Treffer: Scaffolded Team-Based Computational Modeling and Simulation Projects for Promoting Representational Competence and Regulatory Skills

Title:
Scaffolded Team-Based Computational Modeling and Simulation Projects for Promoting Representational Competence and Regulatory Skills
Language:
English
Source:
International Journal of STEM Education. 2024 11.
Availability:
Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
Peer Reviewed:
Y
Page Count:
33
Publication Date:
2024
Document Type:
Fachzeitschrift Journal Articles<br />Reports - Research
Education Level:
Higher Education
Postsecondary Education
DOI:
10.1186/s40594-024-00494-3
ISSN:
2196-7822
Entry Date:
2024
Accession Number:
EJ1433275
Database:
ERIC

Weitere Informationen

Background: This study posits that scaffolded team-based computational modeling and simulation projects can support model-based learning that can result in evidence of representational competence and regulatory skills. The study involved 116 students from a second-year thermodynamics undergraduate course organized into 24 teams, who worked on three two-week-long team-based computational modeling and simulation projects and reflected upon their experience. Results: Results characterized different levels of engagement with computational model-based learning in the form of problem formulation and model planning, implementation and use of the computational model, evaluation, and interpretation of the outputs of the model, as well as reflection on the process. Results report on students' levels of representational competence as related to the computational model, meaning-making of the underlying code of the computational model, graphical representations generated by the model, and explanations and interpretations of the output representations. Results also described regulatory skills as challenges and strategies related to programming skills, challenges and strategies related to meaning-making skills for understanding and connecting the science to the code and the results, and challenges and strategies related to process management mainly focused on project management skills. Conclusion: Characterizing dimensions of computational model-based reasoning provides insights that showcase students' learning, benefits, and challenges when engaging in team-based computational modeling and simulation projects. This study also contributes to evidence-based scaffolding strategies that can support undergraduate students' engagement in the context of computational modeling and simulation.

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