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A Predictive Model of Learning Gains for a Video and Exercise Intensive Learning Environment

Ruipérez-Valiente, José A. and Muñoz-Merino, Pedro J. and Delgado Kloos, Carlos (2015) A Predictive Model of Learning Gains for a Video and Exercise Intensive Learning Environment. In: The 17th International Conference on Artificial Intelligence in Education (AIED 2015), 22-26 June 2015, Madrid, Spain.

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Abstract

This work approaches the prediction of learning gains in an environ- ment with intensive use of exercises and videos, specifically using the Khan Academy platform. We propose a linear regression model which can explain 57.4% of the learning gains variability, with the use of four variables obtained from the low level data generated by the students. We found that two of these variables are related to exercises (the proficient exercises and the average number of attempts in exercises), and one is related to both videos and exercises (the total time spent in both) related to exercises, whereas only one is related to videos.

Item Type: Conference or Workshop Papers (Poster)
Uncontrolled Keywords: Educational data mining, learning analytics, prediction.
Subjects: UNSPECIFIED
Divisions: UNSPECIFIED
Depositing User: Jose Antonio Ruiperez
Date Deposited: 18 Mar 2016 10:34
Last Modified: 20 Jun 2016 09:46
URI: http://eprints.networks.imdea.org/id/eprint/1245

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