Tuned Models of Peer Assessment in MOOCs — mentioned by jngiam1

Mon, 12 Dec 2016 19:45:31 GMT

From Coursera - we use ML in a few places: 1. Course Recommendations. We use low rank matrix factorization approaches to do recommendations, and are also looking into integrating other information sources (such as your career goals). 2. Search. Results are relevance ranked based on a variety of signals from popularity to learner preferences. 3. Learning. There's a lot of untapped potential here. We have done some research into peer grading de-biasing [1] and worked with folks at Stanford on studying how people learn to code [2]. We recently co-organized a NIPS workshop on ML for Education…

Paper and discussion history. A mention is not an endorsement.

Tuned Models of Peer Assessment in MOOCs · HackerPapers discussions

Tuned Models of Peer Assessment in MOOCs — mentioned by jngiam1