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      Learning about social learning in MOOCs: From statistical analysis to generative model

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          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."

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          What Student Affairs Professionals Need to Know About Student Engagement

          George Kuh (2009)
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            Discovering authorities in question answer communities by using link analysis

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              The Dynamics of Open, Peer-to-Peer Learning: What Factors Influence Participation in the P2P University?

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                Author and article information

                Journal
                07 December 2013
                2013-12-19
                Article
                1312.2159
                9fbb6374-6f21-4180-8872-cb6a0d7827da

                http://arxiv.org/licenses/nonexclusive-distrib/1.0/

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                cs.SI

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