A Crowdsourcing Approach to Collecting Tutorial Videos -- Toward Personalized Learning-at-Scale
A Crowdsourcing Approach to Collecting Tutorial Videos -- Toward Personalized Learning-at-Scale
复制标题
收集教程视频的众包方法——实现大规模个性化学习
DOI：
10.1145/3051457.3053973
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发表时间：
2016
期刊：
影响因子：
--
通讯作者：
M. Seltzer
中科院分区：
文献类型：
--
作者：
J. Whitehill;M. Seltzer
我们调查了从网络上的普通人那里众包完整的教程视频的可行性，这些视频是关于如何解决与数学相关的数学问题的。这种有效收集教程视频和其他学习资源的方法（learnersourcing的一种形式[9，11]）可能有助于实现个性化的大规模学习，学生可以获得特定的学习资源-从大量和多样化的集合中提取-根据他们的个人和随时间变化的需求量身定制。我们的研究结果表明，（1）大约100个视频-其中超过80%在数学上完全正确-每周可以以5美元/视频的价格众包;（2）与观看视频相关的平均学习收益（后测减去前测分数）是统计的。sig.高于对照视频（0.105对0.045）;以及（3）观看最佳测试的众包视频的平均学习增益（0.1416）与观看流行的Khan Academy视频的学习增益（0.1506）相当。
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 [9, 11]) 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 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 (3) 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.