Document Type
Conference Proceeding
Publication Date
1-1-2023
Journal / Book Title
Proceedings of International Conference of the Learning Sciences ICLS
Abstract
Integrating agent-based models (ABMs) has been a popular approach for teaching emergent science concepts. However, students continue to find it difficult to explain the emergent process of natural selection. In this study, we employ an ontological framework-the Pattern, Agents, Interactions, Relations, and Causality (PAIR-C)-to guide the design of the ABM simulation module. This study examines the effects of the PAIR-C ABM module versus the Regular ABM module on fostering students' understanding of natural selection. Drawing on pre-posttest data, we found that students in the Intervention group had a better causal understanding when explaining natural selection than the Control group. This paper sheds light on applying an innovative framework to designing effective agent-based simulation modules to teach emergent science concepts.
DOI
10.22318/icls2023.326470
MSU Digital Commons Citation
Su, Man; Chi, Michelene T.H.; Ha, Jesse; and Xin, Yue, "Investigating the Efficacy of an Ontological Framework for Teaching Natural Selection Using Agent-Based Simulations" (2023). Department of Teaching and Learning Scholarship and Creative Works. 205.
https://digitalcommons.montclair.edu/teaching-learning-facpubs/205
Rights
© 2023 International Society of the Learning Sciences. This article is being shared under license by the publisher.
Published Citation
Su, M., H., M. T., Ha, J., & Xin, Y. (2023). Investigating the efficacy of an ontological framework for teaching natural selection using agent-based simulations. In Blikstein, P., Van Aalst, J., Kizito, R., & Brennan, K. (Eds.), Proceedings of the 17th International Conference of the Learning Sciences - ICLS 2023 (pp. 106-113). International Society of the Learning Sciences.