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Turn on,tune in,drop out:Anticipating student dropouts in massive open online courses. Yang D,Sinha T,Adamson D,et al. Proceedings of the 2013 NIPS Data-Driven Education Workshop . 2013
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Peer assessment in MOOCs using preference learning via matrix factorization[C/OL]. Diez J,Luaces O,Betanzos A A,et al. Neural Information Processing Systems Workshop on Data Driven Education . 2013
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A case for ordinal peer evaluation in MOOCs[C/OL]. Shah N B,Bradley J K,Parekh A,et al. Neural Information Processing Systems Workshop on Data Driven Education . 2013
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Using data mining on student behavior and cognitive style data for improving e-learning systems: a case study[J] . Milos Jovanovic,Milan Vukicevic,Milos Milovanovic,Miroslav Minovic.  International Journal of Computational Intelligence Systems . 2012 (3)
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Evaluating geographic data in MOOCs[C/OL]. Nesterko S,Dotsenko S,Hu Q,et al. Neural Information Processing Systems Workshop on Data Driven Education . 2013
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Deconstructing disengagement:analyzing learner subpopulations in massive open online courses. Kizilcec,R.F,Piech,C,Schneider,E. Proceedings of the third international conference on learning analytics and knowledge . 2013
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"Your click decides your fate":Leveraging clickstream patterns from MOOC videos to infer students’’information processing&attrition behavior. SINHA T. .
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Identifying latent study habits by mining learner behavior patterns in massive open online courses. WEN M,ROSE C P. Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management . 2014
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A case study of learning action and emotion from a perspective of learning analytics. ZHU H,ZHANG X,WANG X,et al. Proceedings of the 17th International Conference on Computational Science and Engineering . 2014
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Predicting student retention in massive open online courses using hidden Markov models. BALAKRISHNAN G,COETZEE D. . 2013