Exploring the Motivation of Livestreamed Users in Learning Computer Programming and Coding

This article discusses the emerging presence of online livestreaming programs for computer coding education. The typologies of motivations from a user-gratification perspective were explored from live coding streaming platforms such as “Twitch.tv” and “LiveEdu.tv”. Categories of motivations were ide...

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Bibliographic Details
Published in:	Electronic journal of e-Learning 2021-01, Vol.19 (5), p.363-375
Main Authors:	Huang, Hong, Li, Yongji
Format:	Article
Language:	eng
Subjects:	Coding Cognitive Processes Computer programming Computer Science Education Computers Content Analysis Education Empirical analysis Independent Study Information retrieval Information Seeking Learning Motivation Outreach Programs Programming Social factors Social integration Social Media Software Synchronous Communication Video Technology
Online Access:	Get full text
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Summary:	This article discusses the emerging presence of online livestreaming programs for computer coding education. The typologies of motivations from a user-gratification perspective were explored from live coding streaming platforms such as “Twitch.tv” and “LiveEdu.tv”. Categories of motivations were identified from the literature. Content analysis was used for analyzing the distribution of motivation categories in “Twitch.tv,” as well as blog posts on “LiveEdu.tv” guided by Gratifications Theory. From the literature, five types of motivations were identified: 1) Cognitive; 2) Affective; 3) Social Integration; 4) Personal Integration; and 5) Tension release. In live coding streaming communities, the content analysis of 256 streams and twenty six discussion posts indicated that the primary motivation is cognitive related information seeking, followed by social integration such as community outreach, and then personal integration such as personal recognition. Through content analysis, the authors found that the audience's psychological state while watching online livestreaming of coding practice is mainly focused on learning and information seeking, emotional connectedness, and social interactions. Based on the findings, an empirical motivation model in live coding streaming was also developed. The findings for researchers and practitioners alike in programming education can apply respective motivation characteristics in programming education.
ISSN:	1479-4403 1479-4403