Teaching Undergraduate Artificial Intelligence Classes: An Experiment with an Attendance Requirement

Authors

  • Sven Koenig University of Southern California
  • Tansel Uras University of Southern California
  • Liron Cohen University of Southern California

DOI:

https://doi.org/10.1609/aaai.v34i09.7060

Abstract

We report on an experiment that we performed when we taught the undergraduate artificial intelligence class at the University of Southern California. We taught it – under very similar conditions – once with and once without an attendance requirement. The attendance requirement substantially increased the attendance of the students. It did not substantially affect their performance but decreased their course ratings across all categories in the official course evaluation, whose results happened to be biased toward the opinions of the students attending the lectures. For example, the overall rating of the instructor was 0.89 lower (on a 1-5 scale) with the attendance requirement and the overall rating of the class was 0.85 lower. Thus, the attendance requirement, combined with the policy for administering the course evaluation, had a large impact on the course ratings, which is a problem if the course ratings influence decisions on promotions, tenure, and salary increments for the instructors but also demonstrates the potential for the manipulation of course ratings.

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Published

2020-04-03

How to Cite

Koenig, S., Uras, T., & Cohen, L. (2020). Teaching Undergraduate Artificial Intelligence Classes: An Experiment with an Attendance Requirement. Proceedings of the AAAI Conference on Artificial Intelligence, 34(09), 13374-13380. https://doi.org/10.1609/aaai.v34i09.7060

Issue

Section

EAAI Symposium: Full Papers