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

Abstract

In this paper we argue that simply identifying gateway courses in which a large number of students fail or withdraw and focusing attention on them is not the best use of limited resources. No matter what we do, there will always be courses with high D/F/W rates simply because of the nature of their content and the preparation of the students who must take them. However, some gateway courses defy expectations and produce fewer DFWs than predicted while others produce more. Moreover, the timing of course taking can make a difference between success or failure for particular types of students, and failing or withdrawing from a course does not always lead to stopping out. In this paper we use examples from our work with the analyses of student records to show how one can use student type and point in their academic life to predict success in particular gateway courses. Relating predictions to observed DFW rates can highlight courses exceeding expectations and those which fall below them, and support a more nuanced understanding where attention is needed.

Digging Deeper Into the Data: The Role of Gateway Courses in Online Student Retention

“…Beyond these categorical variables, major predictors of individual student performance can be found in students' previous academic records (Sweeney, Rangwala, Lester & John, 2016;Jayaprakash, Moody, Eitel, Regan, & Baron, 2014;Bloemer, et al, 2017). At our institution, prior cumulative GPA is the most important of these.…”

“…For full-time, first-time Freshman, the first two years are significant as the transitions from first year to second year and from second year to third year have the greatest attrition. Additionally, the greatest attrition for online transfer students occurs between the first and second semesters (Bloemer, Day, & Swan, 2017). Since those students are an important part of our student population, we have classified separately the student's two semesters in their first year.…”

“…From our previous work (Bloemer, et al, 2017), we know that the discrimination ability of the regression for predictions for individual students can be improved by including categorical variables for at least some courses to reflect differences between courses. That step would be inappropriate here as the purpose of this regression equation is to control for student characteristics so that those very differences between courses can be examined more accurately.…”

“…In our earlier work (Bloemer, Day, & Swan, 2017), the difference between the actual DFW rate and the predicted DFW was used to produce a quantitative measure of course effectiveness. This approach is supplemented here with a graphical depiction.…”

Every Learner Everywhere and Lighthouse Institutions: First-Year Experiences

“…Why gateway courses? Difficulties that many first-generation students, low-income students, and students of color encounter in the introductory courses they take in their first two years of postsecondary education can lead to discouragement and abandonment of college plans (Bloemer, Day, & Swan, 2017). This insight led the foundation's postsecondary team to focus on gateway courses.…”