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Characterizing Integrated Learning of Disciplinary Core Ideas and Science Practices in a Computational Thinking (CT)–Integrated Biology Curriculum

  • 23-08-2025
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Abstract

This article delves into the integration of computational thinking (CT) with biology education, specifically focusing on how students learn about natural selection through a CT-integrated curriculum. The study employs Epistemic Network Analysis (ENA) to visualize and analyze students' epistemic connections, which are the co-occurrences of specific science practices and disciplinary ideas. The research investigates how these connections change over time as students engage with a computational model designed as an Emergent Systems Microworld (ESM). The findings reveal that students' engagement with science practices and disciplinary ideas becomes more refined and sophisticated as they progress through the curriculum. The article also highlights the importance of iterative participation in refining both practices and ideas. Additionally, it discusses the implications for curriculum design and classroom instruction, suggesting that access to aggregate and individual student networks can help teachers modify lessons to enhance participation in specific practices and ideas. The study concludes by outlining limitations and future directions, including the potential to incorporate Cross Cutting Concepts (CCCs) into the analytical approach to study three-dimensional learning as advocated by the Next Generation Science Standards (NGSS).

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Title
Characterizing Integrated Learning of Disciplinary Core Ideas and Science Practices in a Computational Thinking (CT)–Integrated Biology Curriculum
Authors
Sugat Dabholkar
Golnaz Arastoopour Irgens
Uri Wilensky
Publication date
23-08-2025
Publisher
Springer Netherlands
Published in
Journal of Science Education and Technology / Issue 5/2025
Print ISSN: 1059-0145
Electronic ISSN: 1573-1839
DOI
https://doi.org/10.1007/s10956-025-10242-z
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