6
Data Collection
We know that 20 percent of engineers began their academic careers with at least 10 credits from a community college and that 40 percent of the recipients of engineering bachelor’s and master’s degrees in 1999 and 2000 attended a community college. However, there are a great many things about the community college pathway to engineering degrees and careers we do not know. A first step is simply to locate lower division engineering programs at community colleges—programs which may not be listed by a standard name. The committee’s perception—echoed by the workshop participants—is that there are important gaps in the data, mostly in reference to students. For example, did students earn their credits from community colleges during their senior year of high school, during the summer before they entered four-year engineering programs, or as students in engineering science who left before obtaining A.S. degrees? This question and a number of others may not be answerable with existing data. What percentage of those who hold engineering degrees transferred to four-year engineering programs (1) with A.S.degrees and (2) without A.S.degrees? What percentage of students who transferred to four-year engineering programs went on to earn undergraduate or graduate degrees in engineering?
Answers to these questions would provide valuable information on the retention of transfer students in four-year programs and on the value of completing A.S. degrees prior to transfer. Policies and programs would be designed differently, depending on the answers to these questions.
The lack of information (especially longitudinal and comparative information that can be disaggregated by gender, race/ethnicity, and other
background variables) on the successes and failures of students who begin their engineering educations in two-year and four-year programs presents serious problems for an analysis of the transfer function of community colleges. Most often, community colleges lose sight of students once they transfer to four-year institutions, precisely when they should begin tracking the educational and career trajectories of their students. Compiling and publicizing data on transfer students’ success in obtaining B.S. or advanced engineering degrees would demonstrate the effectiveness of engineering studies in community colleges nationally and improve their recruitment rates or point to the need to strengthen community college programs.
Less specific factors (e.g., economic, geographic, political, and social factors) also influence the effectiveness of attempts to improve the recruitment, retention, transfer, persistence to degrees (A.S., B.S., and advanced degrees), and the diversity of students on the community college pathway to engineering careers. Compiling and analyzing data on these factors, which are sometimes crucial to decisions, require more financial and personnel resources than smaller schools can afford.
KEY CHALLENGE
Some useful information is being collected. For example, primary data are collected by the National Center for Education Statistics at the U.S. Department of Education, National Science Foundation, and American Association of Engineering Societies Engineering Workforce Commission, which collects data on student enrollments and degrees. All of these data are necessary for policy makers and institutions to facilitate and evaluate the transfer process. However, the comparability and periodicity of data have yet to be determined. In fact, we do not know how many community colleges offer engineering sciences programs! The key challenge is to collect information disaggregated by institution and student characteristics, that is, longitudinal information. The Department of Education’s data are noteworthy examples of useful longitudinal data.
EXEMPLARY APPROACHES
Among the workshop participants who reported that their institutions do compile data on their students, four-year educational institutions were more likely than community colleges to undertake elaborate data collection and analyses and to gather quantitative as well as qualitative data.
University of California, Davis
A considerable amount of data on transfer students is collected at UCD, where a student information system integrates information associated with a student’s admissions application, transfer coursework, and UCD academic record. The Student Affairs Research and Information Unit frequently surveys students regarding their experiences during orientation, advising, retention, and extracurricular activities. The research unit also conducts surveys at intervals of 1, 10, 20, and 30 years after graduation. Alumni survey data are then linked to student data.
The workshop representative from UCD reported that much of the data has not been analyzed, especially with respect to community college transfer students, although the university hopes to do so when resources become available. One study of the persistence of community college transfer students showed that 89 percent of engineering transfer students completed a bachelor’s degree at UCD. Students who transfer and students entering as freshmen have virtually the same graduation rate.
Tidewater Community College/Old Dominion University/Virginia Polytechnic Institute and State University
Community colleges usually do not collect data on their students, and when they do, it is more limited in scope than student data collected by four-year institutions and qualitative rather than quantitative in nature. The Tidewater Community College Office of Institutional Research collects information primarily from voluntary postgraduation surveys. The surveys included questions about the college to which the student transferred, satisfaction with the preparation for transfer, and satisfaction with the program and instructors at TCC. Information from these surveys is typically available upon request.
Virginia Polytechnic Institute and State University share data on transfer students at articulation conferences, including (1) the overall acceptance rate for transfer students and TCC students and (2) grades (anonymously) for TCC transfer students.
West Kentucky Community and Technical College
In 1999, West Kentucky Community (WKC) and Technical College implemented a student survey to evaluate its programs and prepare for ABET accreditation. The surveys include questions about student backgrounds (e.g., age, family educational attainment, access to computers at home); commuting requirements; degree objectives; scheduling needs/preferences, reasons for choosing a collaborative program; and whether
they plan to continue complete an A.S. degree at WKC and/or transfer to a four-year engineering program. The response rate for these annual surveys has been 20–40 percent, and the results have been used in the ABET self-study. Recent surveys have also been conducted by the mathematics department to determine the effectiveness of the calculus series. WKC also collects information on students’ evaluations of their community college experience during advising sessions when students discuss course selections and career goals. Responses are not quantified, but certain incidents are documented for internal purposes.
CONCLUSION
Workshop participants whose institutions do not collect data on student outcomes cited cost as a barrier. Even schools that do collect data on students cited the cost of analyzing these data as a barrier to using them to evaluate the effectiveness of programs. Systematic data collection programs are needed to determine educational and career outcomes for students who begin and complete their educations in community colleges and for students transferring from community colleges to four-year programs.
A recent discussion, convened by the National Governors Association—an initiative that was created in hopes of influencing the impending reauthorization of the Higher Education Act and other major educational laws—explored ways to track students through elementary, secondary, and higher education, which would provide better data on dropout rates and other weaknesses in American education (Chronicle of Higher Education, 2005; Cunningham and Milan, 2005). Other information that panelists suggested would be useful were data on students receiving student aid, the number who need remedial work when they enter college, the number who enter college, especially part-time students who may not enroll directly after high school. The discussion explored ways to improve those stages of education by “aligning” the federal laws that govern them, an initiative the association announced in February, 2005.
The initiative has been opposed by groups citing privacy concerns. To address this issue, the state of Delaware uses randomly assigned numbers to track K–12 students’ dropout rates. Delaware is working to extend the use of those numbers to track the progress of students who attend public and private colleges in the state.
Conclusion 6-1 A comprehensive, systematic strategy for data collection on educational and career outcomes for community college and transfer students would require leadership in the engineering profession and from funding agencies to define the most relevant data items, to encourage col-
laboration between two- and four-year educational institutions, to provide for privacy of students, and to develop vehicles for dissemination.
Conclusion 6-2 A meeting of data-collecting agencies (e.g., National Center for Education Statistics, National Science Foundation Division of Science Resources Statistics, American Association of Community Colleges, and American Society for Engineering Education) would be an ideal forum for developing criteria for collecting data from different kinds of institutions.