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INFORMATICS IN EDUCATION
Journal of Eastern and Central Europe

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INFORMATICS IN EDUCATION

ISSN 1648-5831

© Vilnius University Institute of Mathematics and Informatics

2016, Vol. 15, No. 1
pp. 85-102

DOI: http://dx.doi.org/10.15388/infedu.2016.05

Data Mining of Undergraduate Course Evaluations

Yuheng Helen JIANG, Sohail Syed JAVAAD, Lukasz GOLAB

University of Waterloo
Waterloo, Ontario, N2L 3G1, Canada

Abstract

In this paper, we take a new look at the problem of analyzing course evaluations. We examine ten years of undergraduate course evaluations from a large Engineering faculty. To the best of our knowledge, our data set is an order of magnitude larger than those used by previous work on this topic, at over 250,000 student evaluations of over 5,000 courses taught by over 2,000 distinct instructors. We build linear regression models to study the factors affecting course and instructor appraisals, and we perform a novel information-theoretic study to determine when some classmates rate a course and/or its instructor highly but others poorly. In addition to confirming the results of previous regression studies, we report a number of new observations that can help improve teaching and course quality.

Keywords:

course evaluation, entropy, regression.




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Vilnius University Institute of Mathematics and Informatics, 2016