MoDa: Models and Real-World Data

The MoDa (Modeling + Data) project combines agent-based simulation, domain-specific block-based programming, and data visualization tools to support students’ reasoning about complex environmental phenomena. By building and running simulations and then comparing them to real-world datasets, students can test, validate, and refine their scientific theories.

Intended Audience & Use Case: Curriculum units are designed for middle school science educators; the project is also producing more generalized tools and frameworks for curriculum developers and education researchers.

Project Resources & Platforms

• Concord Consortium MoDa Project Page: Official project research details and principal investigator information.
• CODAP Platform: The Common Online Data Analysis Platform used in MoDa for data visualization.

Associated Publications The design of the original MoDa tool is described in Fuhrmann, T., Rosenbaum, L. F., Eloy, A., Wagh, A., Henrique, B.*, Blikstein, P., & Wilkerson, M. H. (2026). Designing MoDa: A new tool for science learning through data-based computational modeling. International Journal of Child-Computer Interaction, 48, 100819. https://doi.org/10.1016/j.ijcci.2026.100819

The design of the new MoDa tool, which integrates quantitative data analysis support, is described in Wagh, A., Wilkerson, M. H., Eloy, A., Fuhrmann, T., & Bliksteain, P. (2026). Putting the data in MoDa: Integrating agent-based modeling, quantitative data analysis, and teacher responsibity to investigate complex phenomena. Proceedings of the 20th Annual Meeting of the International Society of the Learning Sciences. Irvine, CA, USA.

Findings from our work with MoDa include:

• Wagh, A., Rosenbaum, L. F., Fuhrmann, T., Eloy, A., Blikstein, P., & Wilkerson, M. (2025). Toward Ontological Alignment: Coordinating Student Ideas with the Representational System of a Computational Modeling Unit for Science Learning. Cognition and Instruction, 43(1–2), 1–32. https://doi.org/10.1080/07370008.2024.2427400
• Fuhrmann, T., Rosenbaum, L. F., Wagh, A., Eloy, A., Blikstein, P., & Wilkerson, M. H. (2026). Modality matters: Exploring and capturing students’ mechanistic reasoning during computational modeling in science education. In N. Graulich, M. Haskel-Ittah, & R. Wahyu Bachtiar (Eds.), Exploring mechanistic reasoning in science education: Understanding phenomena (pp. 197–219). Springer Nature Switzerland. https://doi.org/10.1007/978-3-032-10246-1_11
• Fuhrmann, T., Rosenbaum, L., Wagh, A., Eloy, A., Wolf, J., Blikstein, P., & Wilkerson, M. H. (2024). Right but wrong: How students’ mechanistic reasoning and conceptual understandings shift when designing agent-based models using data. Science Education, 109(1), 3-26. https://doi.org/10.1002/sce.21890

The MoDa project is what inspired the Rivulet set of tools, see more here.