 .00 00 2. Acad Scr/Prog Mon -.09* .02 .06 .05 .04 -.06 -.05 -.01 -.05 -.01 -.04 3. Acad Interv -.00 -. 08 .10* .02 .00 -.04 -.02 -.06 -.02 .03 -.06 4. Behavioral Assess .06 -.04 .04 -.04 -.02 -.01 -.01 -.02 00 .02 -.04 5. Behavioral Interv .02 -.04 .03 -.09 .00 -.01 .00 .00 -.03 -.03 .01 6. Social/Emot Assess .04 .02 -.09* .06 -.02 .02 .01 .03 -.02 .00 .04 7. Social/Emot Interv -.02 .04 -.04 -.11* -.03 .05 .01 .05 .08 .01 .04 8. Consult/Prob-solving -.01 .03 -.03 -.02 .03 -.01 .01 -.05 02 .01 -.01 9. Response to Interv -.01 -.04 .06 .10* -.01 -.04 -.01 .02 -.03 -.04 -.02 10.Crisis Interv .00 .03 -.05 -.03 .03 .03 .01 .04 .02 -.02 .02 11.Other -.04 .06 -.02 .02 .00 .05 .0 4 .05 .02 .03 .07 ____________________ p < .005.

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128 Table 38 Correlation Coefficients among Independent Variable s ___________________________________________________ _____________________ 1 2 3 4 5 6 7 8 9 10 11 1. Urban ---2. Suburb -.41* ---3. Rural -.27* -.41* ---4. Ratio .05 -.06 .02 ---5. Admin -.02 .02 -.01 -.03 ---6. Clin .05 .01 -.07 -.06 .16* ---7. SP .06 -.03 -.04 -.04 .13* .72* ---8. Psy -.03 .03 .00 -.02 .06 .59* .26* ---9. Oth -.03 .06 -.03 -.04 .08 .35* .16* .00 ---10. MA/EDS .04 .00 -.04 .00 .09 .34* .25* .01 .31* ---11. PHD .01 .00 -.01 -.04 .10* .77* .54* .64* .07 -.04 ---* p < .005. To determine which employment condition variables w ere most predictive of participation in each continuing development subjec t area, data were subjective to a logistic regression analysis. Data were entered int o a logistic regression model to examine the unique contribution of setting, ratio o f individual students to school psychologist, and supervision received (i.e., admin istrative and clinical) with each CPD subject area while holding all other variables cons tant. The outcome variable, participation in a specified subject area of contin uing professional development, was treated as a dichotomous variable (Yes=1 and No=0). Four explanatory variables were entered into each model: (a) setting; (b) ratio of individual students to school psychologist; (c) administrative supervision receiv ed; and (d) clinical supervision received. Of note, all values for the ratio variabl e were converted to z-scores.

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129 CPD Subject Area: Standardized Psychoeducational A ssessment. A total of 962 observations were included in the analysis, and 193 observations were excluded due to missing data. A total of 384 observations were incl uded in the “1” category, and 578 were included in the “0” category. Results of the l ogistic regression analysis are shown in Table 39. An examination of regression diagnostics indicated that there were no outliers or influential data points. The likelihood ratio test revealed that the model w ith the four factors in the equation was not found to be significantly differen t from the constant-only model (5, N= 962) = 5.7353, p = .3328, which indicates that the set of predictors did not reliably distinguish between those school psychologists who engaged in standardized psychoeducational assessment CPD and those who did not. The Wald and score tests also confirm this finding. The Hosmer-Lemeshow goodnessof-fit test was not significant.

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130 Table 39 Logistic Regression Analysis: Standardized Psychoe ducational Assessment ___________________________________________________ _____________________ Predictor B SEB Wald’s df p Odds 95% CI Ratio ___________________________________________________ _____________________ Constant -0.4296 0.1150 13.9591 1 0.0002* NA Setting Urban 0.2801 0.1662 2.8412 1 0.0919 1.323 0.955-1.833 Rural -0.0180 0.1583 0.0130 1 0.9093 0.982 0.720-1.339 Ratio (z-score) 0.0647 0.0656 0 .9728 1 0.3240 1.067 0.938-1.213 Admin -0.1145 0.1341 0.7292 1 0.3932 0.892 0.686-1.1 60 Clin 0.1395 0.2060 0.4584 1 0.4984 1.150 0.7681.722 ___________________________________________________ _____________________ Test df p ___________________________________________________ _____________________ Overall model evaluation Likelihood ratio test 5.7353 5 0.3328 Score test 5.7696 5 0.32 93 Wald test 5.7311 5 0.33 33 Goodness of fit test Hosmer & Lemeshow 2.9869 8 0.9352 ___________________________________________________ _____________________ Note. Cox and Snell R = .0059. p < .005. CPD Subject Area: Academic Screening/Progress Moni toring. A total of 962 observations were included in the analysis, and 193 observations were excluded due to missing data. A total of 215 observations were incl uded in the “1” category, and 747 were included in the “0” category. Results of the l ogistic regression analysis are shown in Table 40. An examination of regression diagnostics indicated that there were no outliers or influential data points.

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131 The likelihood ratio test revealed that the model w ith the four factors in the equation was found to be significantly different fr om the constant-only model (5, N= 962) = 18.4145, p = .0025, which indicates that the set of predictors reliably distinguished between those school psychologists who engaged in a cademic screening/progress monitoring CPD and those who did not. The Wald and score tests also confirm this finding. The Hosmer-Lemeshow goodness-of-fit test was not si gnificant. This strength of the prediction was .02 according to Cox’s and Snell ’s R. However, the Wald chi-square statistic indicated that there were no individual p redictors that were statistically significant (see Table 40). Therefore, the full mod el with the four factors was statistically significant, but no one predictor could be identifi ed as making a significant unique contribution to the model.

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132 Table 40 Logistic Regression Analysis: Academic Screening/P rogress Monitoring ___________________________________________________ _____________________ Predictor B SEB Wald’s df p Odds 95% CI Ratio ___________________________________________________ _____________________ Constant -1.2696 0.1369 86.0442 1 <.0001* NA Setting Urban -0.5209 0.2196 5.6274 1 0.0177 0.594 0.386-0.913 Rural 0.1559 0.1774 0.7727 1 0.3794 1.169 0.826-1.655 Ratio (z-score) 0.1131 0.0745 2.302 2 1 0.1292 1.120 0.968-1.296 Admin 0.2645 0.1580 2.8 012 1 0.0942 1.303 0.956-1.776 Clin -0.5518 0.2801 3.8 821 1 0.0488 0.576 0.333-0.997 ___________________________________________________ _____________________ Test df p ___________________________________________________ _____________________ Overall model evaluation Likelihood ratio test 18.4145 5 0.0025* Score test 17.5553 5 0.003 6* Wald test 17.0920 5 0.004 3* Goodness of fit test Hosmer & Lemeshow 2.7577 8 0.9486 ___________________________________________________ _____________________ Note. Cox and Snell R = .0190. p < .005. CPD Subject Area: Academic Interventions. A total of 962 observations were included in the analysis, and 193 observations were excluded due to missing data. A total of 332 observations were included in the “1” catego ry, and 630 were included in the “0” category. Results of the logistic regression analys is are shown in Table 41. An examination of regression diagnostics indicated tha t there were no outliers or influential data points.

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133 The likelihood ratio test revealed that the model w ith the four factors in the equation was not found to be significantly differen t from the constant-only model (5, N=962) = 15.2306, p = .0094, which indicates that the set of predictors did not reliably distinguish between those school psychologists who engaged in academic interventions CPD and those who did not. The Wald and score tests also confirm this finding. The Hosmer-Lemeshow goodness-of-fit test was not signif icant. Table 41 Logistic Regression Analysis: Academic Interventio ns ___________________________________________________ _____________________ Predictor B SEB Wald’s df p Odds 95% CI Ratio ___________________________________________________ _____________________ Constant -0.8635 0.1219 50.1633 1 <.0001* NA Setting Urban 0.2556 0.1747 2.1404 1 0.1435 1.291 0.917-1.819 Rural 0.5692 0.1599 12.6686 1 0.0004 1.767 1.291-2.417 Ratio (z-score) 0.0264 0.0678 0.151 2 1 0.6974 1.027 0.899-1.173 Admin 0.0685 0.1386 0.2 439 1 0.6214 1.071 0.816-1.405 Clin -0.2907 0.2237 1.6 887 1 0.1938 0.748 0.482-1.159 ___________________________________________________ _____________________ Test df p ___________________________________________________ _____________________ Overall model evaluation Likelihood ratio test 15.2306 5 0.0094 Score test 15.2988 5 0.009 2 Wald test 15.1165 5 0.009 9 Goodness of fit test Hosmer & Lemeshow 9.6673 8 0.2892 ___________________________________________________ _____________________ Note. Cox and Snell R = .0157. p < .005.

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134 CPD Subject Area: Behavioral Assessment. A total of 962 observations were included in the analysis, and 193 observations were excluded due to missing data. A total of 203 observations were included in the “1” catego ry, and 759 were included in the “0” category. Results of the logistic regression analys is are shown in Table 42. An examination of regression diagnostics indicated tha t there were no outliers or influential data points. The likelihood ratio test revealed that the model w ith the four factors in the equation was not found to be significantly differen t from the constant-only model (5, N= 962) = 8.4149, p = .1348, which indicates that the set of predictors did not reliably distinguish between those school psychologists who engaged in behavioral assessment CPD and those who did not. The Wald and score tests also confirm this finding. The Hosmer-Lemeshow goodness-of-fit test was not signif icant.

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135 Table 42 Logistic Regression Analysis: Behavioral Assessmen t ___________________________________________________ _____________________ Predictor B SEB Wald’s df p Odds 95% CI Ratio ___________________________________________________ _____________________ Constant -1.3589 0.1390 95.5141 1 <.0001* NA Setting Urban 0.4472 0.1922 5.4161 1 0.0200 1.564 1.073-2. 279 Rural -0.0216 0.1953 0.0123 1 0.9118 0.979 0.667-1.435 Ratio (z-score) -0.1069 0.0846 1.5 962 1 0.2064 0.899 0.761-1.061 Admin -0.1422 0.1616 0 .7750 1 0.3787 0.867 0.632-1.19 1 Clin 0.0116 0.2480 0 .0022 1 0.9627 1.012 0.622-1.64 5 ___________________________________________________ _____________________ Test df p ___________________________________________________ _____________________ Overall model evaluation Likelihood ratio test 8.4149 5 0.1348 Score test 8.6242 5 0.12 50 Wald test 8.5209 5 0.12 98 Goodness of fit test Hosmer & Lemeshow 14.9964 8 0.0592 ___________________________________________________ _____________________ Note. Cox and Snell R = .0087. p < .005. CPD Subject Area: Behavioral Interventions. A total of 962 observations were included in the analysis, and 193 observations were excluded due to missing data. A total of 448 observations were included in the “1” catego ry, and 514 were included in the “0” category. Results of the logistic regression analys is are shown in Table 43. An examination of regression diagnostics indicated tha t there were no outliers or influential data points.

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136 The likelihood ratio test revealed that the model w ith the four factors in the equation was not found to be significantly differen t from the constant-only model (5, N= 962) = 11.1397, p = .0487, which indicates that the set of predictors did not reliably distinguish between those school psychologists who engaged in behavioral interventions CPD and those who did not. The Wald and score tests also confirm this finding. The Hosmer-Lemeshow goodness-of-fit test was not signif icant. Table 43 Logistic Regression Analysis: Behavioral Intervent ions ___________________________________________________ _____________________ Predictor B SEB Wald’s df p Odds 95% CI Ratio ___________________________________________________ _____________________ Constant -0.2086 0.1133 3.3298 1 0.0680 NA Setting Urban 0.2294 0.1655 1.9220 1 0.1656 1.258 0.909-1. 740 Rural 0.2371 0.1953 0.0123 1 0.9118 1.268 0.936-1.716 Ratio (z-score) -0.1913 0.0689 7.6 966 1 0.0055 0.826 0.722-0.945 Admin -0.0805 0.1320 0 .3718 1 0.5420 0.923 0.712-1.19 5 Clin -0.0784 0.2048 0 .1464 1 0.7020 0.925 0.619-1.38 1 ___________________________________________________ _____________________ Test df p ___________________________________________________ _____________________ Overall model evaluation Likelihood ratio test 11.1397 5 0.0487 Score test 10.9111 5 0.05 32 Wald test 10.6425 5 0.05 89 Goodness of fit test Hosmer & Lemeshow 11.4415 8 0.1779 ___________________________________________________ _____________________ Note. Cox and Snell R = .0115. p < .005.

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137 CPD Subject Area: Social/Emotional Assessment. A total of 962 observations were included in the analysis, and 193 observations were excluded due to missing data. A total of 166 observations were included in the “1” category, and 796 were included in the “0” category. Results of the logistic regression an alysis are shown in Table 44. An examination of regression diagnostics indicated tha t there were no outliers or influential data points. The likelihood ratio test revealed that the model w ith the four factors in the equation was not found to be significantly differen t from the constant-only model (5, N= 962) = 14.1429, p = .0147, which indicates that the set of predictors did not reliably distinguish between those school psychologists who engaged in social/emotional assessment CPD and those who did not. The Wald and score tests also confirm this finding. The Hosmer-Lemeshow goodness-of-fit test w as not significant.

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138 Table 44 Logistic Regression Analysis: Social/Emotional Ass essment ___________________________________________________ _____________________ Predictor B SEB Wald’s df p Odds 95% CI Ratio ___________________________________________________ _____________________ Constant -1.5044 0.1469 104.8651 1 <.0001* NA Setting Urban 0.2099 0.2031 1.0686 1 0.3013 1.234 0.829-1. 837 Rural -0.5633 0.2277 6.1227 1 0.0133 0.569 0.364-0.889 Ratio (z-score) 0.1466 0.0781 3.5 253 1 0.0604 1.158 0.994-1.349 Admin -0.0103 0.1750 0 .0035 1 0.9531 0.990 0.702-1.39 5 Clin 0.1100 0.2616 0.1768 1 0.6742 1.116 0.668 -1.864 ___________________________________________________ _____________________ Test df p ___________________________________________________ _____________________ Overall model evaluation Likelihood ratio test 14.1429 5 0.0147 Score test 13.9641 5 0.01 58 Wald test 13.5416 5 0.01 88 Goodness of fit test Hosmer & Lemeshow 12.5216 8 0.1294 ___________________________________________________ _____________________ Note. Cox and Snell R = .0146. p < .005. CPD Subject Area: Social/Emotional Interventions. A total of 962 observations were included in the analysis, and 193 observations were excluded due to missing data. A total of 263 observations were included in the “1” category, and 699 were included in the “0” category. Results of the logistic regression an alysis are shown in Table 45. An examination of regression diagnostics indicated tha t there were no outliers or influential data points.

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139 The likelihood ratio test revealed that the model w ith the four factors in the equation was found to be significantly different fr om the constant-only model (5, N=962) = 21.3591, p = .0007, which indicates that the set of predictors reliably distinguished between those school psychologists wh o engaged in social/emotional interventions CPD and those who did not. The Wald a nd score tests also confirm this finding. The Hosmer-Lemeshow goodness-of-fit test was not si gnificant. This strength of the prediction was .02 according to Cox’s and Snell ’s R. The Wald chi-square statistics indicated that ratio of individual students to scho ol psychologist (1, N=962) = 9.8658, p = 0.0017 made a statistically significant unique co ntribution while holding all other variables constant (see Table 45). Those school psy chologists who reported a lower ratio were likely to participate in social/emotional inte rventions CPD as compared to those who reported a higher ratio (OR= 0.762, 95% CI= 0.6 43-0.903). Figure 6 displays a probability plot of the interaction between individ ual student to school psychologist ratio and participation in social/emotional intervention CPD.

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140 Table 45 Logistic Regression Analysis: Social/Emotional Int erventions ___________________________________________________ _____________________ Predictor B SEB Wald’s df p Odds 95% CI Ratio ___________________________________________________ _____________________ Constant -0.7700 0.1234 38.9472 1 <.0001* NA Setting Urban -0.2891 0.1875 2.3758 1 0.1232 0.749 0.519-1. 082 Rural -0.3832 0.1784 4.6165 1 0.0317 0.682 0.481-0.967 Ratio (z-score) -0.2724 0.0867 9.8 658 1 0.0017* 0.762 0.643-0.903 Admin -0.2092 0.1489 1 .9736 1 0.1601 0.811 0.606-1.08 6 Clin 0.3158 0.2200 2 .0610 1 0.1511 1.371 0.891-2.11 1 ___________________________________________________ _____________________ Test df p ___________________________________________________ _____________________ Overall model evaluation Likelihood ratio test 21.3591 5 0.0007* Score test 20.0791 5 0.00 12* Wald test 19.6039 5 0.00 15* Goodness of fit test Hosmer & Lemeshow 3.0914 8 0.9285 ___________________________________________________ _____________________ Note. Cox and Snell R = .0220. p < .005.

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141 Figure 6 Probability Plot: Ratio*Social/Emotional Intervent ions CPD ___________________________________________________ ____________________ 0 0.1 0.2 0.3 0.4 0.5 Ratio (z-score) Probability of CPD Participation -1.4 -0.40.51.52.53.5 4.5 5.5 CPD Subject Area: Consultation/Problem-Solving. A total of 962 observations were included in the analysis, and 193 observations were excluded due to missing data. A total of 312 observations were included in the “1” category, and 650 were included in the “0” category. Results of the logistic regression an alysis are shown in Table 46. An examination of regression diagnostics indicated tha t there were no outliers or influential data points. The likelihood ratio test revealed that the model w ith the four factors in the equation was not found to be significantly differen t from the constant-only model (5, N= 962) = 2.2725, p = .8103, which indicates that the set of predictors did not reliably distinguish between those school psychologists who engaged in consultation/problemsolving CPD and those who did not. The Wald and sco re tests also confirm this finding. The Hosmer-Lemeshow goodness-of-fit test was not si gnificant.

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142 Table 46 Logistic Regression Analysis: Consultation/Problem -Solving ___________________________________________________ _____________________ Predictor B SEB Wald’s df p Odds 95% CI Ratio ___________________________________________________ _____________________ Constant -0.7257 0.1200 36.5849 1 <.0001* NA Setting Urban -0.1145 0.1759 0.4234 1 0.5153 0.892 0.632-1. 259 Rural -0.1608 0.1653 0.9465 1 0.3306 0.851 0.616-1.177 Ratio (z-score) -0.0378 0.0703 0.2 898 1 0.5903 0.963 0.839-1.105 Admin 0.1232 0.1399 0 .7752 1 0.3786 1.131 0.860-1.48 8 Clin -0.0105 0.2159 0 .0024 1 0.9611 0.990 0.648-1.51 1 ___________________________________________________ _____________________ Test df p ___________________________________________________ _____________________ Overall model evaluation Likelihood ratio test 2.2725 5 0.8103 Score test 2.2657 5 0.81 13 Wald test 2.2610 5 0.81 20 Goodness of fit test Hosmer & Lemeshow 7.2055 8 0.5146 ___________________________________________________ _____________________ Note. Cox and Snell R = .0024. p < .005. CPD Subject Area: Response to Intervention. A total of 962 observations were included in the analysis, and 193 observations were excluded due to missing data. A total of 267 observations were included in the “1” catego ry, and 695 were included in the “0” category. Results of the logistic regression analys is are shown in Table 47. An examination of regression diagnostics indicated tha t there were no outliers or influential data points.

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143 The likelihood ratio test revealed that the model w ith the four factors in the equation was not found to be significantly differen t from the constant-only model (5, N=962) = 15.0633, p = .0101, which indicates that the set of predictors did not reliably distinguish between those school psychologists who engaged in response to intervention CPD and those who did not. The Wald and score tests also confirm this finding. The Hosmer-Lemeshow goodness-of-fit test was not signif icant. Table 47 Logistic Regression Analysis: Response to Interven tion ___________________________________________________ _____________________ Predictor B SEB Wald’s df p Odds 95% CI Ratio ___________________________________________________ _____________________ Constant -1.0191 0.1277 63.6827 1 <.0001* NA Setting Urban -0.0262 0.1889 0.0193 1 0.8895 0.974 0.673-1. 411 Rural 0.2993 0.1686 3.1508 1 0.0759 1.349 0.969-1.877 Ratio (z-score) 0.1959 0.0692 8.0 184 1 0.0046 1.216 1.062-1.393 Admin 0.0267 0.1470 0 .0330 1 0.8559 1.027 0.770-1.37 0 Clin -0.3640 0.2468 2 .1750 1 0.1403 0.695 0.428-1.12 7 ___________________________________________________ _____________________ Test df p ___________________________________________________ _____________________ Overall model evaluation Likelihood ratio test 15.0633 5 0.0101 Score test 15.3220 5 0.00 91 Wald test 14.8358 5 0.01 11 Goodness of fit test Hosmer & Lemeshow 8.7644 8 0.3626 ___________________________________________________ _____________________ Note. Cox and Snell R = .0155. p < .005.

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144 CPD Subject Area: Crisis Intervention. A total of 962 observations were included in the analysis, and 193 observations were excluded due to missing data. A total of 143 observations were included in the “1” catego ry, and 819 were included in the “0” category. Results of the logistic regression analys is are shown in Table 48. An examination of regression diagnostics indicated tha t there were no outliers or influential data points. The likelihood ratio test revealed that the model w ith the four factors in the equation was not found to be significantly differen t from the constant-only model (5, N= 962) = 9.0407, p = .1075, which indicates that the set of predictors did not reliably distinguish between those school psychologists who engaged in crisis intervention CPD and those who did not. The Wald and score tests als o confirm this finding. The HosmerLemeshow goodness-of-fit test was not significant.

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145 Table 48 Logistic Regression Analysis: Crisis Intervention ___________________________________________________ _____________________ Predictor B SEB Wald’s df p Odds 95% CI Ratio ___________________________________________________ _____________________ Constant -1.7687 0.1593 123.3018 1 <.0001* NA Setting Urban -0.0748 0.2245 0.1111 1 0.7389 0.928 0.598-1. 441 Rural -0.5162 0.2348 4.8322 1 0.0279 0.597 0.377-0.946 Ratio (z-score) -0.0721 0.0963 0.5 602 1 0.4542 0.930 0.770-1.124 Admin 0.2890 0.1857 2 .4212 1 0.1197 1.335 0.928-1.92 1 Clin 0.0925 0.2714 0 .1161 1 0.7333 1.097 0.644-1.86 7 ___________________________________________________ _____________________ Test df p ___________________________________________________ _____________________ Overall model evaluation Likelihood ratio test 9.0407 5 0.1075 Score test 8.7205 5 0.1 207 Wald test 8.5896 5 0.1 266 Goodness of fit test Hosmer & Lemeshow 7.1885 8 0.5164 ___________________________________________________ _____________________ Note. Cox and Snell R = .0094. p < .005. CPD Subject Area: Other. A total of 962 observations were included in the analysis, and 193 observations were excluded due to missing data. A total of 140 observations were included in the “1” category, and 822 were included in the “0” category. Results of the logistic regression analys is are shown in Table 49. An examination of regression diagnostics indicated tha t there were no outliers or influential data points.

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146 The likelihood ratio test revealed that the model w ith the four factors in the equation was not found to be significantly differen t from the constant-only model (5, N= 962) = 9.9809, p = .0758, which indicates that the set of predictors did not reliably distinguish between those school psychologists who engaged in other CPD and those who did not. The Wald and score tests also confirm this finding. The Hosmer-Lemeshow goodness-of-fit test was not significant. Table 49 Logistic Regression Analysis: Other ___________________________________________________ _____________________ Predictor B SEB Wald’s df p Odds 95% CI Ratio ___________________________________________________ _____________________ Constant -1.5694 0.1519 106.6849 1 <.0001* NA Setting Urban -0.5311 0.2502 4.5074 1 0.0337 0.588 0.360-0. 960 Rural -0.2665 0.2197 1.4722 1 0.2250 0.766 0.498-1.178 Ratio (z-score) 0.0905 0.0873 1.0 740 1 0.3000 1.095 0.923-1.299 Admin -0.2062 0.1876 1 .2079 1 0.2717 0.814 0.563-1.17 5 Clin 0.5415 0.2612 4 .2971 1 0.0382 1.719 1.030-2.86 7 ___________________________________________________ _____________________ Test df p ___________________________________________________ _____________________ Overall model evaluation Likelihood ratio test 9.9809 5 0.0758 Score test 10.1498 5 0.07 11 Wald test 9.9721 5 0.0 760 Goodness of fit test Hosmer & Lemeshow 10.3411 8 0.2419 ___________________________________________________ _____________________ Note. Cox and Snell R = .0103. p < .005.

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147 Research Question 5: What is the relationship between the distribution of selected continuing professional development subjec t areas and geographic region? (Survey Items 35 and 10) Chi-square tests of independence were conducted to test the relationship between each geographic region (i.e., Northeast, Mid-Atlant ic, South Atlantic, East South Central, East North Central, West South Central, West North Central, Mountain, and Pacific) (see Appendix E), as delineated by the United States Cen sus (Hosp & Reschly, 2002), and each subject area of continuing professional develo pment at the alpha significance level of .005. Frequency counts and percentages for each region are displayed in Table 50. Table 50 Frequency Counts and Percentages of Practitioners f or Each Region __________________________________________________ _____________________ N % ___________________________________________________ ____________________ Mid-Atlantic 290 20.86% East North Central 255 18.35 % South Atlantic 245 17.63% Pacific 156 11.22% Northeast 131 9.42% Mountain 109 7.84% West North Central 98 7.05% West South Central 57 4.10% East South Central 49 3.53% ___________________________________________________ _____________________ A total of 1,151 responses were used in these anal yses, and 239 responses were excluded due to missing data. Results indicated tha t there was a significant relationship between selected CPD subject areas and region. A st atistically significant association was

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148 found between region and participation in the follo wing CPD subject areas: (a) academic screening/progress monitoring ( (8, 1151) = 89.9993, p <.0001); (b) behavioral assessment ( (8, 1151) = 44.0519, p <.0001); (c) social/emotional assessment ( (8, 1151) = 26.5853, p = .0008); (d) social/emotional intervention ( (8, 1151) = 22.1686, p = .0046); (e) response to intervention ( (8, 1151) = 35.6605, p <.0001); and (f) crisis intervention ( (8, 1151) = 35.5196, p <.0001). A statistically significant association was not fou nd between region and participation in the following CPD subject areas: ( a) standardized psychoeducational assessment ( (8, 1151) = 16.5412, p = .0353); (b) academic interventions ( (8, 1151) = 20.1062, p = .0099); (c) behavioral interventions ( (8, 1151) = 14.2430, p = .0756); (d) consultation/problem-solving ( (8, 1151) = 16.8059, p = .0322); and (e) other ( (8, 1151) = 17.6469, p = .0240). Details on those tests are presented belo w. Academic Screening/Progress Monitoring. Results indicated that there was a statistically significant relationship between acad emic screening/progress monitoring CPD and region ( (8, 1151) = 89.9993, p <.0001). The strength of association was small to medium (Cramer’s V= .28). Upon reviewing the per centage of school psychologists that reported participating in academic screening/p rogress monitoring CPD, it appears that the East North Central and West South Central regions were different from the others. The East North Central region (40.85) had t he highest percentage of school psychologists participating in academic screening/p rogress monitoring CPD. The West South Central region (4.17) had the lowest percenta ge of school psychologists participating in academic screening/progress monito ring CPD.

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149 Behavioral Assessment. Results indicated that there was a statistically si gnificant relationship between behavioral assessment CPD and region ( (8, 1151) = 44.0519, p <.0001). The strength of association was small to m edium (Cramer’s V= .20). Upon reviewing the percentage of school psychologists th at reported participating in behavioral assessment CPD, it appears that the West South Cent ral and East South Central regions were different from the others. The West South Cent ral region (50) had the highest percentage of school psychologists participating in behavioral assessment CPD. The East South Central region (12.2) had the lowest percenta ge of school psychologists participating in behavioral assessment CPD. Social/Emotional Assessment. Results indicated that there was a statistically significant relationship between social/emotional a ssessment CPD and region ( (8, 1151) = 26.5853, p = .0008). The strength of association was small (Cr amer’s V= .15). Upon reviewing the percentage of school psychologis ts that reported participating in social/emotional assessment CPD, it appears that th e Northeast and East North Central regions were different from the others. The Northea st region (29.41) had the highest percentage of school psychologists participating in social/emotional assessment CPD. The East North Central region (10.8) had the lowest percentage of school psychologists participating in social/emotional assessment CPD. Social/Emotional Interventions. Results indicated that there was a statistically significant relationship between social/emotional a ssessment CPD and region ( (8, 1151) = 22.1686, p = .0046). The strength of association was small (Cr amer’s V= .14). Upon reviewing the percentage of school psychologis ts that reported participating in social/emotional interventions CPD, it appears that the Northeast and East South Central

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150 regions were different from the others. The Northea st region (43.14) had the highest percentage of school psychologists participating in social/emotional interventions CPD. The East South Central region (19.51) had the lowes t percentage of school psychologists participating in social/emotional interventions CPD Response to Intervention. Results indicated that there was a statistically significant relationship between response to interv ention CPD and region ( (8, 1151) = 35.6605, p <.0001). The strength of association was small (Cra mer’s V= .18). Upon reviewing the percentage of school psychologists th at reported participating in response to intervention CPD, it appears that the Mountain a nd Northeast regions were different from the others. The Mountain region (36.84) had th e highest percentage of school psychologists participating in response to interven tion CPD. The Northeast region (8.82) had the lowest percentage of school psychologists p articipating in response to intervention CPD. Crisis Intervention. Results indicated that there was a statistically si gnificant relationship between crisis intervention CPD and re gion ( (8, 1151) = 35.5196, p <.0001). The strength of association was small (Cra mer’s V= .18). Upon reviewing the percentage of school psychologists that reported pa rticipating in crisis intervention CPD, it appears that the Mid-Atlantic region and West So uth Central regions were different from the others. The Mid-Atlantic region (23.77) ha d the highest percentage of school psychologists participating in crisis intervention CPD. The West South Central region (6.25) had the lowest percentage of school psycholo gists participating in crisis intervention CPD.

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151 Chapter Five Discussion School psychologists are faced with a variety of c ontextual factors that impact their professional role. Changes in student demogra phic characteristics and educational law and policy require school psychologists to expa nd their repertoire of skills in order to meet the needs of their clients. Some school psycho logists will be required to extend far beyond their educational training, while others may have to refine pre-existing skills. Despite training backgrounds, school psychologists are ethically responsible for providing appropriate and effective services to pro mote positive academic, behavioral, and social/emotional outcomes for all students. Continuing professional development (CPD) has been identified as a critical means for providing school psychologists with relev ant skills to meet a diverse range of student needs. The present study investigated the C PD subject areas endorsed by school psychologists who are employed full-time in school settings, and the relationship of those areas with selected demographic characteristics, pr ofessional practices, and employment conditions. Summary of the Findings This study was exploratory in nature due to the lim ited literature base relating to CPD activities of school psychologists. The study e xamined the CPD subject areas endorsed by practicing school psychologists and the relationship of those subject areas with demographic characteristics, professional prac tices, and employment conditions.

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152 Findings indicated that the most to least commonly identified CPD subject areas were: behavioral interventions (47.10%); standardized psy choeducational assessment (40%); academic interventions (32.99%); consultation/probl em-solving (31.52%); social/emotional intervention (28.66%); response to intervention (26.32%); behavioral assessment (21.39%); academic screening/progress mo nitoring (20.61%); social/emotional assessment (16.80%); crisis interv ention (16.19%); and other (14.98%). The CPD areas most commonly reported for the “other ” category included assessment and intervention with autism and other low incidenc e disabilities, legal issues/compliance (e.g., IDEIA, NCLB), and neuropsychological assessm ent and intervention. Overall, school psychologists in this particular sample repo rted engaging in a wide variety of CPD activities. The percentage of school psychologists who reported participation in specific CPD subject areas ranged from 14% to 47%. The finding that standardized psychoeducational ass essment was one of the most commonly endorsed CPD subject area is somewhat comp arable to previous studies in which school psychologists reported engaging in ass essment-related CPD areas (e.g., Fowler & Harrison, 2001). However, previous studies have not differentiated between authentic (e.g., Curriculum-Based Measurement [CBM] ) and traditional (e.g., standardized psychoeducational) types of assessment which makes it difficult to determine specific CPD activities of school psychol ogists. The current study clearly differentiated between different types of assessmen t and revealed that twice as many school psychologists reported engaging in standardi zed psychoeducational assessment CPD than in academic screening/progress monitoring (e.g., CBM). Furthermore, even fewer school psychologists reported engaging in beh avioral and social/emotional

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153 assessment. These results highlight the importance of distinguishing between types of assessment practices in order to gain a more accura te picture of school psychologists’ specific CPD activities and needs. Another possible explanation for these results inc ludes the frequently cited finding that school psychologists continue to engag e in more traditional job activities despite the recognized need for role change (Bramle tt et al., 2002; Curtis et al., 2002; Curtis et al., 2006; Hosp & Reschly, 2002). School psychologists in this sample reported that an average of 80.4% of their time was devoted to activities related to special education (Curtis et al., 2006). A plausible explan ation may include that school psychologists’ day to day practice guides their CPD activities. Previous findings have shown that school psychologists rated their CPD nee ds as being likely to influence actual CPD involvement (Fowler & Harrison, 2001). On the o ther hand, if school psychologists want to engage in an expanded role, it might be arg ued that they need to engage in CPD activities that would prepare them for that expande d role. Interestingly, behavioral intervention was the mos t commonly reported CPD subject area activity among school psychologists in cluded in this sample. These results could be explained by a wide variety of reasons, su ch as personal interests, district/building-wide initiatives, and legal manda tes. An interesting hypothesis is that the requirements of IDEA regarding manifestation determ inations, functional behavioral assessment (FBA), and designing individualized beha vior intervention plans (BIP) for those students who have not responded to interventi on have required school psychologists to develop more skills in the area of behavioral assessment and intervention. Crimmins and Farrell (2006) explained how reauthorizations of IDEA have

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154 required school personnel to gain skills related to behavioral assessment and intervention (e.g., FBA, BIP). School personnel are required to conduct a FBA and BIP for students who have been suspended for 10 days or placed in an alternative educational setting in order to determine whether their behavior relates t o a disability. The law also specifies that BIPs should be reviewed and modified as necess ary for those students with existing behavioral plans so that they receive appropriate s ervices. Furthermore, the 2004 reauthorization of IDEA went a step further and ide ntified the need to use system-wide, universal behavioral approaches in order promote su ccessful behavioral outcomes for students. These legal mandates most likely require school psychologists to acquire a greater repertoire of skills associated with behavi oral assessment and intervention (e.g., systems change, implementation of universal support s). As a result, school psychologists may seek out CPD in these areas. This could be one possible reason why school psychologists in this sample most commonly endorsed the behavioral interventions CPD subject area. Another notable finding of the present study indica tes that approximately 26% of school psychologists reported that they participate d in response to intervention CPD during the 2004-2005 school year. These findings ar e encouraging considering the recent focus on Response to Intervention (RtI) as a data-b ased decision-making process that can help students to meet academic, behavioral, and soc io-emotional goals. The IDEIA (2004) includes requirements regarding how schools are to determine whether a child has a specific learning disability. The IDEIA (2004) pr ovides schools with the option to use data-based evidence regarding how well a student re sponds to scientifically-based

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155 interventions (i.e., RtI) to decide on the presence or absence of a specific learning disability (Brown-Chidsey, 2005). Response to Intervention has growing empirical sup port and the potential to redefine service delivery in the schools (Case, Spe ece, & Molloy, 2003; Marston, Muyskens, Lau, & Canter, 2003; Vaughn, Linan-Thomps on, & Hickman-Davis, 2003). It is encouraging that some school psychologists are e ngaging in CPD related to RtI as it shows that some practitioners are making strides to engage in the use of best professional practices and align their practices with both IDEIA and NCLB. However, one must be cautious because RtI may have many different meanin gs depending on the school setting, context, administrative leadership, and state speci fic regulations. Therefore, this particular finding should be interpreted with that possibility in mind. Another noteworthy finding is that there was a stat istically significant negative relationship between the engagement of school psych ologists in CPD activities relating to standardized psychoeducational assessment and in CP D relating to response to intervention ( r = -.20). One possible explanation is that those pra ctitioners who spend a substantial amount of time in activities related to psychoeducational assessment are most likely to not have time, or possibly the skill set, to work within a response to intervention framework. Furthermore, it is likely that a school district that employs the discrepancy model to determine special education eligibility wo uld not be as supportive or knowledgeable of RtI practices. This finding also p rovides support to the current bifurcation of the school psychology field. Profess ionals within the field differ on which type of service delivery they believe is appropriat e to effectively serve students. Debate is centered on whether the traditional IQ-achievement discrepancy or the RtI service

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156 delivery framework is most efficient and effective. It is plausible that school psychologists who endorsed response to intervention CPD would be more likely to engage in professional practices related to RtI and believe that it is a more effective form of service delivery. These school psychologists wou ld be less likely to report engaging in standardized psychoeducational assessment CPD as th ese types of CPD activities would not align with their professional beliefs and pract ices. Another notable finding is that there was a statist ically significant positive relationship between CPD relating to academic scree ning/progress monitoring and to response to intervention ( r = .28). This relationship is not surprising conside ring that academic screening/progress monitoring practices (e .g., CBM) are an integral part of successfully implementing a response to interventio n service delivery framework (Batsche et al., 2005). The use of authentic assess ments, such as CBM, is critical in detecting small changes in student progress within a response to intervention framework (Shinn, 2002). An examination of changes in student progress using CBM data is a defining feature within a RtI framework because dat a guides the decision-making process to determine a student’s response to intervention a nd whether and intervention must be changed, modified, or discontinued (Batsche et al., 2005) Therefore, it is highly plausible that a school psychologist would engage in both aca demic screening/progress monitoring and response to intervention CPD due to the nature of the RtI service delivery framework. Logistic regression analyses were performed in ord er to determine which demographic characteristic, professional practices, and employment condition variables

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157 were most predictive of participation in each CPD s ubject area. A summary of the findings for each category is reported below. Demographic Characteristics. Bivariate correlations revealed that there was a statistically significant negative relationship bet ween age and response to intervention (r= -.14), which suggests that those school psychologis ts who are older may engage in less response to intervention CPD. This finding, althoug h of small practical significance, may be due to various factors, such as differences in p re-service training (e.g., older school psychologists receiving more traditional training), lack of perceived need to engage in response to intervention CPD, or personal interests It is important to note that this finding is also significant considering that nation al data indicate that the field continues to grow older. Curtis et al. (2006) reported that b etween 1990 and 2005 the percentage of all school psychologists who were 40 years of age o r younger declined 10% (i.e., 43.2 to 33.1), whereas those 50 years of age or older incre ased 27.3% (i.e., 20.2 to 47.5). Furthermore, almost one out of 10 (9%) school psych ologists is now 60 years of age or older. The continued aging of the field may have im plications for CPD participation, especially in CPD activities relating to more progr essive knowledge areas and skill sets (e.g., RtI). Demographic characteristic variables as a set (i.e. gender, years of experience, highest degree earned, and NCSP held) did not relia bly distinguish between those school psychologists who engaged in the following CPD subj ect areas and those who did not: (a) standardized psychoeducational assessment; (b) academic screening/progress monitoring; (c) behavioral assessment; (d) behavior al interventions; (e) social/emotional assessment; (f) social/emotional interventions; (g) response to intervention; (h) crisis

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158 intervention; and (i) other. Alternatively, the set of demographic characteristic variables reliably distinguished between those school psychol ogists who did and did not participate in the following CPD subject areas: (a) academic in terventions; and (b) consultation/problem-solving. However, there were n o individual predictors that were statistically significant in either of these logist ic regression analyses. No one predictor could be identified as making a significant unique contribution to either model. These results suggest that these demographic variables to gether had some sort of synergistic effect that helped to explain participation in thes e CPD subject areas, or there are other variables not included in the analysis that are bet ter predictors of CPD participation. Despite the fact that the overall models for both a cademic interventions and consultation/problem-solving CPD were statistically significant, the strength of these predictions was very small ( R= .0190 for academic interventions; R= .02 for consultation/problem-solving). Overall, gender, yea rs of experience, highest degree earned, and NCSP held did not meaningfully predict participation/non-participation in the majority of CPD subject areas. In a related study, Fowler and Harrison (2001) found no relationship between demographic characteristic var iables (i.e., age, gender, credential status, marital status, parental status, and years of experience) and CPD needs. Notably, their study compared needs with demographic charact eristics, and the current study compared actual CPD engagement and demographic char acteristics. Conversely, the findings of the current study are s omewhat surprising considering that relationships between demographic characterist ics and professional practices have been found (Curtis et al., 2002). Curtis et al. (20 02) found that school psychologists with more training and years of experience in school psy chology spent more time in non-

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159 traditional activities, such as individual counseli ng, consultation, and in-services and less time in more traditional activities, such as comple ting initial evaluations and total percentage of time spend in activities related to s pecial education. One might anticipate that professional practices drive CPD activity. For example, it is plausible that school psychologists with more years of experience engage in more consultation, and, thus, more CPD in the area of consultation. However, this type of statement was not supported by the data generated from the current study. The present study did not yield any findings indi cating that gender played a significant role in participation in any CPD subjec t area. These findings were not surprising considering national data that has yield ed mixed results regarding relationships between gender and professional roles. Although som e studies have found that female school psychologists reported spending more time in assessment-related activities and males reported engaging in more systems-level chang e roles, the majority of the research findings on a national level indicated no clear res ults or trends related to gender and professional roles (Curtis et al., 2002; Wilson and Reschly, 1995). Professional Practices. Bivariate correlations indicated that there was a statistically significant positive relationship bet ween standardized psychoeducational assessment CPD and the percentage of total work tim e related to special education ( r = .14) and initial evaluations ( r = .16). This suggests that those school psychologis ts who engaged in standardized psychoeducational assessmen t CPD were more likely to spend a greater percentage of time in activities related to special education and complete a greater number of initial evaluations. This finding may len d support to the idea that actual professional practice is associated with CPD activi ty. A statistically significant negative

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160 relationship was found between social/emotional int erventions CPD and initial evaluations ( r = -.15). The data also suggest that school psycholo gists who engaged in social/emotional interventions CPD were more likely to complete fewer initial evaluations. Social/emotional interventions are con sidered a more non-traditional activity, which may limit the amount of time a scho ol psychologist has to devote to more traditional activities related to special education eligibly. Professional practice variables as a set (i.e., per centage of total work time in activities related to special education, number of psychoeducational evaluations completed relating to initial determination of spec ial education eligibility, and number of special education reevaluations completed) did not reliably distinguish between those school psychologists who engaged in the following C PD subject areas and those who did not: (a) academic screening/progress monitoring; ( b) academic interventions; (c) behavioral assessment; (d) behavioral interventions ; (e) social/emotional assessment; (f) crisis intervention; and (g) other. Alternatively, the set of professional practice variables reliably distinguished between those school psychol ogists who did and did not participate in the following CPD subject areas: (a) standardiz ed psychoeducational assessment; (b) social/emotional interventions; (c) consultation/pr oblem-solving; and (d) response to intervention. Findings indicated that initial evaluations, reeval uations, and total percentage of time spent in activities related to special educati on as a set reliably distinguished between those school psychologists who engaged in standardi zed psychoeducational assessment CPD and those who did not. However, the strength of the prediction was very small ( R= .04). Furthermore, both initial evaluations complet ed and total percentage of time in

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161 activities related to special education each made a statistically significant unique contribution to the regression equation. Odds ratio s revealed that school psychologists who reported completing a greater number of initial evaluations were more likely to participate in standardized psychoeducational asses sment CPD as compared to those who reported completing a fewer number of initial evalu ations. Those school psychologists who reported spending a greater percentage of time in activities related to special education were more likely to participate in standa rdized psychoeducational assessment CPD as compared to those who reported spending a le ss percentage of time in activities related to special education. Findings also indicated that the set of professiona l practice variables reliably distinguished between those school psychologists wh o engaged in social/emotional interventions CPD and those who did not. However, t he strength of the prediction was very small ( R = .03) Initial evaluations completed made a statistically significant unique contribution to the regression equation. Odds ratio s revealed that school psychologists who reported completing fewer initial evaluations w ere more likely to participate in social/emotional interventions CPD as compared to t hose who reported completing a greater number of initial evaluations. Additionally, results indicated that the set of pro fessional practice variables reliably distinguished between those school psychol ogists who engaged in consultation/problem-solving CPD and those who did not. However, the strength of the prediction was very small ( R = .01) Total percentage of time in activities related to special education evaluations made a statistically significant unique contribution to the regression equation. Odds ratios revealed that scho ol psychologists who reported a less

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162 total percentage of time in activities related to s pecial education were more likely to participate in consultation/problem-solving CPD as compared to those who reported a greater total percentage of time. Lastly, findings revealed that the set of professio nal practice variables reliably distinguished between those school psychologists wh o engaged in response to intervention CPD and those who did not. However, th e strength of the prediction was very small ( R = .01) Total percentage of time in activities related to s pecial education evaluations made a statistically significant unique contribution to the regression equation. Odds ratios revealed that school psychologists who reported a less total percentage of time in activities related to special education wer e more likely to participate in response to intervention CPD as compared to those who report ed a greater total percentage of time. Collectively, these results suggested that professi onal practices have some influence, although very small, on whether school p sychologists engage in certain areas of CPD. Professional practices variables did help t o predict participation in standardized psychoeducational assessment, social/emotional inte rventions, consultation/problemsolving, and response to intervention CPD. School p sychologists who were more likely to engage in non-traditional forms of CPD (i.e., socia l/emotional interventions, consultation/problem-solving, and response to inter vention) were less likely to engage in professional practices related to special education (e.g., initial evaluations). Again, one might expect that actual job roles or activities dr ive CPD areas of need and participation. If this were the case, then school psychologists wh o engage in more traditional roles (e.g., completing initial evaluations) would endorse parti cipation in CPD areas related to more traditional roles, and those school psychologists w ho spend less time in such roles could

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163 have more time to engage in more non-traditional ac tivities, and thus, may participate in corresponding CPD activities. Interestingly, reevaluations did not make a signifi cant unique contribution to any of the CPD subject areas. The reason for these find ings is unclear considering that initial evaluations and total percentage of time in activit ies related to special education were found to be influential predictors of CPD participa tion in some areas. One possible explanation is that IDEIA (2004) requires that a re evaluation conducted under Section 614(a)(2)(A) occur not more frequently than once a year and at least once every three years (unless parent and LEA decide otherwise). Thu s, the frequency of reevaluations may vary considerably depending upon the school yea r. Employment Conditions. Bivariate correlations revealed that there was a statistically significant negative relationship bet ween social/emotional interventions CPD and ratio of individual students to school psycholo gist ( r = -.11), indicating that school psychologists who report lower ratio are more likel y to participate in social/emotional interventions CPD. Previous research has found that greater ratios are associated with more time spent in activities related to special ed ucation and lower ratios are associated with more time spent in direct service delivery (e. g., counseling groups, individual counseling) (Curtis et al., 2002; Curtis et al., 20 02; Reschly, 2000; Smith, 1984). It can be argued that lower ratios allow school psychologists to engage in more non-traditional activities, such as social/emotional interventions, which may lead them to participate in social/emotional CPD. Employment condition variables as a set (i.e., scho ol setting, ratio of individual students to school psychologist, administrative sup ervision, and clinical supervision) did

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164 not reliably distinguish between those school psych ologists who engaged in the following CPD subject areas and those who did not: (a) stand ardized psychoeducational assessment; (b) academic interventions; (c) behavio ral assessment; (d) behavioral interventions; (e) social/emotional assessment; (e) consultation/problem-solving; (f) response to intervention; (g) crisis intervention; and (h) other. Alternatively, the set of employment condition variables reliably distinguish ed between those school psychologists who did and did not participate in th e following CPD subject areas: (a) academic screening/progress monitoring; and (b) soc ial/emotional interventions. Findings indicated that school setting, ratio, ad ministrative supervision, and clinical supervision as a set reliably distinguishe d between those school psychologists who engaged in academic screening/progress monitori ng CPD and those who did not. However, no one predictor could be identified as ma king a significant unique contribution to the model. These results suggest th at these employment condition variables together had some sort of synergistic eff ect that helped to explain participation in academic screening/progress monitoring, or there are other variables not included in the analysis that are better predictors of CPD part icipation in this area. Despite the fact that the overall model for academic screening/progr ess monitoring CPD was statistically significant, the strength of this prediction was ve ry small ( R= .02). Findings also indicated that the set of employment condition variables reliably distinguished between those school psychologists wh o engaged in social/emotional interventions CPD and those who did not. However, t he strength of the prediction was very small ( R = .02). Ratio of individual students to school psyc hologist made a statistically significant unique contribution to th e regression equation. Odds ratios

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165 revealed that school psychologists who reported a l ower ratio were more likely to participate in social/emotional interventions CPD a s compared to those who reported a higher ratio. Overall, school setting, ratio, administrative supe rvision, and clinical supervision did not help to predict CPD participation in majori ty of subject areas. It was anticipated that school setting may have an impact on CPD parti cipation, considering past research that has shown a relationship between professional practices and school setting (Curtis et al., 2002; Curtis et al., 2002). For example, Curti s et al. (2002) found that rural school psychologists conducted significantly more reevalua tions as compared to urban and suburban practitioners. Additionally, practitioners in urban and suburban settings served significantly more students via consultation as com pared to practitioners in rural settings. Again, one might anticipate that activity drive CPD needs. Another possible reason to suspect that school setting may be associated with CPD is that different CPD needs have been found among school psychologists from rural, s uburban, and urban settings. Reschly and Connolly (1990) found statistically significant differences in continuing professional development needs among all groups. Rural practitio ners reported greater CPD needs in assessment of neuropsychological functioning, remed ial educational programs, and behavioral interventions in the general education c lassroom. Urban practitioners reported greater CPD needs in adaptive behavior assessment, nonbiased assessment techniques, and minority student education. Both urban and rura l practitioners reported higher CPD needs in interventions for students who receive ser vices in mild/educable mentally handicap programs. Rural, urban, and suburban all r eported significant CPD needs in bilingual education. Notably, many of the CPD categ ories noted in the study were not

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166 included in the current study, which may help expla in inconsistent results. It would have been interesting to know if perceived needs correla ted with actual CPD activity as other studies have found (Fowler & Harrison, 2001). Conversely, one study examined the CPD activities o f urban and rural school psychologists. That study revealed no significant d ifferences in total hours spent in CPD and total number of different CPD activities of urb an and rural school psychologists (Hughes and Clark, 1981), suggesting that school se tting may not be a strong indicator of CPD activity among school psychologists. However, t he results of that particular study should be interpreted with caution because only sch ool psychologists from Virginia were surveyed. Interestingly, the respondents practicing in rural school settings perceived that they received generalist training, had fewer suppor t services, had more involvement in program planning, and experienced more professional isolation as compared to school psychologists in urban settings. These perceived di fferences may have implications for CPD activities, although none were found in the pre sent study. The research exploring school setting in relation t o professional roles and CPD practices is exploratory and inconclusive in nature There are no known studies that specifically examined school setting and different types of CPD. The current study provides preliminary support that CPD activities of school psychologists are not necessarily related to school setting. It is possib le that differences in roles and CPD needs may be more influenced by a combination of other fa ctors (e.g., students to school psychologist ratios, district priorities, or fundin g influences) as well as school setting. Alternatively, one may hypothesize that school sett ing could be an important factor related to CPD. For example, larger school district s may be more likely to provide CPD

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167 opportunities for school psychologists as opposed t o small school districts. Large school district may have more resources available to provi de CPD whereas smaller districts may be limited in their resource allocation. However, s mall districts may benefit from the presence of organizations (e.g., The Institute for Small and Rural Districts in Florida) that are specifically designed to provide services to sm all districts that may not have access to many CPD opportunities. These potential hypotheses related to school setting indicate that more research is needed to explore the impact of school setting on the CPD practices of school psychologists. Additionally, the current study found that school p sychologists who reported a lower ratio were more likely to participate in soci al/emotional interventions CPD as compared to those who reported a higher ratio. Rati o has been found to impact professional practices and service delivery. In fac t, Reschly (2000) noted that student to school psychologist ratios are one of the most “rob ust of the influences on school psychology practice in the public schools” due to i ts significant impact on job satisfaction, assessment practices, and amount of t ime spent in activities related to special education (p. 513). Moreover, Curtis et al. (2002) stated the student to school psychologist ratio are useful data that can be util ized to inform legislators and policymakers about the influence of ratios on the n ature of services school psychologists are able to provide in the schools. There is a possibility that ratio also may impact t he CPD activity of school psychologists due to its influence on professional practices. For example, role change and/or expansion (e.g., consultation, prevention) h ave been found to be associated with a student ratio of 1:1500 or lower (Smith, 1984). Two national studies also confirm that

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168 ratios impact the types of services that are delive red in the schools. Curtis et al. (2002) reported that the greater ratio of student to schoo l psychologist was associated with more initial special education evaluations completed, gr eater number of special education reevaluations completed, and a greater percentage o f time spend in activities related to special education. Conversely, smaller ratios were associated with school psychologists who reported engaging in more counseling of individ ual students and group counseling as compared with school psychologist who reported grea ter ratios. Furthermore, Curtis et al. (2002) found that the greater the ratio, the greate r the number of activities related to special education, which may limit the potential fo r role expansion. Results also indicated that low ratios were associated with school psychol ogists engaging in more preferred roles. Hosp and Reschly (2002) examined relationships betw een ratios according to region and service delivery. It was found that thos e regions with low ratios (i.e., Northeast and Mid-Atlantic) administered more proje ctive measures and conducted more anecdotal behavioral observations as compared to re gions with higher ratios. Regions with high ratios (i.e., East South Central, West So uth Central, West North Central, and South Atlantic) spent more hours per week on assess ment-related activities as compared to those regions with lower ratios. Those findings lend support to the finding of the p resent study that school psychologists who reported lower ratios were more l ikely to engage in more nontraditional roles, such as engaging in social/emoti onal interventions CPD. It is possible that those school psychologists with lower ratios a re more likely to engage in

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169 social/emotional intervention and, thus, participat e in CPD in that area to supplement their current role. The literature on supervision and CPD activities of school psychologists is scant. However, the present study did support previous fin dings in that few school psychologists receive administrative and/or clinica l supervision (Chafouleas, Clonan, & Vanauken, 2002; Fischetti & Crespi, 1999; Ross & Go h, 1993; Zins, Murphy, & Wess, 1989). Approximately 48% of school psychologists in this study reported receiving administrative supervision, and about 12% of practi tioners reported receiving clinical supervision. Clearly, this is an area of concern fo r the field, considering that clinical supervision is one essential component of CPD. Find ings indicated that administrative and clinical supervision received were not related to participation in any CPD subject area. These results may be attributed to the lack o f overall supervision received by school psychologist in this sample. Another possibility is that administrative supervision, which consists of monitoring of job duties, logistics of service delivery, and consumer satisfaction, traditionally does not encompass CPD. One would anticipate that of these types of supervision, clinical supervision would be more associated with CPD activity. However, clinical supervision was not received by t he majority of this sample, and it is unknown how frequently supervision occurred for tho se practitioners who did receive this type of supervision. It may be that school psy chologists did not receive adequate amounts of supervision, which is not unlikely consi dering that past studies have found that supervision occurs on an as needed basis or le ss than NASP and APA recommendations (Chafouleas et al., 2002; Fischetti and Crespi, 1999). Supervision may

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170 not be the most reliable avenue to obtain professio nal development for school psychologists when taking these issues related to s upervision into consideration. Regional Differences. Findings revealed that there was a statistically s ignificant association between region and participation in aca demic screening/progress monitoring, behavioral assessment, social/emotional assessment, social/emotional intervention, response to intervention, and crisis intervention C PD. Overall, the Northeast, East North Central, and East South Central regions were region s of most interest in this study. The percentage of school psychologists in the Northeast region (i.e., CT, MA, ME, NH, RI, VT) appeared higher for participation in social/emo tional assessment and intervention CPD and lower for response to intervention CPD as c ompared to other regions. Previous research has found that the Northeast region had on e of the highest means of projective/personality tests administered per month (Hosp & Reschly, 2000). Projective measures are typically used to assess social/emotio nal functioning and planning for intervention, which may help to explain these findi ngs. The Northeast region was also found to have low means for IQ/ability and achievem ent tests administered per month, suggesting that an emphasis on direct intervention and less emphasis on psychometrics (Hosp & Reschly, 2000). Furthermore, Hosp and Resch ly (2000) found that the Northeast region had low ratios, which may add support to the previous finding of the current study that lower ratios were associated with social/emoti onal intervention CPD. The percentage of school psychologists in the Northeast region was lower than expected for response to intervention CPD. There is limited empirical suppor t for the use of projective/personality assessments and their usefulness in linking assessm ent to intervention, suggesting that research may not be guiding practice (Seitz, 2001). On the other hand, response to

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171 intervention is guided by evidence-based assessment s and interventions and does not endorse the use of assessment and intervention that are not empirically validated by research. Results for the East North Central region (i.e., IL IN, MI, OH, and WI) indicated that the percentage of school psychologists in this region appeared higher for participation in academic screening/progress monito ring CPD and lower for social/emotional assessment CPD as compared to othe r regions. These findings are consistent with previous research that has found sc hool psychologists in the East North Central and West North Central regions were more li kely to use data-based, low inference methods of data collection and fewer proj ective measures (Hosp & Reschly, 2000). Notably, the percentage of school psychologi sts in the East North Central region was one of the highest for participation in respons e to intervention CPD. Academic screening/progress monitoring activities coincide w ith an RtI framework. More specifically, RtI incorporates the use of data-base d academic screening/progress monitoring measures (e.g., CBM) in order to assess student performance and make databased decisions (Batsche et al., 2005). Results for the East South Central region (i.e., AL KY, MS, and TN) indicated that the percentage of school psychologists in this region appeared lower for both social/emotional interventions and behavioral asses sment CPD as compared to other regions. Previous research has found that school ps ychologists in the East South Central region administered more intelligence than every re gion expect the South Atlantic, and administered the most achievement measures per mont h out of any region (Hosp & Reschly, 2002). These findings suggest that this pa rticular region may devote a

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172 substantial amount of time to more traditional scho ol psychology activities, such as psychoeducational assessment, which would leave les s time for engagement in more nontradition activities. Furthermore, Hosp and Reschly (2002) reported that the East South Central region had a mean ratio well above 2,000 st udents per school psychologist. Previous research has found that greater ratios are associated with more time spent in special education activities (e.g., standardized ps ychoeducational assessment) and lower ratios are associated with more time spent in direc t service delivery (i.e., social/emotional interventions) (Curtis et al., 2002). Collectively, these findings may help to explain the low percentage of school psychologists in this regi on who reported participating in social/emotional interventions CPD. The finding that a low percentage of school psychol ogists reported participating in behavioral assessment CPD is unclear when compar ed to previous research. Previous research has found that school psychologists in the East South Central region completed the highest mean number of behavior rating scales a s compared to all other regions (Hosp & Reschly, 2002). Although behavior rating scales a re considered a part of a behavioral assessment, they are norm-referenced and their admi nistration is typically limited to a parent or teacher completing the scale. Behavior ra ting scales are not as time consuming as compared to other behavioral assessment activiti es, such as FBA’s and classroom observations. High ratios can impact service delive ry and place more restrictions on a school psychologist’s time (Curtis et al., 2002). T hus, the administration of behavioral rating scales may be a more feasible assessment met hod. School psychologists from this region may have administered more behavioral rating scales in previous research;

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173 however, that may not necessarily reflect engagemen t in behavioral assessment or behavioral assessment CPD. Limitations of the National Database There are several potential threats to internal and external validity inherent in all survey research and, therefore, to the database to be used to answer the research questions posed in this study. These limitations need to be c onsidered when reviewing the findings because potential threats to validity may represent competing explanations for the results of the study (Johnson & Christenson, 2004). Limita tions to be considered include: (a) social desirability; (b) population validity; (c) c omparability of 2005 NASP membership and the 2004-2005 NASP national database; (d) poten tial differences between responders and non-responders; (e) temporal validity; and (f) the retrospective nature of the data. First, a threat to internal validity exists because participants may provide socially desirable responses. Social desirability bias is de scribed as “the tendency of individuals to deny socially undesirable actions and behaviors and to admit socially desirable ones” (Chung & Monroe, 2003, p. 291). Consequently, parti cipants who comprised the database may have responded to survey items in what they bel ieved was a more socially desirable manner (e.g., responses that reflected what they be lieved others think school psychologists should be doing in terms of professio nal practices), which may have interfered with the accuracy of responses. Second, a potential threat to external validity is that only responses from school psychologists who are members of NASP comprised the national database. The creation of the national database did not account for the po ssibility that those practitioners who join NASP may differ from those who either do not j oin or who join different

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174 professional organizations (Reschly & Wilson, 1995) This is described by the term population validity, which refers to the ability to generalize findings from a sample to a larger target population of individuals who did not participate in the study (Johnson & Christensen, 2004). Third, data indicated that the 2004-2005 national d atabase respondents were comparable to the 2005 NASP membership for gender, but not ethnicity, highest degree earned, or age. The 2004-2005 national database may not necessarily reflect the 2005 NASP membership. Therefore, the results of this stu dy should be interpreted with caution as this sample was taken from the 2004-2005 nationa l database. It has been noted in the literature that sampling school psychologists is a challenging task because there is not a single comprehensive listing of all school psycholo gists practicing in the United States (Curtis et al., 2004). However, Fagan (1994) estima ted that NASP membership represents approximately 70% of all school psychologists and s uggests that NASP membership probably represents one of the best resources for s ampling the field. In addition, the use of the NASP membership list to obtain participants has resulted in higher return rates (e.g., Curtis et al., 2002 return rate= 67.9%; Curt is et al., 1999 return rate= 74%; Graden & Curtis, 1991 return rate= 79%; Hosp & Reschly, 20 02 return rate= 74%; Reschly & Wilson, 1995 return rate= 80%) as compared to other studies that have used alternative sampling methods (Smith, 1984 return rate=49%; Meac ham & Peckham, 1978 return rate=20%; Chafouleas et al., 2002 return rate=37%). Fourth, there may be a difference between responden ts and non-respondents. These two groups may possess different demographic characteristics, engage in different professional practices, and represent different emp loyment conditions that could impact

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175 the content of the national database if non-respond ents had chosen to participate (Curtis, et al., 2004). Fourth, Johnson and Christensen (200 4) describe temporal validity as the extent to which the results of the study can be gen eralized across time. The database was cross-sectional because participants only reported on professional practices during the 2004-2005 school year. The database is comprised of responses from school psychologists at one point in time. There is no gua rantee that primary and secondary analyses, as well as the respective findings, will be applicable in the future. On the other hand, the purpose for creating the database is to p rovide a description of the field of school psychology during one specific period of tim e. Lastly, retrospective data comprised the database which may have resulted in participants reporting inaccurate information (i.e. they had to recall and estimate information). In response to survey item 24, partic ipants indicated that 72.02% had used estimates, 35.23% used a personal log, 10.05% used a central database, and 1.75% used an alternative method to collect data to answer Ite ms 27 through 35 (the responses total more than 100% because respondents were able to end orse more than one option). Thus, the majority (72.02%) of participants reported esti mation as the method to answer one or more of these items. Therefore, it should be noted that the database represents estimates of the demographic characteristics, professional pr actices, and employment conditions of school psychologists in the United States. Implications for Practice and Future Research There is limited research examining CPD within the field of school psychology. This dearth of research is unfortunate because scho ol psychologists value and perceive CPD and supervision as important in their professio nal careers (Chafouleas et al., 2002;

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176 Fowler & Harrison, 2001; Guest, 2000). The findings of this study indicate that school psychologists engaged in a variety of CPD activitie s during the 2004-2005 school year. These findings are encouraging as they suggest that school psychologists are branching out and engaging in more non-traditional types of C PD activities. Even though school psychologists engaged in a varie ty of CPD activities, school psychologists most frequently reported participatio n in behavioral interventions and standardized psychoeducational assessment CPD subje ct areas. These findings coincide with what is typically thought of as the traditiona l school psychologist role—academic testing and behavioral intervention/modification. T his speaks to the need for school psychologists to further expand their CPD activitie s to more non-traditional areas, such as academic screening/progress monitoring and response to intervention. In light of legislative mandates and increased accountability f or outcomes, school psychologists would benefit from directing their CPD activity to areas that are in alignment with such initiatives. However, it should be noted that these data were only based on the 2004-2005 school year. As a result, the availability of more progressive types of CPD (e.g., RtI, academic screening/progress monitoring, and academi c intervention) as well as professional interest in these CPD topics may not h ave been as great during 2004-2005 as compared to present day. Therefore, it is very enco uraging that school psychologists endorsed more progressive CPD subject areas (e.g., RtI, academic screening/progress monitoring) considering the limited availability of CPD in these areas. Recently, professional associations (e.g., NASP) have hosted conferences and summer institutes that have focused on issues pertaining to accountab ility, use of evidence-based practices, academic assessment and intervention, and response to intervention. These opportunities

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177 for CPD have likely provided school psychologists w ith the chance to gain knowledge and skills in more progressive forms of service del ivery. Few significant relationships were found between de mographic characteristics professional practices, and employment conditions a nd CPD subject areas. These findings suggest that there are likely other variables, or f actors, that impact the CPD of school psychologists. Efforts should be made to identify f actors that may represent barriers or enablers to CPD. The identification of barriers and enablers can facilitate the development of more effective CPD programs and init iatives. Successful implementation of CPD at the district and school building level ca n contribute to improved service delivery. Lastly, regional differences found in thi s study, which suggest that some areas of the country are more likely to engage in certain areas of CPD. This information may be used to inform professional organizations, train ing institutions, or other agencies of regions that are practicing progressive forms of se rvice delivery. Selected regions may be identified as models and should be viewed as exempl ars of best practice in school psychological service delivery. Future research should investigate issues beyond ga ining general information on CPD (e.g., frequency, format, perceived needs) to m ore in-depth topics, such as: (a) identification of other key factors that are associ ated with CPD participation and nonparticipation; (b) how CPD is (or is not) linked to school-wide data or initiatives; (c) school psychologists’ perceptions of CPD; and (d) h ow school psychologists can be integrated into effective models of CPD at the dist rict and building levels. First, research should investigate what factors are most predictive of CPD activity. The results of this study did not find many variables that were predict ive of participation. Data suggest that

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178 there are other variables not included in the analy ses that may better help to predict CPD. The present study only examined the CPD subject are as endorsed by school psychologists during the 2004-2004 school year. The study did not investigate the frequency, format, amount, or nature of CPD or who was responsible for the types of CPD endorsed by school psychologists because the survey did not sol icit these types of information. It would be important to gain a more comprehensive pic ture of CPD in school psychology as there are likely systemic variables that influen ce CPD subject area participation, frequency, format, and amount. For example, state C PD requirements, guidelines for the renewal of professional practice credentials, prese nce of major statewide initiatives that include CPD components, and membership in state and /or national professional organizations may impact CPD of school psychologist s. Future research might inquire about this type of detailed information related to CPD in order to gain a better understanding of factors that are related to CPD pa rticipation and non-participation. Second, it is critical to examine actual CPD activi ty, how it relates to school needs, and whether CPD is directly addressing those needs. This is a key area of future research as recent educational legislation (i.e., N CLB, IDEIA) has emphasized student outcomes and accountability for those outcomes. Pra ctitioners should go beyond selecting CPD because they are “interested in” or “ think it might be useful” and make an effort to link CPD activity to student data. Future studies could investigate the consistency between student data and CPD activities of the district or school. Lack of consistency would warrant an in-depth investigation of what factors prevent linking CPD to student data. For example, lack of consistency c ould be a product of train and hope CPD models or unclear school-wide systems-change pl ans that are not driven by data.

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179 Additionally, it would be important to determine wh at procedures or policies need to be in place in order to promote such linkages. Effecti ve CPD evaluations methods also must be an integral part of such policies. It is recomme nded that CPD evaluation go beyond pre-post test knowledge measures to more authentic change, such as student outcomes and behavioral change (NSDC, 2001). Third, future research may explore the perceptions of school psychologists regarding CPD. Only one qualitative study was found that asked school psychologists specific questions about their career development ( Guest, 2000). It would be informative to gain the following information via qualitative i nquiry: (a) What do school psychologists believe is the purpose of CPD?; (b) H ow do school psychologists perceive CPD fitting into their professional role?; (c) What are perceived barriers and enablers to CPD?; and (d) What are the primary reasons that sch ool psychologists select certain CPD activities over others? Answers to these questions would guide future research and provide the field with description information that can be used to improve CPD efforts in the field. Lastly, it would be beneficial to investigate how s chool psychologists can be integrated into effective models of CPD at the dist rict and building levels. As previously mentioned, the NSDC (2001) advocated for building-l evel CPD plans that are driven by student data. However, NSDC does not specifically i dentify how different professionals may integrate themselves into such a CPD plan. It w ould be important to assess the skills of school psychologists and to determine how they c ould best be utilized in a CPD model. For example, school psychologists could collect dat a, facilitate meetings, determine CPD needs based on data, or serve as coaches. School ps ychologists have the potential to

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180 contribute a great deal of knowledge and skills tha t are needed to facilitate school-wide CPD efforts. Conclusion The present study examined the CPD activities of s chool psychologists, the relationship between demographic characteristics, p rofessional practices, and employment conditions and CPD, and regional differe nces in CPD. Findings indicated that school psychologists did not engage in high pe rcentages of CPD in any of the 11 subject areas. School psychologists reported the hi ghest percentages of participation in behavioral interventions and standardized psychoedu cational assessment CPD. Very few relationships were found among demographic characte ristics, professional practices, and employment conditions and each CPD subject area, su ggesting that other variables not included in the analyses may better predict CPD par ticipation. Regional differences were found in the CPD subject areas of academic screenin g/progress monitoring, behavioral assessment, social/emotional assessment, social/emo tional intervention, response to intervention, and crisis intervention. Several limi tations were noted that are important to consider when interpreting the results of this stud y. Implications of the study were described for each major finding. Additional direct ions for future research were generated that can contribute to the CPD literature in school psychology.

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186 Florida Department of Education. (2006). The response to intervention (RtI) model. Retrieved on April 11, 2006 from http://www.firn.edu/doe/commhome/pdf/y2006-8.pdf Fowler, E. & Harrison, P. L. (2001). Continuing pr ofessional development needs and activities of school psychologists. Psychology in the Schools, 38, 75-88. Franklin, M., & Duley, S.M. (2002). Best practices in planning school psychology service delivery programs: An update. In A. Thomas & J. Grimes (Eds.), Best Practices in School Psychology (4th ed.) (pp.145-158). Bethesda, MD: The National Association of School Psychologists. Furlong, M., Morrison, G., & Pavelski, R. (2000). T rends in school psychology for the 21st century: Influences of school violence on profess ional change. Psychology in the Schools, 37 81-90. Garet, M. S., Birman, B. F., Porter, A. C., Desimon e, L., Herman, R., & Yoon, K. S. (1999). Designing effective professional development: Less ons from the eisenhower program executive summary Washington D.C.: United States Department of Education. Garet, M. S., Porter, A. C., Desimone, L., Birman, B. F., Yoon, K. S. (2001). What makes professional development effective? Results f rom a national sample of teachers. American Educational Research Journal, 38 915-945. Glickman, C. D., Gordon, S. P., & Ross-Gordon, J. M (2001). Supervision and instructional leadership a developmental approach (5th edition). Needham Heights, MA: Allyn & Bacon.

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198 Appendices

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199 Appendix A: Comparison of 2005 NASP Membership to 2004-2005 NASP National Database Respondents ___________________________________________________ _____________________ VARIABLES 2005 NASP Membership 2004-0 5 Database ___________________________________________________ _____________________ GENDER Female 73.5% 74% Male 26.5% 26% Percent Responding 63.7% 99.9% ___________________________________________________ _____________________ ETHNICITY White/Caucasian 88.5% 92.6% American Indian/Alaska Native 0.9% 0.8% Asian American/Pacific Islander 1.4% 0.9% African American 3.1% 1.9% Hispanic 3.8% 3.0% Other 2.4% 0.8% Percent Responding 73.8% 97.5% ___________________________________________________ _____________________ HIGHEST DEGREE Bachelors 1.2% 0.1% Master’s 44.8% 32.6% Specialist 22.9% 34.9% Doctorate 28.0% 32.4% Percent Responding 80.4% 99.8% ___________________________________________________ _____________________ MEAN AGE IN YEARS 50.9 46.2 Percent Responding 80.4% 99.8% ___________________________________________________ _____________________

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200 Appendix B: 2004-2005 National Association of Scho ol Psychologists Demographic Characteristics, Emplo yment Conditions, and Professional Practices Survey 1. Gender ____ female ____ male 2. Age ____ 3. Ethnicity (optional) ___ American Indian/Alaska Native___ Asian American /Pacific Islander ___ Black/African American ___ Caucasian ___ His panic ___ Other 4. What language(s) do you speak fluently other than E nglish? _______________ If you speak another language, do you provide psych ological services to students/families in that lang uage? ____yes ____no 5. Disability ___no ___ yes, specify: ______________ 6. Years of experience in school psychology __________ _____ 7. Years of classroom teaching experience (Pre-K-High School) __________ 8. Primary position (e.g., school psychologist, univer sity faculty, administrator, state department) ____ ___________ 9. Annual salary (primary position) __________ 10. State in which employed ______________ 11. Highest degree earned (e.g., bachelors, masters, sp ecialist, doctorate) _______________ 12. Total graduate-level training completed related to school psychology PRIOR TO ENTRY TO PROFESSIONAL PRACTICE (report total number of semester hours; 1 semester hour=1.5 quarter hour) _________

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201 Appendix B: (Continued) 13. Certification/Licensure (Mark all that apply): ___ Nationally Certified School Psychologist ___ Certified by State Education Agency as School P sychologist ___ Certified by State Education Agency as Psych ometrist, or similar title (specify: _______________ ) ___ Licensed School Psychologist (doctorate req’d ; State Board of Psychology) ___ Licensed Psychologist (doctorate req’d; State Board of Psychology) ___ Licensed School Psychologist (non-doctoral; S tate Board of Psychology) ___ Licensed Psychological Associate or similar t itle (non-doctoral; State Board of Psychology; specify:_______________ ) 14. If certified, does certificate allow for independen t practice in non-school setting? ___ yes ___ no 15. If licensed, does license allow for independent pra ctice in non-school setting? ___ yes ___ no 16. Membership (please check all that apply): ___ State School Psychology Association ___ National Education Association ___ American Federation of Teachers ___ Division of School Psychology (16), American Ps ychological Association ___ Local Teachers’ Union ___ American Psychological Association ___ American Counseling Association ___ Council for Exceptional Children ___ Other, specify: _______________ 17. For your PRIMARY employment, please estimate the average number of hours per week of employment in each of the following settings. _____ Public Schools _____ Private Schools ____ Fai th-Based Schools _____ College/University _____ Independent Practice _____ State Department _____ Hospital/Medical Setting ____ Other, specify : ____________________

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202 Appendix B: (Continued) 18. For any SECONDARY employment, please estimate the average number of hours per week of employment in each of the following settings. _____ Public Schools _____ Private Schools ____Fait h-Based Schools _____ College/University _____ Independent Practice _____ State Department _____ Hospital/Medical Setting ____ Other, specify : ____________________ 19. Type of setting (i.e., urban, suburban, rural) ____ ___________ 20. Please estimate average number of hours per week in each setting: ______ Preschool ______ Elementary School ______ Middle/Jr. High School ______ High School ______ Other, specify: _______________ 21. % of students in district who are ethnic minority ______ 22. % of students you serve who are ethnic minority ___ ____ 23. Ratio of School Psychologists to Students for DISTR ICT 1: _____ How many students are YOU responsible for serving? __________ 24. What data did you use to answer items 27 – 35 ____ estimated ____ personal log ____central data base (e.g., dept) ____ other (please specify)________________________ _________ 25. Number of SECTION 504 PLANS that you assisted in developing _______ 26. Number of Psychoeducational Evaluations completed r elating to INITIAL DETERMINATION of special education eligibility ______ 27. Number of REEVALUATIONS ______

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203 Appendix B: (Continued) 28. Number of CONSULTATION CASES (e.g., consultation for interventions, prereferral interventions, but NOT part of a multifactored evaluation _________ 29. Number of students COUNSELED INDIVIDUALLY (not sessions) ________ 30. Number of student GROUPS conducted (not sessions) _______ 31. Total number of STUDENTS served in groups (not sessions) _______ 32. Number of INSERVICE PROGRAMS conducted _________ 33. % of TOTAL WORK TIME in activities relating to special education ______ __ 34. % of TIME RELATING TO SPECIAL EDUCATION for each of following ____ conducting assessments ____ writing reports ____ attending team meetings ____ other (e.g., Medicaid documentation); specify: _______________ 35. Check the top 3 foci of your continuing professiona l development activities: ____ standardized psycho-educational assessment ____ academic screening/progress monitoring (e.g., CBM, DIBELS) ____ academic interventions ____ behavioral assessment ____ behavioral interventions ____ social/emotional assessment ____ social/emotional interventions ____ consultation/problem-solving ____ response to intervention ____ crisis intervention ____ other (specify)_______________________________ ______

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204 Appendix B: (Continued) 36. Did you receive administrative (e.g., unit head, ad ministrator) supervision during the past year? __ y es ___ no; If yes, job title of that person _______________ Average number of supervision hours/month ___ ___ If yes, please indicate all of the following that d escribe that person: _____ degree in school psychology_____ degree in ps ychology ____degree in admin ___ degree in other area; ___ doctoral degree ___masters/specialist degree 37. Did you receive clinical supervision during th e past year? __yes ___no If yes, please indicate all of the following that describe your supervisor: ___degree in school psychology ___degree in psycho logy ___degree in other area; ___doctoral degree ___masters/specialist degree ___ number of school psychologists your supervisor supervised 38. Number of days in your 2004-2005 Contract Period __ __

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205 Appendix C: National Survey Cover Letter June 17, 2005 Dear NASP Member, On behalf of NASP, I am asking for your assistance. Each year, representatives of NASP and state school psychology associations work with legislators and policy-makers, as well as with representatives of other professional assoc iations at both the state and national levels. Repeatedly, we find ourselves needing impor tant information regarding many different aspects of school psychology. It has become clear that our efforts to improve ser vices for children and to advance school psychology depend on the availability of dat a for our field. To gather such data, NASP now conducts a national study of demographic c haracteristics and professional practices every five years. In the three previous s tudies, the willingness of school psychologists like you to participate has resulted in exceptionally strong response rates of as high as 79%. The availability of those data has been invaluable to NASP, state associations, school districts and individual schoo l psychologists. We currently are conducting the next national study and are collecti ng information about the just completed 2004-2005 school year. We would be most appreciative if you would take a f ew minutes to complete the enclosed questionnaire and return it in the enclose d envelope within three weeks of receipt The survey will take only 12-15 minutes to compl ete. Because it is extremely important that the information NASP uses accurately reflects the field of school psychology, a high return rate is essential. As an incentive for participation, ten NASP members who return completed questionnaires will be randomly selected to each re ceive “50 NASP Bucks” that can be used toward the purchase of publications availab le from NASP. In order for us to make these awards, a code number has been included on the return envelope. We want to assure you that data will be reported only in aggre gate form and that the responses of individuals will be treated in the strictest confid ence. When a questionnaire is returned, it is immediately separated from the envelope, so that the individual respondent cannot be identified. Thank you in advance for your time and assistance w ith this NASP project. Sincerely, Michael J. Curtis Research Committee

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206 Appendix D: Minimum and Maximum Values for Selecte d Variables 1. Gender ____ female ____ male 2. Age 22-76 ___ 3. Ethnicity (optional) ___ American Indian/Alaska Native___ Asian Am erican/Pacific Islander ___ Black/African American ___ Caucasian __ Hispanic ___ Other 4. What language(s) do you speak fluently other than E nglish? _______________ If you speak another language, do you provid e psychological services to students/families in th at language? ____yes ____no 5. Disability ___no ___ yes, specify: ______________ 6. Years of experience in school psychology ____ 0-42 ___________ 7. Years of classroom teaching experience (Pre-K-High School) __ 0-30 ________ 8. Primary position (e.g., school psychologist, univer sity faculty, administrator, state department) ____ ___________ 9. Annual salary (primary position) ___ 0-200,000 ____ 10. State in which employed ______________ 11. Highest degree earned (e.g., bachelors, masters, sp ecialist, doctorate) _______________ 12. Total graduate-level training completed related to school psychology PRIOR TO ENTRY TO PROFESSIONAL PRACTICE (report total number of semester hours; 1 semester hour=1.5 quarter hour) ____ 0-160 ___

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207 Appendix D: (Continued) 13. Certification/Licensure (Mark all that apply): ___ Nationally Certified School Psychologist ___ Certified by State Education Agency as School Psychologist ___ Certified by State Education Agency as Ps ychometrist, or similar title (specify: _______________) ___ Licensed School Psychologist (doctorate r eq’d; State Board of Psychology) ___ Licensed Psychologist (doctorate re q’d; State Board of Psychology) ___ Licensed School Psychologist (non-doctora l; State Board of Psychology) ___ Licensed Psychological Associate or simil ar title (non-doctoral; State Board of Psychology; specify:_________ ______ 14. If certified, does certificate allow for independen t practice in non-school setting? ___ yes ___ no 15. If licensed, does license allow for independent pra ctice in non-school setting? ___ yes ___ no 16. Membership (please check all that apply): ___ State School Psychology Association ___ National Education Association ___ American Federation of Teachers ___ Division of School Psychology (16), American Psychological Association ___ Local Teachers’ Union ___ American Psychological Association ___ American Counseling Association ___ Council for Exceptional Children ___ Other, specify: _______________ 17. For your PRIMARY employment, please estimate the average number of hours per week of employment in each of the following settings. Make each one 0 60 _____ Public Schools _____ Private Schools __ __ Faith-Based Schools _____ College/University _____ Independent Pr actice_____ State Department _____ Hospital/Medical Setting ____ Other, s pecify: ____________________

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208 Appendix D: (Continued) 18. For any SECONDARY employment, please estimate the average number of hours per week of employment in each of the following settings. Each one, 0 30 _____ Public Schools _____ Private Schools __ __Faith-Based Schools _____ College/University _____ Independent Pr actice_____ State Department _____ Hospital/Medical Setting ____ Other, s pecify: ____________________ 19. Type of setting (i.e., urban, suburban, rural) ____ ___________ 20. Please estimate average number of hours per week in each setting: ______ Preschool Make each one, 0 60 ______ Elementary School ______ Middle/Jr. High School ______ High School ______ Other, specify: _______________ 21. % of students in district who are ethnic minority 0 100 ___ 22. % of students you serve who are ethnic minority ___ 0 100 __ 23. Ratio of School Psychologists to Students for DISTR ICT 1: 0 8000 How many students are YOU responsible for ser ving? __ 0 8000 ____ 24. What data did you use to answer items 27 – 35 ____ estimated ____ personal log ____centra l database (e.g., dept) ____ other (please specify)__________________ _______________ 25. Number of SECTION 504 PLANS that you assisted in developing 0 100 26. Number of Psychoeducational Evaluations completed r elating to INITIAL DETERMINATION of special education eligibility __ 0 200 __ 27. Number of REEVALUATIONS __ 0 200 __

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209 Appendix D: (Continued) 28. Number of CONSULTATION CASES (e.g., consultation for interventions, prereferral interventions, but NOT part of a multifactored evaluation 0 400 29. Number of students COUNSELED INDIVIDUALLY (not sessions) __ 0 200 30. Number of student GROUPS conducted (not sessions) 0 40 __ 31. Total number of STUDENTS served in groups (not sessions) __ 0 200 __ 32. Number of INSERVICE PROGRAMS conducted __ 0 50 ____ 33. % of TOTAL WORK TIME in activities relating to special education 0 100 __ 34. % of TIME RELATING TO SPECIAL EDUCATION for each of following Make each of the following 0 100 ____ conducting assessments ____ writing repo rts ____ attending team meetings ____ other (e.g., Medicaid documentation); sp ecify: _______________ 35. Check the top 3 foci of your continuing professiona l development activities: ____ standardized psycho-educational assessme nt ____ academic screening/progress monitoring ( e.g., CBM, DIBELS) ____ academic interventions ____ behavioral assessment ____ behavioral interventions ____ social/emotional assessment ____ social/emotional interventions ____ consultation/problem-solving ____ response to intervention ____ crisis intervention ____ other (specify)_________________________ ____________

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210 Appendix D: (Continued) 36. Did you receive administrative (e.g., unit head, ad ministrator) supervision during the past year? __ y es ___ no; If yes, job title of that person ____________ ___ Average number of supervision hours/month 0 40 If yes, please indicate all of the following t hat describe that person: _____ degree in school psychology_____ degree in psychology ____degree in admin ___ degree in other area; ___ doctoral degree ___masters/specialist degree 37. Did you receive clinical supervision during the pas t year? __yes ___no If yes, please indicate all of the following that describe your supervisor: ___degree in school psychology ___degree in ps ychology ___degree in other area; ___doctoral degre e ___masters/specialist degree 0 70 number of school psychologists your supervisor su pervised 38. Number of days in your 2004-2005 Contract Period 80 260

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211 Appendix E: United States Geographic Regions Mountain: AZ, CO, ID, MT, NM, NV, UT, WY Pacific: AK, CA, HI, OR, WA Northeast: CT, MA, ME, NH, RI, VT Mid-Atlantic: NJ, NY, PA South Atlantic: DC, DE, FL, GA, MD, NC, SC, VA, WV East South Central: AL, KY, MS, TN East North Central: IL, IN, MI, OH, WI West South Central: AR, LA, OK, TX West North Central: IA, KS, MN, MO, ND, NE, SD