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Data analysis code for Learning at Scale 2015 paper: Effects of In-Video Quizzes on MOOC Lecture Viewing

Home Page: https://hci.stanford.edu/publications/2016/invideo/invideo-las2016.pdf

Python 0.03% Shell 0.01% Jupyter Notebook 99.97%

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invideo-quizzes-analysis-las2016

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Data analysis code for Learning at Scale 2016 paper: Effects of In-Video Quizzes on MOOC Lecture Viewing

Paper: Learning at Scale 2016

ACM DL

Data analysis code

LaTeX sources for paper

Abstract

Online courses on sites such as Coursera use quizzes embedded inside lecture videos (in-video quizzes) to help learners test their understanding of the video. This paper analyzes how users interact with in-video quizzes, and how in-video quizzes influence users’ lecture viewing behavior. We analyze the viewing logs of users who took the Machine Learning course on Coursera. Users engage heavily with in-video quizzes – 74% of viewers who start watching a video will attempt its corresponding in-video quiz. We observe spikes in seek activity surrounding in-video quizzes, particularly seeks from the in-video quiz to the preceding section. We show that this is likely due to users reviewing the preceding section to help them answer the quiz, as the majority of users who seek backwards from in-video quizzes have not yet submitted a correct answer, but will later attempt the quiz. Some users appear to use quiz-oriented navigation strategies, such as seeking directly from the start of the video to in-video quizzes, or skipping from one quiz to the next. We discuss implications of our findings on the design of lecture-viewing platforms.

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MIT

Author

Geza Kovacs

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