Abstract
Improvement in undergraduate retention and progression is a priority at many US postsecondary institutions and there seems to be a growing movement to address it by identifying gateway courses (foundational courses in which a large number of students fail or withdraw) and concentrating on “fixing” them. This paper argues that may not be the best use of limited resources. No matter what we do, there will always be courses with high DFW rates simply because of the nature of their content and the preparation of the students who must take them. Our research suggests that student type and academic stage affect student success and that gateway courses (courses which block student progression) can be found at all undergraduate levels. Specifically, we have found that one can use student type, academic stage, cumulative GPA, and prior withdrawals to predict success in undergraduate courses. Moreover, relating predictions to observed DFW rates can highlight courses exceeding expectations, and those which fall below them, to support a more nuanced understanding of where and what attention is needed. We illustrate the utility of such approach by examining issues surrounding success in online courses at our institution.
Highlights
Improvement in undergraduate retention and progression is a priority at many US postsecondary institutions
“Gap analysis” is the name we have applied to the procedure we have developed for identifying courses that may impede student success
Gateway courses with high DFW rates are known to contribute to student attrition (Koch & Pistilli, 2015), which makes them attractive targets for the use of data analytics
Summary
Improvement in undergraduate retention and progression is a priority at many US postsecondary institutions. We have found that one can use binary logistic regression with student type, academic stage, cumulative GPA, and prior withdrawals as predictor variables to predict success in undergraduate courses at our institution. One promising step in addressing this issue has been identifying gateway courses, entry level courses which are not passed by a large number of students, impeding their progression to degree (Koch & Pistilli, 2015; Gardner Institute, 2017). Which students are exceeding expectations; DFW rates which are higher than expected indicate courses in which students are failing to meet expectations This approach allows us to isolate courses for further (qualitative) investigation with the goal of identifying issues impeding students’ progression to degree.
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