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Erschienen in: Journal of Science Education and Technology 4/2022

31.05.2022

Supporting Three-dimensional Learning on Ecosystems Using an Agent-Based Computer Model

verfasst von: Lin Xiang, Sagan Goodpaster, April Mitchell

Erschienen in: Journal of Science Education and Technology | Ausgabe 4/2022

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Abstract

The Next Generation Science Standards call for engaging K–12 students in three-dimensional learning, in which students make sense of phenomena or solve problems by simultaneously using science and engineering practices (SEPs), crosscutting concepts (CCCs), and disciplinary core ideas (DCIs). Decades of education research suggest agent-based computer models (ABMs) have the potential to support all three dimensions. However, most existing studies focus on using ABMs to support one or two dimensions (i.e., DCIs and/or SEPs). This article presents a mixed-methods study in which 63 sixth-grade students engaged in ABM-supported, three-dimensional learning to explore the causes of severe bark beetle outbreaks in forest ecosystems. Data collected from pre- and post-assessments, students’ written explanations for the outbreak phenomenon, and videos of classroom instruction suggest the ABM of bark beetle outbreaks supported students in using all three dimensions of science learning to make sense of the target phenomenon. Our results show that the ABM-supported unit significantly improved students’ understanding of ecosystem concepts. The largest improvement was observed among previously low-performing students. Furthermore, students engaged in sophisticated science practices, reasoning with the computer-generated data to develop an evidence-based explanation for the target phenomenon. The ABM helped students to make sense of the target phenomenon using five different CCCs. Importantly, our results also show that ABMs enabled students as young as sixth grade to predict system outcomes and better understand the nature of models in science. This study contributes to the field by bridging ABM education literature with three-dimensional science teaching and learning.

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Metadaten
Titel
Supporting Three-dimensional Learning on Ecosystems Using an Agent-Based Computer Model
verfasst von
Lin Xiang
Sagan Goodpaster
April Mitchell
Publikationsdatum
31.05.2022
Verlag
Springer Netherlands
Erschienen in
Journal of Science Education and Technology / Ausgabe 4/2022
Print ISSN: 1059-0145
Elektronische ISSN: 1573-1839
DOI
https://doi.org/10.1007/s10956-022-09968-x

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