Understanding Video Lectures in a Flipped Classroom SettingPublic
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This project is designed to analyze how flipping a classroom from a traditional setting where the professor and students are in a room together to a setting where the students watch previously filmed lectures. I parsed words from a file that contains the transcription of the closed captioning. There were two sets of files: one for Coursera videos and one for YouTube videos. The Porter Stemming Algorithm was then used to create a language data model of the parsed words. The purpose of parsing these files was to count the number of occurrences of certain technical words and see how often they are missed. Once the files were parsed and the results were analyzed, they showed that the Coursera transcription is a better tool for online courses.
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