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Article

Automatic Judgement of Online Video Watching: I Know Whether or Not You Watched

by 1, 1,* and 2,*
1
Department of Computer Science and Engineering, Korea University, Seoul 02841, Korea
2
Division of Computer Engineering, Hanshin University, Osan 18101, Korea
*
Authors to whom correspondence should be addressed.
Mathematics 2020, 8(10), 1827; https://doi.org/10.3390/math8101827
Received: 23 September 2020 / Revised: 13 October 2020 / Accepted: 14 October 2020 / Published: 18 October 2020
(This article belongs to the Special Issue Artificial Intelligence in Education)
Videos have long been viewed through the free choice of customers, but in some cases currently, watching them is absolutely required, for example, in institutions, companies, and education, even if the viewers prefer otherwise. In such cases, the video provider wants to determine whether the viewer has honestly been watching, but the current video viewing judging system has many loopholes; thus, it is hard to distinguish between honest viewers and false viewers. Time interval different answer popup quiz (TIDAPQ) was developed to judge honest watching. In this study, TIDAPQ randomly inserts specially developed popup quizzes in the video. Viewers must solve time interval pass (RESULT 1) and individually different correct answers (RESULT 2) while they watch. Then, using these two factors, TIDAPQ immediately performs a comprehensive judgement on whether the viewer honestly watched the video. To measure the performance of TIDAPQ, 100 experimental subjects were recruited to participate in the model verification experiment. The judgement performance on normal watching was 93.31%, and the judgement performance on unusual watching was 85.71%. We hope this study will be useful in many areas where watching judgements are needed. View Full-Text
Keywords: video; watching; judgement; viewer; popup quiz; video learning; video advertising; flipped learning; online class; blended learning video; watching; judgement; viewer; popup quiz; video learning; video advertising; flipped learning; online class; blended learning
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MDPI and ACS Style

Yi, E.; Lim, H.; Jo, J. Automatic Judgement of Online Video Watching: I Know Whether or Not You Watched. Mathematics 2020, 8, 1827. https://doi.org/10.3390/math8101827

AMA Style

Yi E, Lim H, Jo J. Automatic Judgement of Online Video Watching: I Know Whether or Not You Watched. Mathematics. 2020; 8(10):1827. https://doi.org/10.3390/math8101827

Chicago/Turabian Style

Yi, Eunseon, Heuiseok Lim, and Jaechoon Jo. 2020. "Automatic Judgement of Online Video Watching: I Know Whether or Not You Watched" Mathematics 8, no. 10: 1827. https://doi.org/10.3390/math8101827

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