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The evidence

The research behind ModelIt

ModelIt is built on a teaching approach with more than a decade of peer-reviewed research behind it, including over $4M in NSF funding to develop and study modeling-based science education. That research was conducted using Cell Collective (the research platform that inspired ModelIt, built by the same team), and it consistently shows the same thing: students who build and simulate models learn more, and learn differently, than students who only read about the same ideas.

The findings

What the research shows

Students learn more.

In a study of students using the platform, the treatment group showed an 8% learning gain; the control group showed none.

Booth et al., CBE—Life Sciences Education, 2021

It engages the brain differently.

Using fMRI, researchers found that students who built and ran models showed different brain activity than students who only read about the same systems. Doing the modeling wasn't the same as reading about it.

Clark, Helikar & Dauer, CBE—Life Sciences Education, 2020

It works across the board.

The same study found equitable outcomes, with no gender gap in performance.

Booth et al., 2021

It builds systems thinking.

A computational-modeling lesson improved students' foundational systems-thinking skills and conceptual knowledge in biology.

Bergan-Roller et al., BioScience, 2018

A recent deployment showed large gains.

Forty-two undergraduates who completed our immune-response lesson raised their average test scores from 60.4% to 89.0%, and their confidence in building computational models rose from 31% to 69%.

PreliminaryPreliminary findings, not yet published.

Worldwide adoption

Used in classrooms and labs worldwide

Cell Collective (the research platform that inspired ModelIt) is used by more than 5,500 scientists at over 200 institutions in 75+ countries, ranging from high schools and community colleges to research universities including Carnegie Mellon, UCLA, Caltech, Columbia, Brown, Purdue, and the University of Toronto. The lab also leads international training on this modeling approach for working scientists, including regular invited instruction at the U.K. Wellcome Trust and the European Bioinformatics Institute (EMBL-EBI). ModelIt brings the same approach, purpose-built for K-12.

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Carnegie Mellon
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UCLA
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Caltech
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Columbia
Brown logo
Brown
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Purdue
U of Toronto logo
U of Toronto
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UC Irvine
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San Francisco State
Manchester logo
Manchester
Virginia Tech logo
Virginia Tech
Waterloo logo
Waterloo
West Virginia logo
West Virginia
Tufts logo
Tufts
Georgetown logo
Georgetown
U of Nebraska logo
U of Nebraska
Emory logo
Emory
U Rochester logo
U Rochester
U Delaware logo
U Delaware
UC Merced logo
UC Merced
U of Kent logo
U of Kent
Carnegie Mellon logo
Carnegie Mellon
UCLA logo
UCLA
Caltech logo
Caltech
Columbia logo
Columbia
Brown logo
Brown
Purdue logo
Purdue
U of Toronto logo
U of Toronto
UC Irvine logo
UC Irvine
San Francisco State logo
San Francisco State
Manchester logo
Manchester
Virginia Tech logo
Virginia Tech
Waterloo logo
Waterloo
West Virginia logo
West Virginia
Tufts logo
Tufts
Georgetown logo
Georgetown
U of Nebraska logo
U of Nebraska
Emory logo
Emory
U Rochester logo
U Rochester
U Delaware logo
U Delaware
UC Merced logo
UC Merced
U of Kent logo
U of Kent
Research foundation

Selected publications

Bergan-Roller, H. E., Galt, N. J., Chizinski, C. J., Helikar, T., & Dauer, J. T. (2018). Simulated computational model lesson improves foundational systems thinking skills and conceptual knowledge in biology students. BioScience, 68(8), 612–621.

https://doi.org/10.1093/biosci/biy054

King, G. P., Bergan-Roller, H. E., Galt, N. J., Helikar, T., & Dauer, J. T. (2019). Modelling activities integrating construction and simulation supported explanatory and evaluative reasoning. International Journal of Science Education, 41(13), 1764–1786.

https://doi.org/10.1080/09500693.2019.1640914

Clark, C. A. C., Helikar, T., & Dauer, J. T. (2020). Simulating a computational biological model, rather than reading, elicits changes in brain activity during biological reasoning. CBE—Life Sciences Education, 19(3), ar45.

https://doi.org/10.1187/cbe.19-11-0237

Booth, C. S., Song, C., Howell, M. E., Rasquinha, A., Saska, A., Helikar, R., Sikich, S. M., Couch, B. A., van Dijk, K., Roston, R. L., & Helikar, T. (2021). Teaching metabolism in upper-division undergraduate biochemistry courses using online computational systems and dynamical models improves student performance. CBE—Life Sciences Education, 20(1), ar13.

https://doi.org/10.1187/cbe.20-05-0105

Lucas, L., Helikar, T., & Dauer, J. T. (2022). Revision as an essential step in modeling to support predicting, observing, and explaining cellular respiration system dynamics. International Journal of Science Education, 44(13), 2152–2179.

https://doi.org/10.1080/09500693.2022.2114815

Dauer, J., Dauer, J., Lucas, L., Helikar, T., & Long, T. (2022). Supporting university student learning of complex systems: an example of teaching the interactive processes that constitute photosynthesis. In Fostering Understanding of Complex Systems in Biology Education (pp. 63–82). Springer.

https://doi.org/10.1007/978-3-030-98144-0_4

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