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Educational policy analysis archives.
n Vol. 9, no. 49 (November 24, 2001).
Tempe, Ariz. :
b Arizona State University ;
Tampa, Fla. :
University of South Florida.
c November 24, 2001
Computing experience and good practices in undergraduate education : does the degree of campus "wiredness" matter? / Shouping Hu [and] George D. Kuh.
Arizona State University.
University of South Florida.
t Education Policy Analysis Archives (EPAA)
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1 of 20 Education Policy Analysis Archives Volume 9 Number 49November 24, 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 .Computing Experience and Good Practices in Undergra duate Education: Does the Degree of Campus "Wiredness" Matter? Shouping Hu Seton Hall University George D. Kuh Indiana UniversityCitation: Hu, S. and Kuh, G.D. (2001, November 24). Computing Experience and Good Practices in Undergraduate Education: Does the Degree of Camp us "Wiredness" Matter?, Education Policy Analysis Archives 9 (49). Retrieved [date] from http://epaa.asu.edu/epa a/v9n49.html.AbstractResponses to the College Student Experience Questionnaire 4th Edition from 18,844 students at 71 colleges and universitie s were analyzed to determine if the presence of computing and informat ion technology influenced the frequency of use of various forms of technology and other educational resources and the exposure to good educ ational practices. Undergraduates attending "more wired" campuses as d etermined by the 1998 and 1999 Yahoo! Most Wired Campus survey more frequently used computing and information technology and reported h igher levels of engagement in good educational practices than their counterparts at less
2 of 20wired institutions. Non-traditional students benefi ted less than traditional students, but both women and men students benefited comparably from campus "wiredness."IntroductionAn increasingly technology-oriented workplace makes competence in computer and information technology essential (Gilbert, 1996; Gr een & Gilbert, 1995; Morrison, 1999; West, 1996). Thus, it is no surprise that computing and information technologies have proliferated on most campuses and now typically rep resents a substantial share of an institution's operating budget (Finkelstein, France s, Jewett, & Scholz, 2000; Institute for Higher Education Policy, 1999). Continuously upgrad ed, the technology is supposed to add value to the student experience. E-mail, for ex ample, promises to remove time and distance barriers between students and faculty memb ers (Gilbert, 1995; D'Souza, 1992) and students are generally satisfied with this mode of communication, reporting that it has a positive effect on the learning process (D'So uza, 1992), especially when faculty members use email to elaborate on key points made d uring class discussions and provide feedback to students (D'Souza, 1992; Hawarth, 1999; Roach, 1999). Assuming the benefits of email extend to the use of other forms of electronic technologies, it seems plausible that more is bette r, meaning that the more pervasive the technology the more students will use it and the mo re they will benefit. However, relatively few studies have looked specifically at the relationships between computing and information technology and the overall undergra duate experience. It's also possible that prospective students consider the degree to wh ich an institution is "wired" (i.e., the availability of advanced forms of computing and inf ormation technology) when deciding to which schools they will apply and ultimately, th e specific college they will attend (Armstrong, 2000; Bernstein, Caplan, & Glover, 2000 ; Jackson, 2000). Some studies are encouraging, showing positive infl uences of the use of information technology on a broad range of desired outcomes of college (Flowers, Pascarella, & Pierson, 2000; Kuh & Vesper, 2001; Pew Internet and American Life, 2000). At the same time, others worry about potentially undesirab le consequences of the overwhelming presence of computer and information t echnology (Upcraft, Terenzini, & Kruger, 1999). For example, Wen (2000) reported tha t as more and more adolescents grow up communicating via instant electronic messag ing, chat rooms and email, they would be isolated from and have little experience w ith face-to-face human contact. Though the Internet offers almost unlimited access to information, some caution that it must not become "a substitute for hands-on learning (Malveaux, 2000, p. 38). In addition, it is not clear whether the availability and use of technology promotes or discourages student engagement in good educational practices, behaviors that are linked with a host of desirable college outcomes (Chickeri ng & Gamson, 1987). Haworth (1999) suggests that e-mail does not increase the f requency of student-faculty interaction, but rather allows it to take a differe nt form. Peers and faculty members are the two most importan t agents of socialization for students in college (Pascarella & Terenzini, 1991; Weidman, 1989). One way to determine the impact of computing and information t echnology on the quality of undergraduate education is to examine the relations hip between the degree to which a campus is wired and the level of student engagement in a range of empirically-derived good educational practices (Chickering & Gamson, 19 87). Included among such good
3 of 20practices are student-faculty contact, peer coopera tion, and active learning.PurposeThis study examines the relationships between the a vailability of computing and information technology (wiredness), use of the tech nology, and student engagement in three good educational practices (faculty contact, peer cooperation, active learning). Two questions guide this study.First, does highly accessible, advanced forms of co mputing and information technology have a demonstrable effect on students' experiences with this technology and their exposure to good educational practices? That is, do students use technology more frequently and interact more frequently with their teachers, engage in more cooperative peer activities, and have more active learning expe riences on wired campuses compared with their counterparts at less wired campuses?Second, does the degree of campus wiredness have di fferential effects on the experiences of different types of students (men and women, traditional age and older students)? Previous studies have reported certain d ifferences in how men and women use computing and information technology (Kuh & Hu, 2001; Pew Internet and American Life, 2000). However, it is not known whet her there are differences in the relationships between campus wiredness and students experiences with information technology and their exposure to good educational p ractices depending upon student characteristics such as gender or age.MethodsData Source and InstrumentThe data used in this study are from the College St udent Experiences Questionnaire (CSEQ) research program. The fourth edition of the CSEQ (Pace & Kuh, 1998) is designed for students attending four-year colleges and universities and gathers information about students' background (age, major field, and so forth) and their experiences in three areas. The first area is the a mount of studying, reading, and writing students do and the time and energy (quality of eff ort) they devote to various activities measured by items contributing to 13 Activities Sca les. One of these scales, Computer and Information Technology (C&IT), is composed of n ine items describing various forms and uses of computers and information technol ogy that we will discuss later in the paper. The response options for all Activities item s are: 1="never," 2="occasionally," 3="often," and 4="very often."The second area includes 10 Environment items repre senting student perceptions of the extent to which their institution emphasizes import ant conditions for learning and personal development. Student responses are scored on a 7 point scale ranging from "strong emphasis" = 7 to a "weak emphasis" = 1.The final set of questions asks students to estimat e the extent to which they have made progress since starting college in 25 areas that re present desired outcomes of higher education. Response options for the Gains items are : 1="very little," 2="some," 3="quite a bit," and 4="very much."
4 of 20The validity of self-reported information such as t hat obtained by the CSEQ has been thoroughly examined (Baird, 1976; Lowman & Williams 1987; Pace, 1985; Pike, 1995; Turner & Martin, 1984). Generally, self-reported in formation is likely to be valid if five conditions are met: (1) if the information requeste d is known to the respondents, (2) the questions are phrased clearly and unambiguously (La ing, Sawyer, & Noble, 1988), (3) the questions refer to recent activities (Converse & Presser, 1989); (4) the respondents think the questions merit a serious and thoughtful response (Pace, 1985), and (5) answering the questions does not threaten, embarras s, or violate the privacy of the respondent or encourage the respondent to respond i n socially desirable ways (Bradburn & Sudman, 1988). CSEQ items satisfy all these condi tions. The questionnaire requires that students reflect on what they are putting into and getting out of their college experience. The items are clearly worded, well defi ned, and have high face validity. The nature of the questions refers to common experience s of students during the current school year, typically a reference period of about six months or less. The format of most response options is a simple rating scale that help s students to accurately recall and record the requested information, thereby minimizin g this as a possible source of error. The Estimate of Gains items ask students to make a value-added judgment (Pace, 1990) and student responses to such questions are general ly consistent with other evidence, such as results from achievement tests (Brandt, 195 8; DeNisi & Shaw, 1977; Hansford & Hattie, 1982; Lowman & Williams, 1987; Pace, 1985 ; Pike, 1995). For example, Pike (1995) found that student reports to Gains items fr om the CSEQ were highly correlated with relevant achievement test scores and concluded that self reports of progress could be used as proxies for achievement test results if there was a high correspondence between the content of the criterion variable and p roxy indicator. Based on their review of the major college student research instruments, Ewell and Jones (1996) concluded that the CSEQ has excellent psychometric properties and high to moderate potential for assessing student behavior associated with college outcomes. The measure of the extent to which an institution i s wired ("wiredness") was from the "most wired" survey of college campuses conducted b y Yahoo! Internet Life magazine in 1998 and 1999, the same years the data for this stu dy were collected. The "most wired" survey collects information about a variety of fact ors related to information technology access and infrastructures (e.g., number of wired c lassrooms and dorms), general institutional support (e.g., library resources, ema il accounts), administrative services (e.g., on-line course registration, advising), and student support (e.g., technical support, orientation). Although somewhat controversial, more than 1,000 institutions participated in the most recent survey (Young, 2000). Because th e 1998 and 1999 rankings of campus wiredness for the 100 most wired campuses ar e somewhat unstable, we coded campus wiredness as a dichotomous variable. Thus, t hose colleges and universities that were ranked in either year were considered to be am ong the "more wired campuses" and those that were not ranked were categorized as "les s wired." SampleThe sample is composed of 18,344 undergraduates fro m 71 four-year colleges and universities who completed the 4th edition of the C SEQ in 1998 and 1999. The schools include 21 research universities (RU), 9 doctoral u niversities (DU), 22 comprehensive colleges and universities (CCU), 8 selective libera l arts colleges (SLA), and 11 general liberal arts colleges (GLA) as classified by The Ca rnegie Foundation for the
5 of 20Advancement of Teaching (1994). Although the mix of schools reflects the diversity and complexity of four-year colleges and universities, for all practical purposes the CSEQ database constitutes a convenience sample in that i nstitutions administer the instrument in different ways and for different reasons. Women (63%), traditional-age students (92%), first-year students (48%), and students from private colleges are over-represented in the sample compared with the national profile of undergraduates attending four-year colleges and universities. About 77% were White stu dents, 8% Asian Americans, 6% African Americans, 6% American Indians and students from other backgrounds and 4% Latinos. Also, more than half of the students were majoring in a pre-professional area, 17% in math and science, 10% in social science, and 8% in humanities. Almost one-fifth (19%) had majors from two or more of the major fiel d categories. Among the 71 institutions in this study, 21 were more wired camp uses with 29% of students and 50 were less wired campuses with 71% of students in th e sample. VariablesBecause socioeconomic status (SES) and student abil ity are highly correlated and affect college outcomes (Pascarella & Terenzini, 1991), tw o control variables were created, student SES and academic preparation. SES was repre sented by level of parents' education and the amount parents contributed to col lege costs. This estimate of SES is not a robust measure of socioeconomic status, but i t is the best approximation possible from the variables included on the CSEQ. Academic p reparation is the sum of student self-reported grades and educational aspirations. I n addition, institutional selectivity and control (public, private) were also controlled in a ll analyses with the selectivity measures taken from Barron's Profiles of American Colleges (1996). Student gender, race and ethnicity, major field, institutional type, and yea r in college were coded as dummy variables. The variables were coded as follows: Sex (0=women, 1=men); Age (0=traditional-age students under age 24, 1=stu dents 24 and older); Race or ethnicity was coded as a set of dummy varia bles: Asian Americans, African Americans, Latinos, Whites, and Other Ethni city (American Indians and others), with Whites as the omitted reference group ; SES (the sum of parent education where 1=neither pa rent a college graduate, 2=one parent a college graduate, and 3=both parents college graduates and amount parents contribute to college costs where 1=none to 6=all or nearly all); Academic preparation (the sum of grades where 5=A a nd 1=C, Cor lower and educational aspirations where 2=expect to pursue an advanced degree after college and 1=does not expect to pursue an advanced degree) ; Major field (humanities, mathematics and sciences, social sciences, pre-professional, and students in two or more major fields, with pre-professional omitted as reference group); Institutional type (RU, DU, CCU, SLA, GLA with RU o mitted as reference group); Institutional control (0=public, 1=private); Institutional selectivity (6=most competitive, 5=hi ghly competitive, 4=very competitive, 3=competitive, 2=less competitive, and 1=not competitive); Year in college (first-year, sophomore, junior, and senior, with first-year omitted as reference group); Colleges and universities that were ranked in eithe r year were considered to be
6 of 20among the "more wired campuses" (coded as 1) and th ose that were not ranked were categorized as "less wired" (coded as 0);Overall C&IT score (the sum of individual C&IT item scores). The psychometric properties for the computer and information technol ogy scale are acceptable, with a reliability alpha of .78. The interrelationship b etween C&IT items ranges from .102 to .735. The nine C&IT items are: Used a computer or word processor to prepare report s or papers. 1. Used e-mail to communicate with an instructor or ot her students. 2. Used a computer tutorial to learn material for a co urse or developmental/remedial program. 3. Participated in class discussions using an electron ic medium (e-mail, list-serve, chat group, etc.). 4. Searched the World Wide Web or Internet for informa tion related to a course. 5. Used a computer to retrieve materials from a librar y not at this institution. 6. Used a computer to produce visual displays of infor mation (charts, graphs, spreadsheet, etc.). 7. Used a computer to analyze data (statistics, foreca sting, etc.). 8. Developed a Web page or multimedia presentation. 9. The engagement measures included the three good pra ctice indicators: student-faculty contact, cooperation among students, and active lea rning. The items in each good practice indicator and the psychometric properties of the scales are presented in Appendix.Data AnalysisThe analysis was performed in two steps. First, we used analysis of covariance (ANCOVA) to estimate the impact of campus wiredness on the nature and frequency of computer and information technology use, including each of nine different uses ranging from "writing papers" to "developing web page and m ultimedia presentations" as well as an overall measure of use of C&IT defined as the su m of the frequency of the nine types of use. Then, we used multivariate analysis of cova riance (MANCOVA) to estimate a covariate model of the influence of campus wirednes s on the good practice variables, such as student-faculty contact, peer cooperation, and active learning. The independent variable was the dichotomized measure of campus wir edness (more wired was coded 1 and less wired coded 0). We then repeated the analy ses for both men and women separately to determine whether the relationships b etween campus wiredness, uses of technology, and student engagement in the three goo d practices differed for men and women. Finally, we repeated these analyses for both traditional and non-traditional students.We calculated the effect size of campus wiredness ( more wired vs. less wired) on the outcome variables following Cohen's (1977) suggesti ons where anything below .20 was considered a trivial effect, between .20 and .50 a small effect; between .50 and .80 a medium effect; and above .80 a large effect.ResultsTable 1 presents the descriptive statistics of the indicators on computing experience and
7 of 20 good practices for all students and students in mor e wired and less wired campuses. The three most frequent C&IT activities were using a co mputer for word processing, using e-mail to communicate with an instructor or classma tes, and searching the Internet for course material (Table 1). The three least frequent C&IT activities were developing a Web page or multimedia presentation, participating in class discussions via an electronic medium, and retrieving off-campus materials. This t rend is similar for students at both more wired and less wired campuses, but "using a co mputer tutorial" was among the least frequent activities for students at less wire d campuses. Students at more wired campuses had slightly higher average scores on eigh t of nine computing items (tied for retrieving off-campus library materials) and the to tal computing experience. The three good practice measures also very slightly favored s tudents at wired campuses.Table 1 Descriptive Statistics of Campus Wiredness, Computi ng Experience, and Good PracticesVARIABLES AllMore WiredLess Wired Mean (%) S.D.Mean (%) S.D.Mean (%) S.D. 1. Used computer/word processor forpaper 3.720.613.760.563.710.63 2. Used e-mail to communicate withclass 3.410.923.610.763.330.97 3. Used computer tutorial to learnmaterial 1.881.002.081.071.790.95 4. Joined in electronic class discussions1.711.001. 901.081.640.96 5. Searched Internet for course material3.160.923.2 50.893.120.93 6. Retrieved off-campus librarymaterials 1.801.011.801.031.801.00 7. Made visual displays with computer2.361.062.471. 072.311.05 8. Used a computer to analyze data1.951.032.051.071 .911.01 9. Developed Web page, multimediapresentation 1.630.941.721.021.590.91 C&IT Overall Score21.615.1922.655.3621.195.06 Good Practice Indicators Faculty-Student Contact23.015.5823.045.4323.005.64Student Cooperation20.804.7420.844.7220.784.74Active Learning41.877.5742.197.6541.747.53N 18,3445,31513,029 Tables 2 and 3 compare the computing experiences an d exposure to good educational practices at more and less wired campuses by sex an d age. Again, the same general patterns of using computer and information technolo gy were evident. The three most frequent C&IT activities were using a computer for word processing, using e-mail to
8 of 20 communicate with an instructor or classmates, and s earching the Internet for course material. The three least frequent C&IT activities were developing a Web page or multimedia presentation, participating in class dis cussions via an electronic medium, and retrieving off-campus materials (or using compu ter tutorial). Men and women who attended a more wired campus had slightly higher av erage scores on eight of nine computing items (tied for retrieving off-campus lib rary materials) and the total computing experience. Consistent with the findings reported by Kuh and Hu (in press), men used C&IT slightly more frequently than women a nd also preferred more advanced forms of C&IT. Women opted more often for word proc essing and e-mail, with men more frequently using visual displays, data analysi s, and multimedia presentation options.The general pattern of more frequent use of technol ogy favoring more wired campuses was also true for traditional-age students. However non-traditional (older) students showed a somewhat mixed pattern, though the overall computing score (C&IT) favored students at the more wired campuses with the advant age due primarily to the more frequent use of the more common forms of C&IT such as e-mail.Table 2 Descriptive Statistics of Computing Experience & Go od Practices By Gender in More and Less Wired CampusesVARIABLES MenWomen More WiredLess WiredMore WiredLess Wired Mean (%) S.D.Mean (%) S.D.Mean (%) S.D.Mean (%) S.D. Computing Experiences 1. Used computer/word processorfor paper 3.720.603.660.613.790.533.740.61 2. Used e-mail to communicatewith class 3.510.813.190.923.660.733.400.93 3. Used computer tutorial to learnmaterial 2.091.051.861.002.071.081.760.94 4. Joined in electronic classdiscussions 1.941.091.681.001.881.071.610.95 5. Searched Internet for coursematerial 3.230.873.100.923.270.903.130.94 6. Retrieved off-campus librarymaterials 1.891.051.871.011.751.021.760.99 7. Made visual displays withcomputer 2.541.042.461.062.431.082.221.04 8. Used a computer to analyzedata 2.221.092.151.031.951.051.770.96 9. Developed Web page,multimedia presentation 1.941.091.760.941.590.951.490.83 C&IT Overall Score23.075.6321.735.1922.395.1820.884 .78 Good Practice Indicators Faculty-Student Contact23.015.5822.985.5823.055.342 3.005.55
9 of 20 Student Cooperation20.464.8320.354.7421.064.6321.03 4.67 Active Learning41.217.5840.677.5742.777.6442.367.36N 1,9874,7773,3288,252Table 3 Descriptive Statistics of Computing Experience & Go od Practices by Age at More and Less Wired CampusesVARIABLES TraditionalNon-Traditional More WiredLess WiredMore WiredLess Wired Mean (%) S.D.Mean (%) S.D.Mean (%) S.D.Mean (%) S.D. Computing Experiences 1. Used computer/word processorfor paper 3.770.533.730.613.540.863.540.81 2. Used e-mail to communicatewith class 3.640.723.390.922.941.102.661.12 3. Used computer tutorial to learnmaterial 2.091.071.790.951.840.991.851.00 4. Joined in electronic classdiscussions 1.911.081.640.971.600.901.590.92 5. Searched Internet for coursematerial 3.270.883.130.933.021.012.990.99 6. Retrieved off-campus librarymaterials 1.801.031.791.001.901.071.911.01 7. Made visual displays withcomputer 2.471.072.311.052.401.072.331.07 8. Used a computer to analyzedata 2.061.071.911.011.901.021.951.05 9. Developed Web page,multimedia presentation 1.731.021.590.911.600.871.630.91 C&IT Overall Score22.745.3221.274.9820.745.7620.445 .68 Good Practice Indicators Faculty-Student Contact23.085.3923.075.6522.176.012 2.295.50 Student Cooperation20.934.7120.994.7518.944.4118.76 4.20 Active Learning42.127.6541.597.5643.567.5143.197.08N 5,06811,8052471,224 The differences in the three good practice indicato rs for students at more or less wired campuses were small and mixed in direction. Women h ad higher scores on the good practice indicators at both more and less wired cam puses. Traditional-age students reported more contact with their faculty members an d more interactions with their peers compared with older, non-traditional students. At t he same time, non-traditional students were more engaged in active learning activities tha n were traditional students (Table 3). To better understand the relationships between camp us wiredness and student experiences with computing and information technolo gy and good educational practices,
10 of 20 we must control the potentially confounding effects of student background and institutional characteristics such as control and s electivity. Table 4 presents the results from the ANCOVA and MANCOVA analyses that take thes e confounding effects into account.Overall, students on more wired campuses were much more likely to use computer and information technology (an effect size of .32). Thi s means that students at the "more wired" schools had on average about a .32 standard deviation advantage in the overall use of computer and information technology compared with their counterparts attending less wired institutions. This pattern was consisten t for all nine forms of the technology represented on the CSEQ, though the effect sizes we re generally small and in some cases trivial. This pattern of computing experience was c onsistent for men, women, and traditional students. However, the degree of wiredn ess did not affect older, non-traditional students except with regard to the use of e-mail, which favored students at the more wired campuses.Table 4 Effect Size of Campus Wiredness on Student Computing Experiences & Good Practices AllMenWomenTraditionalNonTraditional ANOVA 1. Used computer/word processor forpaper 0.10*0.12*0.09*0.10*0.06 2. Used e-mail to communicate withclass 0.23*0.31*0.19*0.23*0.29*3. Used computer tutorial to learnmaterial 0.28*0.25*0.29*0.29*0.00 4. Joined in electronic classdiscussions 0.24*0.26*0.24*0.26*0.00 5. Searched Internet for coursematerial 0.17*0.20*0.16*0.18*0.01 6. Retrieved off-campus librarymaterials 0.09*0.11*0.07*0.09*0.09 7. Made visual displays withcomputer 0.23*0.20*0.25*0.23*0.11 8. Used a computer to analyze data 0.20*0.18*0.22*0.21*0.01 9. Developed Web page, multimediapresentation 0.18*0.24*0.14*0.19*0.00 C&IT Overall Score 0.32*0.35*0.31*0.33*0.13 MANOVA
11 of 20 Faculty-Student Contact 0.08*0.11*0.06*0.08*0.07 Student Cooperation0.020.060.000.020.04Active Learning 0.11*0.13*0.09*0.11*0.10 N 18,3446,76411,58016,8731,471Note: Effect sizes over .20 were bolded; Less wired campuses were the reference group; p < .001.Statistically significant differences for student-f aculty contact and active learning favored all but non-traditional students at the "mo re wired" campuses. However, because the effect sizes were lower than .20 these differen ces are not likely to have any practical importance. No differences were found with regard t o peer cooperation for students as a whole or for any sub-group nor was campus wiredness related to the experiences of non-traditional students with any of the three good educational practices.LimitationsThis study is limited in several ways. First, the m easures of C&IT and other student experiences used in the study were limited to those represented on the CSEQ. The CSEQ C&IT items do not exhaustive the ever-expanding ran ge of possible computing and information technology available to students on man y campuses that conceivably could affect their learning in positive or negative ways. For example, instructor-designed use of hypermedia and hypertext are not specifically me ntioned nor are activities that represent non-educational uses of C&IT such as surf ing the Web or playing games. Thus, these data do not shed light on such potentia l debilitating behaviors associated with C&IT such as Internet addiction or cocooning ( Kandell, 1998; Reisberg, 2000). Second, this study is based on a convenience sample of institutions participating in the CSEQ research program from a recent two-year period If data from other institutions were available or a longer time period was covered perhaps the results would differ. Also, the measure of campus wiredness is based sole ly on the Yahoo! Internet Life survey. Other sources of data about the availabilit y and use of C&IT might have yielded other results.DiscussionAttending a wired campus seems to have positive tho ugh trivial in magnitude benefits on engagement in good educational practices. Althou gh the use of computing and information technology for word processing and e-ma il is practically universal, students attending a wired campus use these forms of technol ogy even more than their counterparts elsewhere. In the case of e-mail this was also true for older students. Kuh and Hu (in press) found that C&IT use was assoc iated in complex, statistically significant ways with the overall amount of effort students devote to educationally purposeful college activities. Academic effort comb ined with C&IT use in turn yielded greater gains in certain areas (e.g., science and t echnology, vocational preparation, and intellectual development). Taken together, the find ings of Kuh and Hu (in press) and this study confirm the popular view that C&IT use is pos itively related to college student learning and personal development. Equally importan t, the pervasive presence of C&IT
12 of 20at more wired campuses as determined in the present study did not have any negative effects, but ranged from benign to slightly positiv e on the outcome variables of interest. Even so, additional research is needed to determine the extent to which C&IT is being used for purposes that may be incompatible with the educational missions of postsecondary institutions, such as surfing the web playing games, or for personal use (e.g., communicating with family, friends, and empl oyers). Several studies suggest that use of C&IT may differ depending on student background characteristics (Kuh & Hu, 2001; Pew Internet and A merican Life, 2000). For instance, Kuh and Hu (in press) found that overall men more f requently used C&IT compared with women. But in terms of different types of C&IT use, women favored word processing and e-mail, with men more frequently usi ng visual displays, data analysis, and multimedia presentation options. The findings i n this study indicated the degree of campus wiredness benefited both women and men compa rably with regard to their computing experiences and exposure to good educatio nal practices. The only major difference related to student background characteri stics was that non-traditional students seem to benefit less from campus wiredness than tra ditional students, with the single exception of e-mail use. Though some have argued th at computing and information technology may be less accessible to students of co lor compared with White students (Malveaux, 2000), this was not the case in our prev ious study of C&IT use (Kuh & Hu, 2001). This may be because accessibility to C&IT is less of a problem once students are in college. Additional research into these and rela ted questions would be welcome. We did not conduct any kind of cost-benefit analysi s in assessing the merits of C&IT on student engagement in good educational practices or the frequency and satisfaction with the availability or use of the technology. The diff erences favoring students at the more wired campuses were generally so small so as to not be practically significant. Perhaps a careful examination of the investments made by more wired campuses in technology and additional measures of student learning outcomes wo uld suggest that some of this money might be better spent on other types of resou rces (e.g., additional faculty members) if it can be demonstrated that other types of educational experiences yield greater benefits. But it is also possible that more precise estimates of campus wiredness would discover more sizeable differences in the mag nitude of the relationships between C&IT and educationally purposeful student experienc es. That is, this study divided institutions into only two groups (more wired, less wired). Should the rankings of wiredness become more stable, it would be prudent t o determine if the strength of the relationships between C&IT and student experiences increases.ConclusionComputer and information technology represents a su bstantial investment of university resources that fortunately seems to be generally be neficial for virtually all types of students. The results of this study show that the d egree of campus wiredness was positively associated with student use of computer and information technology, although the effect sizes were generally small in magnitude. The evidence also suggests that campus wiredness did not reduce student engagement in good practices such as student-faculty contact, cooperation among students and active learning. In fact, students at more wired schools actually reported mo re contact with their teachers and more substantive interaction with their peers. In a ddition, there was no gender difference in the relationship between the degree of campus wi redness and student computing
13 of 20experience and engagement in good practices. That s aid, older, non-traditional students did not seem to benefit as much as their younger co unterparts. On balance, it appears that the presence of computi ng and information technology, even on campuses where it is especially prevalent, does not hinder the educational process. Additional research is needed to corroborate these findings and to better understand the effects of technology use on student learning and p ersonal development.ReferencesArmstrong, L. (2000, March 13). How wired is that c ampus? Learn the "port-to-pillow" ratio before you pick a school. Business Week Online http://www.businessweek.com:/2000/00_11/b3672136.ht m Baird, L. L. (1976). Using self-reports to predict student performance New York: The College Board.Barron's Profiles of American Colleges (1996). Hauppage, NY: Barron's Educational Series.Bernstein, R., Caplan, J., & Glover, E. (2000). Ame rica's most wired colleges: 2000. Yahoo! Internet Life Bradburn, N.M., & Sudman, S. (1988). Polls and surveys: Understanding what they tell us San Francisco: Jossey-Bass. Brandt, R. M. (1958). The accuracy of self estimate s. Genetic Psychology Monographs 58 55-99. Carnegie Foundation for the Advancement of Teaching (1994). A classification of institutions of higher education Princeton, NJ: Carnegie Foundation for the Advancement of Teaching.Chickering, A. W., & Gamson, Z. F. (1987). Seven pr inciples for good practice in undergraduate education. AAHE Bulletin, 39 (7), 3-7. Cohen, J. (1977). Statistical power analysis for the behavioral scien ces (Rev. ed.) New York: Academic Press.Converse, J.M., & Presser, S. (1989). Survey questions: Handcrafting the standardized questionnaire Newbury Park, CA: Sage. D'Souza, P. V. (1992). Emails role in the learning process: A case study. Journal of Research on Computing in Education, 25 254-264. DeNisi, A.S., & Shaw, J.B. (1977). Investigation of the uses of self-reports of abilities. Journal of Applied Psychology 62 641-644. Dolence, M. G., & Norris, D. M. (1995). Transforming higher education: A vision for learning in the 21st century Ann Arbor, MI: Society for College and University Planning.
14 of 20Ewell, P. T., & Jones, D. P. (1996). Indicators of "good practice" in undergraduate education: A handbook for development and implement ation Boulder, CO: National Center for Higher Education Management Systems.Finkelstein, M. J., Frances, C., Jewett, F. I., & S cholz, B. W. (2000). Dollars, distance, and online education: The new economics of college teaching and learning Phoenix, AZ: ACE and the Oryx Press.Flowers, L., Pascarella, E. T., & Pierson, C. T. (2 000). Information technology use and cognitive outcomes in the first year of college. Journal of Higher Education 6 637-667. Gilbert, S. W. (1995). Technology and the changing academy: Symptoms, questions, and suggestions. Change, 27 (5), 58-61. Gilbert, S. W. (1996). Making the most of a slow re volution. Change, 28 (2), 10-23. Green, D. C., & Gilbert, S. W. (1995). Great expect ations: Content, communications, productivity, and the role of information technolog y in higher education. Change, 27 (2), 8-18.Hansford, B.C., & Hattie, J.A. (1982). The relation ship between self and achievement/performance measures. Review of Educational Research 52 123-142. Haworth, B. (1999). An analysis of the determinants of student email use. Journal of Education for Business 55-59. Higher Education Research Institute (1999). Freshmen embrace the Internet as an educational tool Los Angeles: UCLA Graduate School of Education & Information Studies.Institute for Higher Education Policy (1999). Distance learning in higher education Washington, DC: Institute for Higher Education Poli cy. Jackson, G. A. (2000, August 11). The wired campus: Enough is enough. Chronicle of Higher Education B8. Kandell, J. J. (1998). Internet addiction on campus : The vulnerability of college students. CyberPsychology & Behavior 1 (1). [online] http://www.inform.umd.edu/CC/Personal/~kandell/iacpb art.htm. Kuh, G. D., & Hu, S. (2001). The relationships betw een computer and information technology use, selected learning and personal deve lopment outcomes, and other college experiences. Journal of College Student Development, 42 217-232. Kuh, G. D., & Vesper, N. (2001). Do computers enhan ce or detract from student learning. Research in Higher Education 42 87-102. Kuh, G. D., Vesper, N., Connolly, M. R., & Pace, C. R. (1997). College Student Experiences Questionnaire: Revised norms for the th ird edition Bloomington, IN: Indiana University Center for Postsecondary Researc h and Planning.
15 of 20Laing, J., Swayer, R, & Noble, J. (1989). Accuracy of self-reported activities and accomplishments of college-bound seniors. Journal of College Student Development 29 ,362-368. Lowman, R. L., & Williams, R. E. (1987). Validity o f self-ratings of abilities and competencies. Journal of Vocational Behavior, 31 1-13. Malveaux, J. (2000). Technology, learning, and the future of education. Black Issues in Higher Education, 17 38. McCollum, K. (2000, February 25). Eleven leading un iversities opt out of magazine's Â‘most wired' competition. Chronicle of Higher Education A53. Morrison, J. L. (1999). The role of technology in e ducation today and tomorrow: An interview with Kenneth Green, Part II. On The Horizon, 7 (1), 2-5. Pace, C. R. (1985). The credibility of student self-reports Los Angeles: University of California, The Center for the Study of Evaluation, Graduate School of Education. Pace, C.R. (1990). College Student Experiences Questionnaire, Third Ed ition Los Angeles: University of California, The Center for t he Study of Evaluation, Graduate School of Education. (The CSEQ is now distributed b y the Center for Postsecondary Research and Planning, Indiana University).Pace, C. R., & Kuh, G. D. (1998). College Student Experiences Questionnaire, Fourth Edition Bloomington, IN: Indiana University Center for Po stsecondary Research and Planning.Pascarella, E. T., & Terenzini, P. T. (1991). How college affects students: Findings and insights from twenty years of research San Francisco: Jossey-Bass. Pew Internet and American Life (2000). Tracking online life: How women use the internet to cultivate relationships with family and friends http://126.96.36.199/reports/pdfs/Report1.pdfPike, G. R. (1995). The relationships between selfreports of college experiences and achievement test scores. Research in Higher Education, 36 1-22. Reisberg, L. (2000, June 5). 10% of students may sp end too much time online, study suggests. The Chronicle of Higher Education [online ] http://chronicle.com/free/2000/06/2000060501t.htmRoach, R. (1999). The higher education technology r evolution. Black Issues in Higher Education, 16 92-97. Turner, C. F., & Martin, E. (Eds.). (1984). Surveying subjective phenomenon (Vol. 1). New York: Russell Sage Foundation.Upcraft, M. L., Terenzini, P. T., & Kruger, K. (199 9). Looking beyond the horizon: Trends shaping student affairs--Technology. In C. J ohnson and H. Cheatham (Eds.), Higher education trends for the next century: A res earch agenda for student success (pp.
16 of 20 30-35). Washington, DC: American College Personnel Association. Weidman, J.C. (1989). Undergraduate socialization: A conceptual approach. In J.C. Smart (Ed.). Higher education: Handbook of theory and research Vol. V (pp. 289-322). New York: Agathon.Wen, P. (2000, April 27). Disconnected: Teens being isolated from face-to-face human contact. The Times-Picayune E1, E4. Young, J. R. (2000, April 28). Yahoo's Â‘most wired colleges' list again provokes controversy. Chronicle of Higher Education A49.About the AuthorsShouping Hu Assistant Professor Department of Educational Administration and Superv ision College of Education and Human Services Seton Hall University 400 South Orange Avenue South Orange, NJ 07079Tel: 973-275-2324 Fax: 973-761-7642 Email: firstname.lastname@example.orgShouping Hu is Assistant Professor of Higher Educat ion and Educational Research at Seton Hall University. His current research concent rates on college access, choice, persistence, financial aid policy, college student engagement in learning, and college impact on students. He taught graduate-level course s Finance in Higher Education, Educational Policy Analysis, and Educational Resear ch Design at Seton Hall. George D. Kuh Professor Center for Postsecondary Research and Planning School of Education Indiana University 201 N. Rose Avenue Bloomington, IN 47405Tel: 812-856-8383 Fax: 812-856-8394 Email: email@example.comGeorge D. Kuh is Chancellor's Professor of Higher E ducation at Indiana University Bloomington and director of the National Survey of Student Engagement and the College Student Experiences Questionnaire Program. His current research focuses on efforts to improve undergraduate education and coll ege and university cultures.AppendixCSEQ Items That Represent Good Practice in Undergra duate Education
17 of 20Student-Faculty Contact (The alpha coefficient for computing experience is 0.82, and the item intercorrelations range from 0.03 to 0.58.) Asked a librarian or staff member for help in findi ng information on some topic. Asked your instructor for information related to a course you were taking (grades, make-up work, assignments, etc.). Discussed your academic program or course selection with a faculty member. Discussed ideas for a term paper or other class pro ject with a faculty member. Discussed your career plans and ambitions with a fa culty member. Socialized with a faculty member outside the classr oom (had a snack or soft drink, etc.) Participated with other students in a discussion wi th one or more faculty members outside of class. Worked with a faculty member on a research project. Used e-mail to communicate with an instructor or ot her students. Met with a faculty member or staff advisor to discu ss the activities of a group or organization. Talked with a faculty member, counselor or other st aff member about personal concerns. Cooperation Among Students (The alpha coefficient for computing experience is 0.70, and the item intercorrelations range from 0.03 to 0.61.) Worked on a class assignment, project, or presentat ion with other students. Tried to explain material from a course to someone else (another student, friend, co-worker, family member). Met other students at some campus location (campus center, etc.) for a discussion. Played a team sport (intramural, club, intercollegi ate). Worked on a campus committee, student organization, or project (publications, student government, special event, etc.). Worked on an off-campus committee, organization, or project (civic, group, church group, community event, etc.). Managed or provided leadership for a club or organi zation, on or off the campus. Discussed with another student, friend, or family m ember why some people get along smoothly, and others do not. Asked a friend for help with a personal problem. Active Learning (The alpha coefficient for computing experience is 0.82, and the item intercorrelations range from 0.01 to 0.49.) Gone back to read a basic reference or document tha t other authors had referred to. Made a judgment about the quality of information ob tained from the library, World Wide Web, or other sources.
18 of 20 Participated in class discussions using an electron ic medium (e-mail, list-serve, chat group, etc.). Took detailed notes during class. Contributed to class discussions. Developed a role-play, case study, or simulation fo r a class. Tried to see how different facts and ideas fit toge ther. Summarized major points and information from your c lass notes or readings. Applied material learned in a class to other areas (your job or internship, other courses, relationships with friends, family, co-wor kers, etc.). Used information or experience from other areas of your life (job, internship, interactions with others) in class discussions or a ssignments. Worked on a paper or project where you had to integ rate ideas from various sources. Used a dictionary or thesaurus to look up the prope r meaning of words. Used a campus learning lab or center to improve stu dy or academic skills (reading, writing, etc.). Read articles or books about personal growth, selfimprovement, or social development. Read articles about scientific or mathematical theo ries or concepts in addition to those assigned for a class. Identified with a character in a book, movie, or te levision show and wondered what you might have done under similar circumstance s. Taken a test to measure your abilities, interests, or attitudes. Copyright 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 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
19 of 20 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 Education Commission of the States 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 California State UniversityÂ—Stanislaus Jay D. Scribner University of Texas at Austin Michael Scriven firstname.lastname@example.org Robert E. Stake University of IllinoisÂ—UC Robert Stonehill U.S. Department of Education David D. Williams Brigham Young University EPAA 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 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 Investigacin Mara Beatriz Luce (Brazil)Universidad Federal de Rio Grande do
20 of 20 Educativa-DIE/CINVESTAVrkent@gemtel.com.mx email@example.com 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