Please use this identifier to cite or link to this item:
https://repository.isls.org//handle/1/10282
Title: | How Can Computational Modeling Help Students Shift Their Ideas Towards Scientifically Accurate Explanations? |
Authors: | Fuhrmann, Tamar Wagh, Aditi Rosenbaum, Leah F. Eloy, Adelmo Wilkerson, Michelle Blikstein, Paulo |
Keywords: | Learning Sciences |
Issue Date: | 2023 |
Publisher: | International Society of the Learning Sciences |
Citation: | Fuhrmann, T., Wagh, A., Rosenbaum, L. F., Eloy, A., Wilkerson, M., & Blikstein, P. (2023). How can computational modeling help students shift their ideas towards scientifically accurate explanations?. In Blikstein, P., Van Aalst, J., Kizito, R., & Brennan, K. (Eds.), Proceedings of the 17th International Conference of the Learning Sciences - ICLS 2023 (pp. 441-448). International Society of the Learning Sciences. |
Abstract: | This paper explores how MoDa, an integrated computational modeling and data environment, enabled students to express their ideas about diffusion and shift them toward canonical ideas. Drawing on data from an 8-day unit with two 6th-grade science classes, we analyze students' utterances in presentations, drawings, and written responses to document their diverse ideas about diffusion We present three case studies to illustrate how engaging with computational modeling in MoDa and the unit around it enabled students to shift from non-canonical ideas towards more canonical explanations of diffusion. In particular, we identify three factors that helped in shifting students’ ideas: the availability of code blocks to represent a diverse range of ideas including non-canonical ones, consistent access to video data of the phenomenon, and model presentations to the whole class. The paper illustrates how a computational modeling tool and curriculum can make students' diverse ideas visible and shift them toward canonical explanations. |
Description: | Long Paper |
URI: | https://doi.org/10.22318/icls2023.208036 https://repository.isls.org//handle/1/10282 |
Appears in Collections: | ISLS Annual Meeting 2023 |
Files in This Item:
File | Size | Format | |
---|---|---|---|
ICLS2023_441-448.pdf | 502.58 kB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.