Research

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Photo of Kevin Haudek and group; Steve Bennett and Weiwei He; Joe Krajcik

CREATE for STEM Institute teams conduct research that focuses on impactful projects in undergraduate education through Discipline-Based Educational Research (DBER). We design innovative K-16 science curricula and investigate the effects of new teaching methods on student learning, engagement, and community impact, with our work increasingly incorporating artificial intelligence to enhance support for teachers and learners. We are leaders in STEM assessment design and professional development for educators, collaborating with international partners in over a dozen countries.  CREATE fosters new talent, provides seed money for initial work and supports the grant writing process.  Our goal is for CREATE to be a hub for the exchange of information and ideas!

 

 

Publications

2026

2024

Li, T., Adah Miller, E., Simani, M. C., & Krajcik, J. (2024). Adapting scientific modeling practice for promoting elementary students’ productive disciplinary engagement. International Journal of Science Education, 1–35. https://doi.org/10.1080/09500693.2024.2361488

Li, T., Chen, I.-C., Adah Miller, E., Miller, C. S., Schneider, B., & Krajcik, J. (2024). The relationships between elementary students' knowledge-in-use performance and their science achievement. Journal of Research in Science Teaching, 61(2), 358-418. https://doi.org/https://doi.org/10.1002/tea.21900

Nordine, J., Kubsch, M., Fortus, D., Krajcik, J., & Neumann, K. (2024). Middle school students’ use of the energy concept to engage in new learning: What ideas matter? Journal of Research in Science Teaching, 61(9), 2191–2222. https://doi.org/10.1002/tea.21950

Jin, H., Yan, D., & Krajcik, J. (Eds.). (2024). Handbook of research on science learning progressions (1st ed.). Routledge. https://doi.org/10.4324/9781003170785

He, P. Shin, N., Zhai, X. & Krajcik, J. (2024). A design framework for integrating artificial intelligence to support teachers’ timely use of knowledge-in-use assessments in K-12 STEM Classrooms, Zhai, X. & Krajcik, J. Uses of Artificial Intelligence in STEM Education. Oxford University Press, Oxford.

Haudek, K. C., & Zhai, X. (2024). Examining the effect of assessment construct characteristics on machine learning scoring of scientific argumentation. International Journal of Artificial Intelligence in Education. 34, 1482-1509. https://doi.org/10.1007/s40593-023-00385-8

Harris, C. J., Krajcik, J., & Pellegrino, J. W. (2024). Creating and using instructionally supportive assessments in NGSS classrooms. NSTA Press.

Eidin, E., Bielik, T., Touitou, I., Bowers, J., McIntyre, C., Damelin, D., & Krajcik, J. (2024). Thinking in terms of change over time: Opportunities and challenges of using system dynamics models. Journal of Science Education and Technology, 33(1), 1–28. https://doi.org/10.1007/s10956-023-10047-y

De Jong, T., Lazonder, A. W., Chinn, C. A., Fischer, F., Gobert, J., Hmelo-Silver, C. E., Koedinger, K. R., Krajcik, J. S., Kyza, E. A., Linn, M. C., Pedaste, M., Scheiter, K., & Zacharia, Z. C. (2024). Beyond inquiry or direct instruction: Pressing issues for designing impactful science learning opportunities. Educational Research Review, 44. https://doi.org/10.1016/j.edurev.2024.100623