Title
Learning about Social Learning in MOOCs: From Statistical Analysis to Generative Model.
Abstract
We study user behavior in the courses offered by a major Massive Online Open Course (MOOC) provider during the summer of 2013. Since social learning is a key element of scalable education in MOOCs and is done via online discussion forums, our main focus is in understanding forum activities. Two salient features of MOOC forum activities drive our research: 1. High decline rate: for all courses studied, the volume of discussions in the forum declines continuously throughout the duration of the course. 2. High-volume, noisy discussions: at least 30% of the courses produce new discussion threads at rates that are infeasible for students or teaching staff to read through. Furthermore, a substantial portion of the discussions are not directly course-related. We investigate factors that correlate with the decline of activity in the online discussion forums and find effective strategies to classify threads and rank their relevance. Specifically, we use linear regression models to analyze the time series of the count data for the forum activities and make a number of observations, e.g., the teaching staff's active participation in the discussion increases the discussion volume but does not slow down the decline rate. We then propose a unified generative model for the discussion threads, which allows us both to choose efficient thread classifiers and design an effective algorithm for ranking thread relevance. Our ranking algorithm is further compared against two baseline algorithms, using human evaluation from Amazon Mechanical Turk. The authors on this paper are listed in alphabetical order. For media and press coverage, please refer to us collectively, as "researchers from the EDGE Lab at Princeton University, together with collaborators at Boston University and Microsoft Corporation."
Year
DOI
Venue
2013
10.1109/TLT.2014.2337900
TLT
Keywords
DocType
Volume
Internet,computer aided instruction,educational courses,social sciences computing,statistical analysis,Amazon mechanical turk,MOOC forum,MOOC provider,discussion thread,forum activity count data,generative model,human evaluation,linear regression model,massive online open course provider,online discussion forum,social learning,statistical analysis,teaching staff,thread classifier,thread relevance,user behavior,MOOC,concept learning,data mining,regression,social learning networks
Journal
7
Issue
ISSN
Citations 
4
1939-1382
18
PageRank 
References 
Authors
1.66
10
6
Name
Order
Citations
PageRank
Christopher G. Brinton111815.23
Mung Chiang27303486.32
Shaili Jain327219.55
Henry Lam4414.12
Zhenming Liu541925.35
Felix Ming Fai Wong6878.15