Paper ID:250655F3
Authos: Ryota Kozakai, Shoichiro Hara and Yuji Watanabe
Title: Learning Tendency Analysis of Scratch Programming Course(Entry Class) for
Upper Elementary School Students Based on Bayesian Item Response Theory
Publisher: Algorithm_Lab.
Conference: ICAITD 2025: The Second International Conference of AI new Technology and open Discussion
Location: Pleasanter Lounge Nakano, Tokyo Japan
Date: 1-4 june 2025
Editor: Kazuo Ohzeki (Algorithm_Lab. Professor Emeritus of Shibaura Institute of Technology, Professor of Emeritus of International Professional University of Technology in Tokyo)
Citation: Proceedings: ICAITD 2025
https://doi.org/10.63211/j.p.25.645303
pages: 17-26
Abstract:
In this study, we analyzed the results of the scoring of program codes created in the Scratch programming course held by Nagoya City University for Upper Elememtary school students who participated on July 15, 2021 (18 students), June 30, 2022 (19 students), and July 6, 2023 (20 students). On the day of the course, each student programmed an entry-level assignment in the Scratch certification textbook provided by the university. The input programs were recorded on Google Drive and shared with the instructor. We analyzed the relationship between correctness and incorrectness of each student's program input on Google Drive using Bayesian Item Response Theory, and confirmed the transition of participants' proficiency levels from year to year, the appropriateness of the questions, and the difficulty level that participants seemed to perceive. From these results, we can confirm the trend of the awareness of Scratch programming in the 2021-2023.
Keywords: Programming Education, Upper Elememtary School Student, Scratch, Bayesian IRT
Category: Full paper
Review process: Committee review
Publication date: July 2nd 2025
First received date: Jan. 31st 2025
Copyright :Author(Full), AlgorithmLab.(First-in-the-world publishing rights granted by the author as the Prceedings of ICAITD 2025)
Licence:Viewer can download and view this review paper, but cannot secondary distribute (redistribute) it. (It is not Creative Commons License, nor MIT Licence) In other words, "Do not distribute" is the License
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