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

L@S 2014 - Proceedings of the 1st ACM Conference on Learning at Scale

Volumn , Issue , 2014, Pages 61-70

  Konstan, Joseph A ^a   Walker, J D ^b   Brooks, D Christopher ^c   Brown, Keith ^b   Ekstrand, Michael D ^a  

^a University of Minnesota   (United States)

^b UNIVERSITY OF MINNESOTA   (United States)

^c EDUCAUSE   (United States)

Author keywords

Distance learning; Evaluation; MOOC; Open learning

Indexed keywords

DISTANCE EDUCATION; ONLINE SYSTEMS; RECOMMENDER SYSTEMS;

CLASSROOM INSTRUCTION; EVALUATION; MOOC; OPEN LEARNING; SUBJECT MATTERS;

TEACHING;

EID: 84899679149     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2556325.2566244     Document Type: Conference Paper

References (3)

1. M.D. Ekstrand, M. Ludwig, J.A. Konstan, and J.T. Riedl. 2011. 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.
2. 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.
3. 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.