Please use this identifier to cite or link to this item: https://repository.isls.org//handle/1/6322
Title: Learning Science Through Coding: An Investigation Into the Design of a Domain Specific Modeling Experience
Authors: Anderson, Emma
Wendel, Daniel
Keywords: Design
Issue Date: Jun-2020
Publisher: International Society of the Learning Sciences (ISLS)
Citation: Anderson, E. & Wendel, D. (2020). Learning Science Through Coding: An Investigation Into the Design of a Domain Specific Modeling Experience. In Gresalfi, M. and Horn, I. S. (Eds.), The Interdisciplinarity of the Learning Sciences, 14th International Conference of the Learning Sciences (ICLS) 2020, Volume 3 (pp. 1253-1260). Nashville, Tennessee: International Society of the Learning Sciences.
Abstract: Modeling is a core scientific practice. Today scientists create computer models requiring knowledge and skill in both science and computation. Additionally, computational modeling can provide powerful opportunities for learning. Hence, there is a need within K-12 science education to teach computational modeling. However, there are many barriers to incorporating this practice into K-12 classrooms, including the difficulty of learning how to code. In this paper we present the creation of a domain-specific modeling experience with a “custom block” visual programming language for an agent-based modeling environment for high school biology students. We found that with refined language, which maintained the metaphors and the abstractions vital to the science concepts being taught, students were able to complete a computational model without having been taught how to code. We also found preliminary evidence of students being able to learn science through building a computational model composed of customized code blocks.
URI: https://doi.dx.org/10.22318/icls2020.1253
https://repository.isls.org//handle/1/6322
Appears in Collections:ICLS 2020

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