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1 of 18 Education Policy Analysis Archives Volume 9 Number 25July 22, 2001ISSN 1068-2341 A peer-reviewed scholarly journal Editor: Gene V Glass, College of Education Arizona State University Copyright 2001, the EDUCATION POLICY ANALYSIS ARCHIVES. Permission is hereby granted to copy any article if EPAA is credited and copies are not sold. Articles appearing in EPAA are abstracted in the Current Index to Journals in Education by the ERIC Clearinghouse on Assessment and Evaluation and are permanently archived in Resources in Education .Occupational Trends and Program Priorities Dan Rosenthal Auburn University Kitty C. Collier Alabama Commission on Higher EducationAbstractInstitutions of higher education that respond to th e economic base in their region will remain competitive and be better positioned to obtain public funds and donor support. In addition to mand ated program viability standards based on measures such as gradu ation rate, individual institutions and state coordinating boards can use ten-year occupational trend data to assess future program viability. We u sed an occupational demand model to determine whether academic programs can meet projected statewide needs for high demand and high growth occupations. For example, computer engineering, the highest grow th rate occupation in Alabama, is projected to have 365 annual average job openings, with 93.6% total growth over ten years. But only 46 comp uter engineering majors graduate annually from all Alabama instituti ons of higher education. We recommend using an occupational deman d model as a
2 of 18planning tool, decision-making tool, and catalyst f or collaborative initiatives.Introduction Institutions of higher education operate in a highl y competitive environment. The push for increased state funds, new programs, more students, and expanded services led to increased emphasis on statewide coordination dur ing the 1950s and 1960s as states sought to bring rationality to their rapidly growin g higher education systems. However, competition took on new meaning during the 1980s an d 1990s when state revenue for higher education began to dwindle or disappear as o ther state functions moved into priority funding positions. In addition, state legi slatures and the public at large began to raise questions about accountability, performance, and productivity of the higher education systems (McGuinness, 1997). At the same t ime, business and industry began calling for more effective responses to employment needs. By the late 1990s, it was clear that the market fo r higher education had changed. While the values and traditions of the academy rema ined "venerable sources of strength," institutions and their governing boards began to look to the external environment to understand the context in which thos e values and traditions must operate (Mingle, 1998). That environment included a changin g labor market that demanded new skills for workers, the emergence of technologies s uch as the Internet, the challenge to market share of traditional colleges and universiti es by new providers of postsecondary education, and the intensely competitive and changi ng public policy context, which exacerbated cost, price, and productivity pressures on institutions of higher education (Mingle, 1998). To strike a balance between the demands of the mar ket, the academy, and the public, some state-level higher education agencies have taken steps to link occupational trends to academic program priorities based on (a) the connection between higher education and the economy; (b) the current focus on meeting student and employer demands for job and skills training; (c) the need f or public institutions of higher education to respond to state policy directives and demonstrate wise stewardship of public resources; and (d) the benefits of academic program planning and review in a statewide context. Connection Between Higher Education and the Economy In response to a growing demand for agricultural an d technical education, Congress passed the Morrill Act of 1862 to provide funds to establish land-grant colleges so that members of the working class could obtain a liberal, practical education. Every state and territory now has one or more landgrant colleges (National Association of State Universities and Land-Grant Colleges, 2000 ). The Carnegie Foundation for the Advancement of Tea ching (1976) suggested the two best restraints on higher education are competi tion and state budgets. An institution that responds to the economic base in its region wi ll remain competitive and be better positioned to obtain financial support from donors and legislators. According to Seymour (1988), one of the key charac teristics of strategic planning is "matching institutional capabilities with enviro nmental conditions to achieve goals," and listed three considerations for determining pro gram priority: mission, internal
3 of 18factors, and external factors. Toombs and Tierney ( 1991) recognized environmental factors, and specifically "market forces," in their components of curriculum design. Hines (1988) points out in a review of the relation ship between higher education and state governments that: Increased investment of public funds in higher educ ation toward the goal of increased economic development is predicated on the assumption that there will be a payoff, that economic activity will incre ase, that the tax base will expand, and that revenue will increase. (p. 33) Although it may be appealing to define mission, ro le, and program priorities in isolation, successful universities understand that this process cannot occur without consideration of their constituencies (Western Inte rstate Commission for Higher Education, 1992a). In fact, many higher education p lans include the education of personnel needed for "an advanced economy" (Western Interstate Commission for Higher Education, 1992b). For example, colleges and universities have added academic programs in areas such as computer engineering and management information systems when those knowledge areas became crucial for indus trial development. Current Focus on Meeting Student and Employer Deman ds for Job and Skills Training Mingle (1998) noted that higher education is moving from a producer-dominated enterprise to one fully sensitive to and focused on the consumer. Public expectations of higher education appear to have no bounds, putting considerable pressure on colleges and universities: The American labor market is both extraordinarily d iverse and exceptionally dynamic, making it difficult not only to generalize about the knowledge and "skill sets" college graduates need b ut also to make predictions about the future demand for specific oc cupations. Through surveys and interviews of employers and external ad visory groups, increasing numbers of colleges stay closely tuned t o this changing job market. This information is shaping college program s in important ways. (p. 6) The Joint Commission on Accountability Reporting ( 1996) emphasized the need to stay focused on the consumer and recommends that institutions survey graduates and report placement rates (pp. 3850). While placemen t is an important measure of accountability, it is more closely related to curre nt employment than to future employability. Nor can placement identify employmen t possibilities for which no programs are in place. State-level coordinating age ncies currently explore ways to conduct market analyses to determine how best to ad dress the needs of their state. A review of the Alabama Commission on Higher Educatio n (1999) recommended that the agency devote more effort and resources to statewid e market analyses, and the State Higher Education Executive Officers Association off ers "State and System Tools for Success in the New Market Environment" as an on-lin e seminar for state higher education agency staff. With respect to employer needs, there is a well-do cumented national disequilibrium between the supply and demand for in formation technology workers.
4 of 18Evidence for a severe worker shortage includes a hi gh job vacancy rate, low unemployment, projected demand outstripping supply, higher than average salary increases, and demand for foreign workers (Freeman & Aspray, 1999). The national failure to develop sufficient technical talent is s o severe that it could "substantially undermine" the future growth of the electronics and information technology industry (Platzer, Novak, & Kazmierczak, 1999, p 13).Need for Public Institutions of Higher Education to Respond to State Policy Directives and Demonstrate Wise Stewardship of Publ ic Resources In recent years, many states have required academi c program review and approval as a way to curb unnecessary duplication of program s among public institutions and to judge the appropriateness of existing programs (McG uinness, 1997). Most criteria for program review require employer needs analyses that indicate whether new or existing programs respond to employment needs. In some cases the link between employment opportunities and program graduates is a critical f actor. For example, Alabama passed "program viability" legislation in 1996 that requir es academic programs in all public institutions to meet minimum graduation rates or be terminated (Program Viability Act, 1996). After a three-year monitoring period of nonviable programs, institutions can request waivers for programs that still do not meet graduation rate standards provided they can document unique or extraordinary character istics of the program. Factors that may be considered in this evaluation are placement of graduates in program-related areas of employment, success of program graduates, and ma rket demands. Alabama institutions are evaluating how best to assess the link between graduates in low-producing programs and the state's employment n eeds. Benefits of Academic Program Planning and Review in a Statewide Context One economy driven process is the relationship betw een occupational trends and institutional programs. While individual institutio ns and groups of institutions can analyze occupational trends within their state, the institutional approach does not take into account what other in-state and out-of-state i nstitutions are doing to meet the need. With limited resources available to higher educatio n, institutional representatives, legislators, and policy makers must be committed to the most effective use of state dollars for the citizenry. A statewide approach to academic program planning and review requires institutions to think "outside the box," b ecause what appears to be best for an individual institution may not be the best course o f action for the region. While an institution may identify a high-demand occupation b ased on labor market projections and employer feedback, it must consider the product ivity of existing and planned programs in the region to avoid potential duplicati on and market oversupply. The public trust requires that state dollars be spent on progr ams that have high priority and provide substantial benefit.Previous Use of Occupational Trends at the State Le vel Although state-level agencies have been interested in links between occupational projections and academic programs for some time, th e challenge has been to assess these relationships as a context for institutional progra m review. Some states have developed comprehensive proactive approaches to program needs assessment, while others simply
5 of 18react to institutional plans. Arizona In 1998, the Arizona legislature challenged the B oard of Regents and the State Board of Directors for Community Colleges to develop a mutual statewide process for identifying and meeting needs for advanced post secondary education. In response, the two boards jointly convened the 1998 Higher Edu cation Study Committee. The process utilizes a Joint Review Committee to evalua te requests for new or expanded programs on the basis of statewide criteria for nee d. Although needs assessment remained an institutional function, the case for a new program could be strengthened if multiple institutions partnership to meet the need. They recommend several sources of data to demonstrate program need, including the Ari zona Department of Commerce, the Arizona Department of Economic Security, and the Bu reau of Labor Statistics (Arizona Board of Regents and the State Board of Directors o f Community Colleges for Arizona, 1998). Florida Sanchez, Laanan, and Wiseley (1999) provide an ex cellent summary of state efforts to measure students' post-college ear nings. Most initiatives follow program completers or graduates into the workplace to estim ate average annual earnings or placement. Florida pioneered in this area with the Florida Education and Training Placement Information Program, established by a leg islative directive and a joint agreement between the Florida State Department of E ducation and the Florida Department of Labor and Employment. Other states su ch as Ohio, California, North Carolina, Texas, and Washington have pursued simila r approaches. However, these efforts provide little information on whether gradu ates are being trained in the fields most needed by employers. Idaho has taken a somewha t broader approach to needs assessment through statewide roundtable discussions and the use of specific advisory committees (Dodson, 1999). Illinois The Illinois Board of Higher Education is a membe r of a consortium with other state agencies committed to sharing labor mar ket information. The board has conducted statewide analyses by field of study, com paring employment projections with graduate survey data. Typically, the board will con duct a statewide study of existing programs in a field, followed by institutional stud ies of related programs a few years later. The initial analysis gives institutions a us eful context for their own assessments. One recent board study included social work and hum an services (Illinois Board of Higher Education, 1997). A similar review of health professions education i n Illinois in 1992 compared projected average annual job openings with estimate d total supply and number of degrees conferred in the state, and made recommenda tions for capacity adjustment in individual programs. The analysis was followed by r ecommendations for health professions education in 1993 and the implementatio n of policies for health professions education in 1995. The purpose of the study was to adjust educational capacity, and the board recommended that some programs be reduced and monitored, some be maintained, and some be expanded (Illinois Board of Higher Education, 1995). In 1998, the board published a report that identif ied and proposed solutions to meet the educational needs in Lake County (north of Chicago). The study included market research conducted by a private consulting f irm. The board staff convened a number of forums to provide an opportunity for Lake County residents to express their educational needs, and conducted further research t o analyze demographic and economic data relevant to educational demand and need. They used the number and percent of positions in Lake County that required postsecondar y education as compiled by the Illinois Occupational Information Coordinating Comm ittee to assess educational demand (Illinois Board of Higher Education, 1998). Based on the results, the board
6 of 18established a University Center in Lake County that offered high quality, convenient, and affordable education built on the resources and programs of existing institutions. Ohio Gottlieb (1995) used an industry-occupation matri x combined with occupational projections to identify industries lik ely to provide future entry level and advanced training jobs as a way to re-prioritize jo b training programs in two-year institutions in the Cleveland-Akron area of Ohio. Wisconsin The University of Wisconsin System supports a mar ket research unit that works with universities to identify needed pro grams in their region by looking at demand from employers and students. Faculty still i dentify areas of interest for new programs, but the market research unit then samples regional businesses using the Dunn and Bradstreet list (Sell, 1999).Statement of the Problem The state of Alabama needs a systematic statewide p rocess for comparing occupational projections with the number of graduat es of academic programs for use in program planning. Although individual institutions have made such comparisons as needed to foster strategic planning for program pri oritization, resource allocation, curriculum development, and course availability, th e need to analyze occupational and graduation data at the state level has been heighte ned by several recent developments. They include more limited resources to support high er education, passage of a program viability bill with provisions for waiver of nonv iability based on factors related to meeting occupational needs, and recommendations by the Evaluation Committee of the Alabama Commission on Higher Education to increase the agency's use of market research as a planning tool.The purpose of this study is to compare occupationa l projections for the state of Alabama with graduation rates in corresponding acad emic programs to provide a context for state and institutional policy decisions on cur rent programs and new program initiatives, and to comply with recent program viab ility legislation.Methods We employed three major tools to establish a contex t for state and institutional policy decisions: (a) statewide employment projecti ons, (b) number of degrees conferred, and (c) a crosswalk to relate one with t he other. We limited the analysis to high-demand and fast-growing occupations in Alabama that require a Bachelor's degree or higher, as identified by the Alabama Department of Industrial Relations. They define high-demand occupations as having at least 535 average annual job openings Fast-growing occupations have at least 50 average annual job openings and a n average annual growth rate of at least 3.2% (Alabama Depart ment of Industrial Relations, 1998). Employment Projections The Bureau of Labor Statistics has prepared nation al employment projections since 1957 (U. S. Department of Labor, 1995). Minim al input data was available at first, but by the early 1970s a standard methodology was d eveloped that is still in use today (U. S. Department of Labor, 1986; 1997). The bureau releases ten-year national employment projections every other year. It uses ma ny factors to make projections, including the composition of the labor force, econo mic growth, demand, and
7 of 18 occupational trends. For example, occupational tren ds are based on data collected from an Occupational Employment Survey prepared and summ arized by the bureau. The survey is administered by each state, and contains data on approximately 775 occupations in 350 industries. The data includes nu mber of employees and salary range by occupation, providing regular empirical informat ion on occupational employment. Information is stored in a projections database th at is programmed to generate employment trends over a ten-year period. The burea u makes several key assumptions during the projection process. For example, work pa tterns will not change during the projection period (length of average work week), br oad social and educational trends will continue, there will be no major war, there wi ll not be a significant change in the size of the armed forces, and there will be fluctua tions in economic activity due to the business cycle. The most recent national projection s localized for the state level are for the ten-year period 1996 2006 (Silvestri, 1997). (See, also, U. S. Department of Labor, 1998.) The bureau monitors and validates projections, and exceptions to general assumptions are reported. For example, they found t hat both the manufacturing and health industries suffered unexpected setbacks in 1 998 that were attributed to the Asian economic crisis and more stringent health care reim bursement policies (Goodman & Consedine, 1999). The bureau conducted a detailed analysis of the ed ucational requirements of occupations and published the minimum amount of pre paration that most employers required. However, requirements can vary from emplo yer to employer, and there may be more than one way to qualify. For example, the educ ational preparation listed for registered nurses is associate degree, although bac calaureate graduates take the same licensure exam and are hired for the same entry-lev el positions. For that reason, bureau educational requirements for each occupation must b e evaluated for accuracy in a given state (U. S. Department of Labor, 1995; 1996). The demand for college graduates continues to incr ease as duties become more complex due to new technology and changing business practices. This phenomenon, called educational upgrading accounted for one-third of the college-level jobs created between 1983 and 1994 (Shelley, 1996). Changes in e mployment growth can be due to the growth of an industry as well as changes in occ upational structure. For example, employment in the health-related professions is exp ected to increase along with growth in the health services industry. More use of comput er technology, a structural change, will accelerate the need for systems analysts and p rogrammers, and reduce the need for typists (Franklin, 1997). Nationally, the ten fastest growing occupations that require a bachelor's degree are: (a) database administrators, computer support specialists and all other computer scientists, (b) computer engineers, (c) systems ana lysts, (d) physical therapists, (e) occupational therapists, (f) special education teac hers, (g) speechlanguage pathologists and audiologists, (h) physician assistants, (i) res idential counselors, and (j) securities and financial services sales workers (see Table 1); (U. S. Department of Labor, 1998, p. 52).Table 1 Fast-Growing Occupations in Nation Requiring a Bachelor's Degree, 1996-2006Occupation Ten-Year% Growth
8 of 18 Database Administrators118Computer Engineers109Systems Analysts103Physical Therapists71Occupational Therapists66Special Education Teachers59Speech-Language Pathologistsand Audiologists 51 Physician Assistants47Residential Counselors41Financial Services and Sales38 The bureau provides each state with a data set for making local projections. Using special software, states prepare projections that a re parallel to the national but based on local populations, industries, and employees. We us ed the Alabama Occupational Trends data for April 1998, which are localized fro m federal projections, to estimate statewide employment demand in various occupations (Alabama Department of Industrial Relations, 1998). We defined employment or occupational demand as the projected annual average number of job openings in Alabama for the period 1996 -2006. Specifically, we evaluated the projected employment need for all high-demand and fast-growing occupations that require a bachelor's degree or higher (we excluded first professional preparation). In Alabama these occupat ions are: (a) secondary school teachers, (b) general managers and top executives, (c) registered nurses, (d) elementary school teachers, (d) systems analysts, (e) special education teachers, (f) accountants and auditors, (g) computer engineers, (h) engineering, math and natural science managers, (i) residential counselors, (j) preschool and kindergar ten teachers (combined group), (k) physical therapists, (l) operations research analys ts, (m) speechlanguage pathologists and audiologists, and (n) occupational therapists.Number of degrees conferred Public and private institutions of higher educatio n in Alabama prepare a mandatory completions survey as one of the federal reports used in the Integrated Postsecondary Education Data System of the National Center for Education Statistics (U. S. Department of Education, 1994 98). The com pletions survey is a comprehensive report of graduates organized by award level and cu rriculum. The curriculum area is designated by a program description and six-digit c ode based on the national Classification of Instructional Programs taxonomy. (For more information on academic program definitions, see Morgan, Hunt, & Carpenter, 1991). Institutions forward an annual completions report to the Alabama Commission on Higher Education, the statutory state coordinating agency, which maintain s a longitudinal statewide repository of these reports (Alabama Commission on Higher Educ ation, 1994 98). Using this curricula completion information we wer e able to determine the number of degrees conferred in a given program in a given year in Alabama. For
9 of 18example, the number of completions in registered nu rse preparation programs is the sum of the number of nursing degree completions reporte d under program code 51.1601 at each institution in a given year. We can use this m ethod to determine the total number of degree completions reported for any academic discip line in the state. In this study, we define degrees conferred as the average annual number of completions report ed by postsecondary institutions in Alabama based on the five-year period 1993-94 through 1997-98 (July 1 June 30 reporting period). Averag es include public and private institutions and are based on Integrated Postsecond ary Education Data System reports. Crosswalk Some occupations listed in the state employment pr ojections have an obvious relationship to an instructional program reported i n the completions survey. When questions arose, we consulted a crosswalk database to help identify the relationship. The database relates occupations to academic programs b y linking an occupational employment survey code to an instructional program code (National Crosswalk Data Center, April, 1999). For example, based on statewide repository data an d prior knowledge, we identified 24 Alabama colleges and universities tha t report baccalaureate and master's degree completions in programs that lead to employm ent in the occupational category systems analyst Colleges confer degrees in the following related instructional programs (and program codes): (a) computer and information s ciences, general (11.0101), (b) information sciences and systems (11.0401), (c) com puter science (11.0701), (d) computer and information sciences, other (11.9999), and (e) management information systems and business data processing, general (52.1 201). Note that all of these programs are offered at the bachelor's level, and programs ( a) and (e) are offered at the master's level as well. A crosswalk database query for systems analyst degree program codes pointed to the following occupations (and occupational codes): (a) systems analysts, electronic data processing (25102), (b) data base administrators (2 5103), (c) computer support specialists (25104), (d) computer programmers (2510 5), (e) computer programmer aides (25108), (f) all other computer scientists (25199), and (g) computer science teachers, postsecondary (31226). The crosswalk query shows that graduates who earn a systems analyst or related degree in college are reported on the Occupational Employment Survey as working as systems analysts, as well as in a cluster of relate d jobs. Thus, we can link the number of systems analyst and related degrees conferred to th e number of projected job openings for systems analysts and related occupations, altho ugh some graduates will enter other fields. Note that to be conservative in our estimat e of needed graduates, we limited the number of projected job openings to systems analyst eliminating all of the related fields. The articulation between academic program and occup ation will be more precise for some occupations than others. Occasionally, crosswa lk relationships were adjusted to better reflect specific conditions in Alabama.Findings The application of this model to 15 high-demand and fast-growing occupations requiring a minimum of a bachelor's degree yielded the general conclusion that existing programs in Alabama colleges and universities will supply a sufficient number of
10 of 18graduates to meet the state's demand for many of th ese occupations through the year 2006. For reporting purposes, we grouped the result s of 15 occupational demand analyses into three categories: (a) occupations whe re the supply of graduates is projected to meet or exceed demand, (b) occupations where the supply of graduates is projected to be insufficient to meet demand, and (c) occupations requiring further study. Occupations Where the Supply of Graduates is Projec ted to Meet or Exceed Demand The supply of graduates is projected to meet or exc eed the demand for (a) general managers and top executives, (b) registered nurses, (c) elementary school teachers, (d) accountants and auditors, (e) engineering, math and natural science managers, (f) residential counselors, (g) preschool and kindergar ten teachers, (h) physical therapists, (i) speech-language pathologists and audiologists, and (j) occupational therapists. Figure 1. High-demand and fast growing occupations where the supply college graduates is projected to meet or exceed statewide need. Occupations Where the Supply of Graduates is Projec ted to be Insufficient to Meet Demand The supply of graduates is projected to be insuffi cient to meet the demand for (a) systems analysts, (b) special education teachers, ( c) operations research analysts, and (d) computer engineers.
11 of 18 Figure 2. High-demand and fast growing occupations where the supply college graduates is projected to be insufficient to meet s tatewide need. Occupations that Require Further Study The supply of graduates and demand for secondary s chool teachers requires further analysis with respect to need in specific c ertification areas.
12 of 18Figure 3. High-demand and fast growing occupations that require further study.Discussion We recommend three primary uses for an occupational demand model: (a) as a planning tool, (b) as a decision making tool, and ( c) as a catalyst for collaborative initiatives. Planning Tool A model of occupational demand provides a valuable contextual base for statewide discussions of employment needs, and ways that higher education can address those needs. Although a demand model cannot provide absolute judgments on the need for particular programs, it can provide a starting point for asking the right questions. For example, we found that Integrated Postsecondary Edu cation Data Systems completions in secondary education are not the best source for the available supply of teachers. Institutions can award teaching certificates withou t offering academic programs, and teachers may be certified through alternative route s. Therefore, degree completions surveys may underestimate the total number of certi fications awarded. The Oklahoma State Regents commissioned the Southern Regional Ed ucation Board (1998) to conduct a study of educator supply and demand by type of ce rtification. In Alabama, consultation with officials at the State Department of Education suggested that for the most part, Alabama produces more new teachers than local educa tion agencies need, with the exception of areas such as special education, forei gn languages education, and sciences other than biology. Given the difficulty of hiring foreign language teachers and the low productivity in many foreign language programs in t he state, we need to formulate policies that lead to an understanding occupational needs and focus on solutions. State policy formulation should involve all stakeholders in meaningful deliberations (institutional representatives, the state coordinat ing board, the state department of education, business leaders, legislators, etc.).Decision Making Tool Individual institutions and state coordinating boa rds can use data based on an occupational demand model as a tool in making acade mic program decisions. The relationship between number of college graduates an d occupational demand can serve as an important source of information for determining whether institutions of higher education are meeting the employee training needs o f business and industry. If an occupation is identified as high-demand or fast-gro wing, and an institution's faculty express interest in developing an academic program in this field, they should consider the productivity of existing programs, and the pote ntial productivity of newly approved programs. Several years ago the Alabama Commission on Higher Education approved three new master's level programs in physical thera py. When the new programs were included in estimates of future productivity, the s upply and demand for physical therapists in the state was in approximate balance, even though physical therapy is projected to be a fast-growing occupation during th e period 1996-2006. Institutions will be better able to allocate limited resources to app ropriate programs when the regional
13 of 18productivity of existing programs is considered. We view comparisons of occupational projections wi th academic program graduates as a focal point for discussion, rather t han an absolute measure of need to continue existing programs or establish new ones. A complex decision, such as whether or not to close an academic program, requires broad based judgments that include multiple components in the decision process, such a s job placement of current students, emerging market trends, and research support (parti cularly at the graduate level). While research on occupational trends is an important inf ormation source, we view it as part of a larger decision-making framework. Institutions can use the model to identify areas t hat are not currently being addressed by the educational system. For example, i nformation technology (computer engineers, systems analysts) is an area where exist ing programs are not producing adequate numbers of professionals. Institutions may want to implement strategies to increase enrollment in existing programs or plan ne w ones. Another useful process is to identify high-demand and fast-growing programs that are not offered by any institution in the state. Finally, while the selection of an oc cupation is an individual choice, educational organizations can help consumers make i nformed decisions by providing valid information about the prospects for occupatio nal employability. Catalyst for Statewide Cooperative Initiatives It is difficult for competing institutions to fost er cooperative ventures, and collaboration is not the norm among institutions of higher education. However, an occupational demand model can identify program area s that are ripe for cooperative initiatives. Relationships can be encouraged throug h collaborative inter-institutional discussions and financial incentives, and cooperati ve programs can be established that benefit the state as a whole.Other Influences We used an occupational demand model to compare pr ojected employment needs with statewide graduation rates as a metric for pro gram resource allocation. We mentioned other influences on the demand model, suc h as the goodness of fit between occupations and academic degrees, variations in min imum educational job qualifications, migration of graduates to (and from ) other states. In Alabama, there are graduates of out-of-state corporations that are not accountable to the Alabama Commission on Higher Education. These influences ar gue for using an occupational demand model as part of a broader decision-making p rocess.Notes This article is based on a presentation at the 39th Annual Forum of the Association of Institutional Research, Seattle, Was hington, June 2, 1999. We wish to thank Douglas Dyer, Chief, Labor Market Information Division, Alabama Department of Industrial Relations, and his staff, for providing us with state employment projections and related materials, and for meeting with us to d iscuss this project.References
14 of 18Alabama Commission on Higher Education. (1994 98) Academic programs by discipline. Montgomery, AL. Alabama Commission on Higher Education. (1999). The report of the seventh quadrennial evaluation committee. Montgomery, AL. Alabama Department of Industrial Relations. (1998). Alabama occupational trends for 2006. Montgomery, AL: Research and Statistics Division. Arizona Board of Regents and the State Board of Dir ectors for Community Colleges for Arizona. (1998, December). Report of the Arizona higher education study commit tee. Phoenix, AR: Higher Education Study Committee.Carnegie Foundation for the Advancement of Teaching (1976). The states and higher education. San Francisco: Jossey-Bass. Dodson, R. (email@example.com). (1999, Febru ary 10). Personal communication. Franklin, J. C. (1997). Industry output and employm ent projections to 2006. Monthly Labor Review, 120, (11), 58 -83. Washington DC: U. S. Department of L abor. Freeman, P. & Aspray, W. (1999). The supply of technology workers in the United States. Washington DC: Computing Research Association. Goodman, W. C. & Consedine, T. D. (1999). Job growt h slows during crisis overseas. Monthly Labor Review, 122, (2), 3-23. Washington DC: U. S. Department of Labo r. Gottlieb, P. D. (1995). Industries, occupations, and training needs in the Cleveland-Akron labor market: 19952004. Cleveland, OH: Center for Regional Economics Issues.Hines, E. R. (1988). Higher education and state governments: Renewed par tnership, cooperation, or competition? (ASHE/ERIC Higher Education Report No. 5). Washington, DC: Association for the Study of Higher Education. Illinois Board of Higher Education. (1995, January) Health professions education in Illinois. Springfield, IL. Illinois Board of Higher Education. (1997, July). Statewide Analysis for Public University Program Reviews. Springfield, IL. Illinois Board of Higher Education. (1998, Septembe r). Illinois higher education in the 21st century Identifying and responding to the ed ucational needs in Lake County: A committee report. Springfield, IL.Joint Commission on Accountability Reporting. (1996 ). JCAR technical conventions manual. [On-line]. Available: http://www.aascu.org McGuinness, A. C. Jr. (1997). Essay: The function a nd evolutions of state coordination and governance in postsecondary education. In 1997 State postsecondary education structures sourcebook. Denver, CO: Education Commission of the States.
15 of 18Mingle, J. R. (1998). Responding to the new market for higher education [Special Issue]. Priorities, Summer (11). Washington, DC: Association of Governing Boa rds of Universities and Colleges.Morgan, R. L., Hunt, E. S., & Carpenter, J. M. (199 1). Classification of instructional programs (1990 ed.). Washington, DC: National Center for Ed ucation Statistics. National Association of State Universities Land-Gra nt Colleges. (2000). What is a land-grant college? [Online]. Available: http://www.nasulgc.org National Crosswalk Data Center. (April, 1999). National Occupational Information Coordinating Committee crosswalk. [On-line]. Available: http://www.state.ia.us/ncdc Platzer, M. D., Novak, C. A., & Kazmierczak, M. F. (1999). CyberEducation. Washington DC: American Electronics Association.Program Viability Act of 1996, Alabama Code, Sectio n 165-8 [On-line]. Available: http://www.legislature.state.al.us/codeofalabama/19 75/16% 2D5%2D8.htm Sanchez, J. R., Laanan, F. S., & Wiseley, W. C. (19 99). Post-college earnings of former students of California community colleges: Methods, analysis, and implications. Research in Higher Education, 40 (1), 87-113. Sell, K. (firstname.lastname@example.org). (1999, February 15). Unp ublished data. E-mail to Kitty Collier (email@example.com).Seymour, D. T. (1988). Developing academic programs (ASHE/ERIC Higher Education Report No. 3). Washington, DC: Association for the Study of Higher Education. Shelley, K. J. (1996). College can still lead to th e fast track, but the transfer station is likely to be crowded. Occupational Outlook Quarterly, 40 (2), 2-9. Washington DC: U. S. Department of Labor Silvestri, G. T. (1997). Occupational employment to 2006. Monthly Labor Review, 120 (11), 58 -83. Washington DC: U. S. Department of La bor. Southern Regional Education Board. (1998). Oklahoma educator supply and demand study. Oklahoma City: Oklahoma State Regents for Higher E ducation. Toombs, W. & Tierney, W.G. (1991). Meeting the mandate (ASHE/ERIC Higher Education Report No. 6). Washington, DC: Associatio n for the Study of Higher Education.U. S. Department of Education (1994 98). Integrated Postsecondary Education Data System Completions Survey (Form IPEDS-C). Washington, DC: National Center fo r Education Statistics. U. S. Department of Labor. (1986, April). Employment Projections for 1995: Data and Methods (Bulletin 2253). Washington, DC: Bureau of Labor S tatistics U. S. Department of Labor. (1995, December). Employment Outlook: 1994-2005, Job Quality and Other Aspects of Employment Growth (Bulletin 2472).Washington, DC:
16 of 18 Bureau of Labor Statistics.U. S. Department of Labor. (1996). Occupational Projections and Training Data (Bulletin 2471). Washington, DC: Bureau of Labor St atistics. U. S. Department of Labor. (1997). BLS Handbook of Methods. Washington, DC: Bureau of Labor StatisticsU. S. Department of Labor. (1998). Occupational Outlook Quarterly, 42 (2). Washington, DC: Bureau of Labor Statistics.Western Interstate Commission for Higher Education. (1992a) Insights on the higher education-economy relationship (Working Paper No. 4). Boulder, CO: Office of Research and Policy Analysis.Western Interstate Commission for Higher Education. (1992b). Joined or unconnected (Working Paper No. 5). Boulder, CO: Office of Resea rch and Policy Analysis.About the AuthorsDr. Dan RosenthalAssociate Director of Planning and Analysis203 Samford HallAuburn University, Auburn, Alabama firstname.lastname@example.orgDr. Kitty C. CollierDirector of PlanningAlabama Commission on Higher EducationP.O. Box 302000Montgomery, Alabama email@example.comCopyright 2001 by the Education Policy Analysis ArchivesThe World Wide Web address for the Education Policy Analysis Archives is epaa.asu.edu General questions about appropriateness of topics o r particular articles may be addressed to the Editor, Gene V Glass, firstname.lastname@example.org or reach him at College of Education, Arizona State University, Tempe, AZ 8 5287-0211. (602-965-9644). The Commentary Editor is Casey D. C obb: email@example.com .EPAA Editorial Board Michael W. Apple University of Wisconsin Greg Camilli Rutgers University
17 of 18 John Covaleskie Northern Michigan University Alan Davis University of Colorado, Denver Sherman Dorn University of South Florida Mark E. Fetler California Commission on Teacher Credentialing Richard Garlikov firstname.lastname@example.org Thomas F. Green Syracuse University Alison I. Griffith York University Arlen Gullickson Western Michigan University Ernest R. House University of Colorado Aimee Howley Ohio University Craig B. Howley Appalachia Educational Laboratory William Hunter University of Calgary Daniel Kalls Ume University Benjamin Levin University of Manitoba Thomas Mauhs-Pugh Green Mountain College Dewayne Matthews Western Interstate Commission for HigherEducation William McInerney Purdue University Mary McKeown-Moak MGT of America (Austin, TX) Les McLean University of Toronto Susan Bobbitt Nolen University of Washington Anne L. Pemberton email@example.com Hugh G. Petrie SUNY Buffalo Richard C. Richardson New York University Anthony G. Rud Jr. Purdue University Dennis Sayers Ann Leavenworth Centerfor Accelerated Learning Jay D. Scribner University of Texas at Austin Michael Scriven firstname.lastname@example.org Robert E. Stake University of IllinoisUC Robert Stonehill U.S. Department of Education David D. Williams Brigham Young UniversityEPAA Spanish Language Editorial BoardAssociate Editor for Spanish Language Roberto Rodrguez Gmez Universidad Nacional Autnoma de Mxico email@example.com Adrin Acosta (Mxico) Universidad de Guadalajaraadrianacosta@compuserve.com J. Flix Angulo Rasco (Spain) Universidad de Cdizfelix.firstname.lastname@example.org
18 of 18 Teresa Bracho (Mxico) Centro de Investigacin y DocenciaEconmica-CIDEbracho dis1.cide.mx Alejandro Canales (Mxico) Universidad Nacional Autnoma deMxicocanalesa@servidor.unam.mx Ursula Casanova (U.S.A.) Arizona State Universitycasanova@asu.edu Jos Contreras Domingo Universitat de Barcelona Jose.Contreras@doe.d5.ub.es Erwin Epstein (U.S.A.) Loyola University of ChicagoEepstein@luc.edu Josu Gonzlez (U.S.A.) Arizona State Universityjosue@asu.edu Rollin Kent (Mxico)Departamento de InvestigacinEducativa-DIE/CINVESTAVrkent@gemtel.com.mx email@example.com Mara Beatriz Luce (Brazil)Universidad Federal de Rio Grande do Sul-UFRGSlucemb@orion.ufrgs.brJavier Mendoza Rojas (Mxico)Universidad Nacional Autnoma deMxicojaviermr@servidor.unam.mxMarcela Mollis (Argentina)Universidad de Buenos Airesmmollis@filo.uba.ar Humberto Muoz Garca (Mxico) Universidad Nacional Autnoma deMxicohumberto@servidor.unam.mxAngel Ignacio Prez Gmez (Spain)Universidad de Mlagaaiperez@uma.es Daniel Schugurensky (Argentina-Canad)OISE/UT, Canadadschugurensky@oise.utoronto.ca Simon Schwartzman (Brazil)Fundao Instituto Brasileiro e Geografiae Estatstica firstname.lastname@example.org Jurjo Torres Santom (Spain)Universidad de A Coruajurjo@udc.es Carlos Alberto Torres (U.S.A.)University of California, Los Angelestorres@gseisucla.edu
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