Abstract
There are a number of contributing factors to misperceptions over first-year retention rates among traditional and non-profit university students. In addition to the usual transitional, social, emotional and academic determinants, modern-day university students face unprecedented economic burdens and pressures driven by the state of the job market. Data on these and other factors must be gathered and extrapolated using quantitative methods in order to derive an accurate picture of the true situation if the furtherance of misperceptions is to be avoided.
Keywords: retention rates, traditional, non-profit, university, academic quantitative
Introduction
In many ways, the stakes for college students have never been higher or more difficult to attain. Widespread access to a secondary education, once a hallmark of an affluent society, has been badly eroded by the nation’s recent economic downturn, the worst since the Great Depression. Once-abundant funding for America’s traditional and non-profit colleges and universities has dwindled at an alarming rate, pushing more and more of the cost onto students, who must assume massive debt before they graduate and enter the job market. This is an increasingly bleak situation, but the prospects for individuals without a university education are even bleaker. Thus, young Americans today face a dilemma: accumulate burdensome debt in order to earn a degree or forego a college degree and take their chances in a competitive, technology-driven job market. America’s university students have never faced pressure quite like this. Even so, it is not sufficient to determine or explain retention rates among first-year students.
It is not surprising that perceptions over first-year student retention rates at traditional and non-profit universities should reflect ambiguity given the current environment. There are a number of factors involved in first-year student retention that have little or nothing to do with finances, or future job prospects. These other factors present a complex picture that does not easily lend itself to interpretation. Alienation; separation from family and friends and academic and social adjustment problems are part of a correlative mix that requires a much more extensive and detailed examination of the student loss situation at these schools. The importance of such a study is considerable at this time, considering how much of the available student pool has been co-opted by for-profit universities, in particular by Web-based institutions that allow students to earn a degree at home. Ultimately, it is vital that the industry secure an accurate picture of the situation before determining and adopting a corrective course of action.
Research design
Writers, researchers and observers of trends in postsecondary education agree, in general, that transitional issues play a large role in first-year college student retention. Studies conducted over the past two decades have drawn considerable attention from university administrators to this issue. “In 1997, concerns about enrollment growth, persistence, graduation, and student learning led university administrators to focus on student transition” (Cavote and Koprera-Frye, 2004). In order to capture as representative a cross-section as possible, this study will seek to quantify a number of elements that impact the retention rates of first-year students in traditional and non-profit universities, including:
The number of universities that offer “First-Year Experience” courses, which provide students with important information that extends the orientation process throughout the first year (Barefoot, 2003)
The prevalence of social support and transitional counseling services offered by universities, aimed at helping first-year students become acclimated to their new environment
The implementation of non-consequential (i.e. ungraded) self-assessment tools, used during the first year in order to provide the student with a sense of their academic performance, build confidence and offer students an opportunity to engage in two-way communication with instructors (Tinto, 1997)
The comparative impact of curricula across the various universities and the extent to which differences in (and the variety of) course offerings contribute to retention/persistence rates among first-year students
Demographic data, including race/ethnicity, gender, age, economic background and cultural attitudes toward higher education
Personal and lifestyle data, ranging from employment status to dating activity (aimed at gauging comparative levels of social activity across universities)
Quantitative research will be preferable to qualitative data gathering for several important reasons. In this process, the information gathered must not be tainted or inappropriately influenced by the interpretation of anecdotal evidence, so it will be necessary and desirable to take the interviewer out of the equation. This is a study designed to disprove a prior conception about first-year student retention rates, so it will be vital to extrapolate purely numerical data that can be used to correct this misperception. The kind of skewed perspective that produced the problematic notion about differences in first-year retention rates, presumably, originated in unsubstantiated assumptions. Therefore, it will be crucial to utilize a combination of well-prepared, detailed quantitative tools, such as online surveys and questionnaires. To the extent possible (and practicable), existing university student data will be accessed and incorporated to facilitate the research process.
Statistical testing
The survey data accumulated from the 20 traditional and non-profit universities will be extrapolated and broken out into tables that reflect comparative findings in the data categories outlined under research design. Each table will reflect, in numbers and bar graphs, an accurate representation of the comparative retention rates. Additionally, chi-square analysis will be utilized to parse the more directly quantifiable information, such as demographics and lifestyle data. In order to determine authoritative conclusions from the data collected, this study will take advantage of recent advances in statistical theory and computational practices, as spelled out in the Research in Higher Education article by Eric L. Dey and Alexander W. Astin (1993). As Dey and Astin point out, there is little difference between “traditional linear regression” models and more arcane methods, such as probit analysis. Thus, this study will employ up-to-date statistical and computer software-based analytical tools but will use a linear construct in the analysis of the information thus produced.
In order to round out the measures of student persistence, the study will implement a predictor covariate, as used in the Cavote/Kopera-Frye student retention study. This will consider high school GPAs and ACT scores, which will be used to develop a composite, retention determinant picture using scores from approximately 300 students from traditional and non-profit universities. Cavote/Kopera-Frye indicates that “ACT scoresand high school GPAwere significantly correlated with students’ RFI category” (year).
Ethical considerations
One of the primary factors in determining that a quantitative approach is preferable in this case is that it provides a more reliable safeguard for data sources, which will be utilized as a collective rather than as individual subjects used in an experimental or quasi-experimental environment. Any information gathered will be done so under supervision by university officials. The personal student survey will be administered at the end of class, with the participation of the course instructor who will serve as proxy. Otherwise, all survey data will be gathered using secure, online technology, which will be password protected and protected under U.S. law as proprietary information. The success of the entire study will hinge on the extent to which university stakeholders can be convinced that university data and student input will be protected.
Conclusion
The greatest need in light of the present misperception is to gather a data field sufficiently broad to prove that assumptions concerning first-year student retention rates are demonstrably wrong. Quantification is the only reliable means for achieving this goal. To that end, clearly delineated findings can be used to “fine tune” qualitative approaches that address the problem on an individual level (McLaughlin, Brozovsky and McLaughlin, 1998). The historic prevalence of first-year student departure is at risk of reaching historic levels, given persistent economic and other market-driven factors. As such, it is essential that misperceptions be thoroughly disproven and corrected.
References
Barefoot, B. (2003). “Second Survey of First-Year Academic Practices.” Brevard, NC: Policy
Center on the First Year of College. Web. http://www.brevard.edu/fyc/survey/2002/findings.html.
Cavote, S. and Kopera-Frye, K. (2004). “Non-Traditional Student Persistence and First
Year Experience Courses.” Journal of College Student Retention, 8(4).
Dey, E. L. and Astin, A. W. (1993). “Statistical Alternatives for Studying College
Retention: A Comparative Analysis of Logit, Probit, and Linear Regression.” Research in Higher Education, 34(5).
Fidler, P.P. (1991). “Relationship of Freshman Orientation Seminars to Sophomore Return
Rates.” Journal of the Freshman Year Experience, 3(1).
McLaughlin, G.W., Brozovsky, P.V. and McLaughlin, J.S. (1998). “Changing
Perspectives on Student Retention.” Research in Higher Education, 39(1).
Tinto, V. (1999). “Taking Student Retention Seriously: Rethinking the First Year of
College.” NACADA Journal, 19(2).
