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Assigning Educational Videos at Appropriate Locations in Textbooks

Marios Kokkodis, Anitha Kannan, and Krishnaram Kenthapadi

Abstract

The emergence of tablet devices, cloud computing, and abundant online multimedia content presents new opportunities to transform traditional paper-based textbooks into tablet-based electronic textbooks. Towards this goal, techniques have been proposed to automatically augment textbook sections with relevant web content such as online educational videos. However, a highly relevant video can be created at a granularity that may not mimic the organization of the textbook. We focus on the video assignment problem: Given a candidate set of relevant educational videos for augmenting an electronic textbook, how do we assign the videos at appropriate locations in the textbook? We propose a rigorous formulation of the video assignment problem and present an algorithm for assigning each video to the optimum subset of logical units. Our experimental evaluation using a diverse collection of educational videos relevant to multiple chapters in a textbook demonstrates the efficacy of the proposed techniques for inferring the granularity at which a relevant video should be assigned.

Details

Publication typeInproceedings
Published inInternational Conference on Educational Data Mining (EDM)
PublisherInternational Educational Data Mining Society

Previous versions

Marios Kokkodis, Anitha Kannan, and Krishnaram Kenthapadi. Assigning Videos to Textbooks at Appropriate Granularity, ACM, March 2014.

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