Gap Analysis: An Innovative Look at Gateway Courses and Student Retention

Summary and Critique by Keith Robinson Jr.

Summary

Authors William Bloemer, Scott Day, and Karen Swan of University of Illinois--Springfield challenged the notion that identifying gateway courses in which faculty focuses their attention on the large number of students that fail or withdraw is an effective use of limited resources. The authors recognized that these gateway courses do not have the same impact on all students, an unfair assumption that previous approaches in quantifying and identifying the best "fix" tend to share. Students come from diverse backgrounds and have different learning needs. They argue that the effectiveness of a course should be determined by the contexts of the students within it; "it is unreasonable to expect all courses to serve students equally well." The authors searched for the right measures to identify problem gateway courses, taking a look at the context of the students enrolled.

The data was pulled from all undergraduate degree-seeking students enrolled in a small, Midwestern public university over a four year period. An end of term grade of D, F, or prior Withdrawal from a course indicated that the student failed to complete the course successfully. The authors measured persistence, enrollment in the next regularly scheduled term or graduation, for two reasons: the probability of a student that takes a break in enrollment to graduate is much lower because most students simply do not return, and in order to connect individual courses to persistence it must be done with a short measure.

Students were classified according to type and stages in their academic life cycle. Student types were as follows: Native Freshmen, Honors Freshmen, On-ground Transfers, and Online Transfers. Stages in the academic life cycle were the first term (critical for transfer students), end of the first year/second semester (freshmen), and second and third year. Anything beyond the third year was considered the last stage. The research utilized a binary logistic regression to predict the probability a student would post a D, F, or Withdraw grade in any specific course the institution offered over a particular four-year period. Student Type, point in the Student Life Cycle, prior cumulative GPA, and fraction of courses students already received a D, F, or W were predictor variables. The predicted D, F, and W rates were utilized as a benchmark against actual course performance, and the difference (Gap) between them was calculated.

The results of the study illustrated that the ranking of courses based on actual and predicted DFW rates painted a similar picture; however, significant differences were noted as well. Some courses with high DFW rates had high predicted rates, some courses performed better than expected. There were also courses with DFW rates not high enough to attract attention but are much higher than expected given the student population. And there were courses with extremely low DFW rates, near zero, despite predicted rates being substantial.

In conclusion, while gateway courses with D, F, and Withdrawal rates are the first to receive the attention of retention efforts, at times this attention is misdirected and often harmful. It may be necessary to identify "problem" courses to replicate its relative success with a specific student type or problematic student population. It is beneficial to identify problem courses, however, it is equally as beneficial to identify the student types and at what cycle they are in their academic careers to base expectations.

Critique

The study is clearly limited to the undergraduate population of a small, Midwestern public university over a four-year period; it is not indicative of all students across the US. In analysis of D, F, and W grades received, there appeared to be students with high GPAs with high W rates, assumed to protect their GPAs. That skews the data. It is also nearly impossible to truly quantify problem courses. While a course may prove difficult, it could just as easily be due to lack of student effort. Additionally, The authors recognize that other approaches than that utilized in the research may be more appropriate for other academic institutions based on local factors that impact student success (or failure). And finally, while the fastest, most cost-effective solution to high DFW rates may be in academic advising such as preventing particular types of students from attempting courses known to be difficult for students at their current stage of academic life cycle, that may come across as discriminatory. 

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Gap Analysis: An Innovative Look at Gateway Courses and Student Retention