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Exploring the influence of favorite projects on programming skill improvement: analyzing the longitudinal dataset of 5 years of public activity on scratch social media

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Abstract

Scratch is widely used as an introductory educational tool for computer programming. However, little is known about how the action of adding favorite projects on Scratch social media influences programming skill improvement. On Scratch social media, learners select personally intriguing projects to view and learn from. Favorite projects both motivate users to participate on social media and serve as scaffolding material for learners. In this study, we analyzed a dataset of 50,786 users from 5 years of longitudinal activities on Scratch social media using the Zones of Proximal Flow theory. To understand how favorite projects influence learners, we compared the frequency of social media use and programming skill improvement between users who did and did not add favorite projects, and we found a significant difference in programming skill improvement. Among users with favorite projects, there is a proximal difference of two to five Dr. Scratch scores of the favorite project above users’ capability level, which maximizes the frequency of social media use and programming skill improvement.

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Acknowledgements

We thank Prof. Xiangdong Chen and Prof. A.Y.M. Atiquil Islam(East China Normal University) for enlightening discussions. We thank Prof. Yonghe Wu (East China Normal University) for sharing the analysis methods on big data. We thank Prof. Andres Monroy-Hernandez (Princeton) for sharing data on Scratch social media and for the warm and detailed reply to our follow-up questions.

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EL: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Writing—original draft. JL: Data curation, Methodology, Writing—review & editing. JZ: Conceptualization, Supervision—review & editing.

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Correspondence to Jiping Zhang.

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Lian, E., Lin, J. & Zhang, J. Exploring the influence of favorite projects on programming skill improvement: analyzing the longitudinal dataset of 5 years of public activity on scratch social media. Education Tech Research Dev 71, 295–312 (2023). https://doi.org/10.1007/s11423-022-10157-1

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