Title: Academic performance analysis to support proactive student advising for an electrical engineering program

Authors: Richelle V. Adams; Cathy-Ann Radix

Addresses: Department of Electrical and Computer Engineering, The University of the West Indies, St. Augustine Campus, Trinidad and Tobago ' Department of Electrical and Computer Engineering, The University of the West Indies, St. Augustine Campus, Trinidad and Tobago

Abstract: Using correlation, regression and hierarchical clustering methods, the authors examined three consecutive graduating cohorts of students in an electrical and computer engineering undergraduate program to determine which courses (or groups of courses) were the best predictors of graduation GPA. The aim was to develop predictive models that support a consistent proactive advising experience. The main impact of this study is the methodology which can be applied to other programs with similar weighted GPA schemes and with limited data sources. Other impacts were: the model identified which types of courses impacted GPA performance most, bringing clarity as to where cohort-wide intervention may be required; and the model can help us identify earlier 'at-risk' and 'exceptional' students.

Keywords: proactive advising; student performance; prediction; engineering curriculum.

DOI: 10.1504/IJQRE.2020.10028310

International Journal of Quantitative Research in Education, 2020 Vol.5 No.1, pp.16 - 38

Received: 26 Mar 2018
Accepted: 10 Apr 2019

Published online: 15 Apr 2020 *

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