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Apples to Apples: Differences in Viewer Retention When Longer Content is Chopped into Smaller Bites

Published: 24 June 2019 Publication History

Abstract

Numerous studies have concluded that viewer retention decreases as video length increases. However, we are not aware of any prior work in which a set of longer MOOC (Massive Open Online Course) videos are compared with the same content split into multiple shorter videos. We are fortunate to be in the unique position to have two separate MOOCs that teach essentially the same content using two different platforms (the LEGO Mindstorms NXT and EV3 robots). In our NXT MOOC, videos are quite long, with over 20% of the videos having a running time of more than ten minutes. The EV3 MOOC has very similar content; EV3 MOOC scripts were written by modifying NXT scripts as appropriate. However, many of the EV3 lessons were split into two or three shorter videos in place of a single longer one. NXT videos that are very close in terms of both content and duration to EV3 videos have similar average percentage viewed. This suggests that the two populations watching the videos are similar and that we have a promising setup for analyzing the relationship between NXT lessons whose EV3 counterparts consist of multiple shorter videos. We present an analysis of our data, along with various interpretations some, but not all, of which support the "shorter videos are better" hypothesis.

References

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cover image ACM Other conferences
L@S '19: Proceedings of the Sixth (2019) ACM Conference on Learning @ Scale
June 2019
386 pages
ISBN:9781450368049
DOI:10.1145/3330430
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 24 June 2019

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Author Tags

  1. MOOC
  2. Video analysis
  3. in-video dropout
  4. online education
  5. viewer engagement

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  • Research
  • Refereed limited

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L@S '19

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L@S '19 Paper Acceptance Rate 24 of 70 submissions, 34%;
Overall Acceptance Rate 117 of 440 submissions, 27%

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