Joseph A. Konstan
J.D. Walker
Michael D. Ekstrand
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.
- M.D. Ekstrand, M. Ludwig, J.A. Konstan, and J.T. Riedl. 201 Rethinking the recommender research ecosystem: reproducibility, openness, and LensKit. In Proceedings of the Fifth ACM Conference on Recommender Systems (RecSys '11). ACM, New York, NY, USA, 133--140. Google Scholar
Digital Library
- D.A. McConnell, D.N. Steer, K.D. Owens, C. Knight, 2005. How students think: Implications for learning in introductory geoscience courses. Journal of Geoscience Education, Vol. 53, No. 4, 462--470.Google ScholarCross Ref
- B. Means, Y. Toyama, R. Murphy, M. Bakia, and K. Jones, 2010. Evaluation of evidence-based practices in online learning: A meta-analysis and review of online learning studies. Washington, DC: Center for Technology in Learning, U.S. Department of Education.Google Scholar
Index Terms
- Teaching recommender systems at large scale: evaluation and lessons learned from a hybrid MOOC
Recommendations
Teaching Recommender Systems at Large Scale: Evaluation and Lessons Learned from a Hybrid MOOC
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