Marios Kokkodis, Anitha Kannan, and Krishnaram Kenthapadi
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. The use of multimedia content such as educational videos along with textual content has been shown to improve learning outcomes. While such videos are becoming increasingly available, even 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. We also show that our objective function exhibits submodularity and hence admits an efficient greedy algorithm with provable quality guarantees, when the number of logical units is large. 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.
© Microsoft Research
Marios Kokkodis, Anitha Kannan, and Krishnaram Kenthapadi. Assigning Educational Videos at Appropriate Locations in Textbooks, International Educational Data Mining Society, July 2014.
Marios Kokkodis, Anitha Kannan, and Krishnaram Kenthapadi. Assigning Videos to Textbooks at Appropriate Granularity, ACM, March 2014.