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Abstract-As enrollment in computer science (CS) majors continues to rise, CS departments are facing increased pressure to accommodate larger numbers of students, improve student graduation rates, and reduce time to graduate. As a result, effective student advising is critical to ensure the CS major is the right fit for students and to help students complete the degree in a timely and successful manner. Additionally, advisers play a crucial role in identifying struggling students and ensuring at-risk students either improve or quickly transition to a different major (saving resources both for the student and for the department). However, it is challenging for CS advisers to identify struggling students early. Often, by the time at-risk students are identified, these students have expended a considerable amount of time, effort, and money in the major when they could have been pursuing a major more suitable to their strengths. In the present work, we analyze actual enrollment data and develop models for predicting student performance. By leveraging these data-based models, we can identify at risk students with up to 77% accuracy. Based on these models, we also propose approaches to improve student advising in CS undergraduate programs.
Index Terms-Education, Success, Prediction, Classification, Advising, Modeling
(ProQuest: ... denotes formulae omitted.)
I. INTRODUCTION
From 2010-2017, the number of computer science (CS) degrees conferred has increased 50.7% [1]. While many students are interested in pursuing a CS degree, not all students are prepared or suited to the degree. In fact, 28% of students who start in CS will change majors within the first three years [2]. Since CS programs are increasingly overcrowded, it is crucial to help students succeed and graduate in a timely manner. Similarly, students who are having difficulty with the computer science degree need to be offered support in order to quickly improve, or be advised to find another major before investing too heavily into the degree. The sooner a student realizes that CS is not the right fit, the sooner the student can transition to a better fit major, and the sooner the CS department can free up limited space and resources to help additional CS students succeed.
Given the increasing enrollment and high student turnover in CS degree programs, identifying and advising struggling students early in the...
