Please use this identifier to cite or link to this item: https://repository.isls.org//handle/1/7518
Title: Knowledge Creation Analytics for Jigsaw Instruction: Temporal Socio-Semantic Network Analysis
Authors: Ohsaki, Ayano
Oshima, Jun
Keywords: Learning Sciences
Issue Date: Jun-2021
Publisher: International Society of the Learning Sciences
Citation: Ohsaki, A. & Oshima, J. (2021). Knowledge Creation Analytics for Jigsaw Instruction: Temporal Socio-Semantic Network Analysis. In de Vries, E., Hod, Y., & Ahn, J. (Eds.), Proceedings of the 15th International Conference of the Learning Sciences - ICLS 2021. (pp. 537-540). Bochum, Germany: International Society of the Learning Sciences.
Abstract: This study aims to gain insight into how to design lesson plans with jigsaw instruction to promote knowledge creation. Collaborative learning has been discussed as a method for improving students’ learning. However, little research on jigsaw instruction analyzed from the knowledge creation perspective has been conducted. Previous research has resulted in the development of the new temporal socio-semantic network analytics (SSNA) to emphasize the visualization of ideas changing during the knowledge creation process. Therefore, we conducted temporal analysis on students’ learning of a more complex problem through jigsaw instruction than previous studies to examine the differences between high- and low-learning-outcome groups. The results of three investigations suggest that designing lessons such that they prompt students to engage in generative tasks can contribute to learning as knowledge creation.
URI: https://doi.dx.org/10.22318/icls2021.537
https://repository.isls.org//handle/1/7518
Appears in Collections:ISLS Annual Meeting 2021

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