Karen Swan, William Bloemer, Leonard Bogle, Scott Day


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.


predictive analytics; gateway courses; student success

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DOI: http://dx.doi.org/10.24059/olj.v22i4.1515

Copyright (c) 2018 Karen Swan, William Bloemer, Leonard Bogle, Scott Day