Teaching recommender systems at large scale: evaluation and lessons learned from a hybrid MOOC

  • Authors:

  • Joseph A. Konstan;J.D. Walker;D. Christopher Brooks;Keith Brown;Michael D. Ekstrand

  • Affiliations:

  • University of Minnesota, Minneapolis, MN, USA;University of Minnesota, Minneapolis, MN, USA;EDUCAUSE, Louisville, CO, USA;University of Minnesota, Minneapolis, MN, USA;University of Minnesota, Minneapolis, MN, USA

  • Venue:
  • Proceedings of the first ACM conference on Learning @ scale conference
  • Year:
  • 2014

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Abstract

In Fall 2013 we offered an open online Introduction to Recommender Systems through Coursera, while simultaneously offering a for-credit version of the course on-campus using the Coursera platform and a flipped classroom instruction model. As the goal of offering this course was to experiment with this type of instruction, we performed extensive evaluation including surveys of demographics, self-assessed skills, and learning intent; we also designed a knowledge-assessment tool specifically for the subject matter in this course, administering it before and after the course to measure learning. We also tracked students through the course, including separating out students enrolled for credit from those enrolled only for the free, open course. This article reports on our findings.