Measuring the Academic Impact of Course Sequencing using Student Grade Data
Tess Gutenbrunner, Daniel Leeds, Spencer Ross, Michael Riad-Zaky, Gary Weiss
Jun 30, 2021 20:40 UTC+2
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Session PS1
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Gather Town
Keywords: Course Sequencing, Student Performance, Data mining, Education
Abstract:
Undergraduate college students have substantial flexibility in choosing the order in which they take courses, since most courses either have no prerequisites or only a single prerequisite. However, the specific order that courses are taken can have an impact on student performance. This paper describes a general methodology for assessing the impact of course sequencing on student performance, as measured by course grades, and applies this methodology to eight years of undergraduate academic data from Fordham University. The results demonstrate that certain course orderings are associated with improved student grade performance. This study introduces a methodology, new metrics, and a publicly available data-processing tool that can be applied to any student course-grade data set to measure course sequencing effects. The results can be used to inform student decisions, modify course recommendations, and even modify course prerequisites.