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

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

20 Scopus citations

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.

Original languageEnglish (US)
Title of host publicationL@S 2014 - Proceedings of the 1st ACM Conference on Learning at Scale
PublisherAssociation for Computing Machinery
Pages61-70
Number of pages10
DOIs
StatePublished - Jan 1 2014
Event1st ACM Conference on Learning at Scale, L@S 2014 - Atlanta, GA, United States
Duration: Mar 4 2014Mar 5 2014

Other

Other1st ACM Conference on Learning at Scale, L@S 2014
CountryUnited States
CityAtlanta, GA
Period3/4/143/5/14

Keywords

  • Distance learning
  • Evaluation
  • MOOC
  • Open learning

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    Konstan, J. A., Walker, J. D., Brooks, D. C., Brown, K., & Ekstrand, M. D. (2014). Teaching recommender systems at large scale: Evaluation and lessons learned from a hybrid MOOC. In L@S 2014 - Proceedings of the 1st ACM Conference on Learning at Scale (pp. 61-70). Association for Computing Machinery. https://doi.org/10.1145/2556325.2566244