Assigning Videos to Textbooks at Appropriate Granularity

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, and to further augment the educational experience by enriching them with relevant supplementary materials. Given a candidate set of relevant educational videos for augmenting an electronic textbook, how do we assign the videos at the appropriate granularity (a collection of logical units in the book)? 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 inACM Conference on Learning at Scale (L@S)
PublisherACM
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