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Register a new userA Crowdsourcing Approach To Collecting Tutorial Videos -- Toward Personalized Learning-at-Scale
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Added by
Jacob Whitehill
Publication date
2016
fields
Informatics Engineering
and research's language is
English
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We investigated the feasibility of crowdsourcing full-fledged tutorial videos from ordinary people on the Web on how to solve math problems related to logarithms. This kind of approach (a form of learnersourcing) to efficiently collecting tutorial videos and other learning resources could be useful for realizing personalized learning-at-scale, whereby students receive specific learning resources -- drawn from a large and diverse set -- that are tailored to their individual and time-varying needs. Results of our study, in which we collected 399 videos from 66 unique teachers on Mechanical Turk, suggest that (1) approximately 100 videos -- over $80%$ of which are mathematically fully correct -- can be crowdsourced per week for $5/video; (2) the crowdsourced videos exhibit significant diversity in terms of language style, presentation media, and pedagogical approach; (3) the average learning gains (posttest minus pretest score) associated with watching the videos was stat.~sig.~higher than for a control video ($0.105$ versus $0.045$); and (4) the average learning gains ($0.1416$) from watching the best tested crowdsourced videos was comparable to the learning gains ($0.1506$) from watching a popular Khan Academy video on logarithms.
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In this paper we propose applying the crowdsourcing approach to a software platform that uses a modern and state-of-the-art 3D game engine. This platform could facilitate the generation and manipulation of interactive 3D environments by a community of users producing different content such as cultural heritage, scientific virtual labs, games, novel art forms and virtual museums.
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