Book Chapters | CAIRE Research Lab | Washington State University

2026

Eidin, E., Bowers, J., & He, P. (2026). Modeling in the Digital Era: An Overview of Practical Studies on Computerized Model-Based Science Instruction (pp.203-220). In: Leite, L., Dourado, L., Afonso, A.S., Morgado, S., Carvalho, L. (eds) Practical Work in Science Education in the Digital Era. Advances in Technology-Rich Science Education, vol 2. Springer, Cham. https://doi.org/10.1007/978-3-032-13788-3_1.

He, J., Li, T., Xu, Z., Xie, K. (2025). Leveraging Generative AI in Designing and Delivering Individualized Responsive Feedback for Pre-service Teachers in Higher Education. In: Adarkwah, M.A., Amponsah, S., Huang, R., Thomas, M. (eds) Artificial Intelligence and Human Agency in Education: Volume Two. Future Education and Learning Spaces. Springer, Singapore. https://doi.org/10.1007/978-981-96-9251-4_11

He, P., Shin, N. Kaldaras L.,& Krajcik, J. (2024). Integrating artificial intelligence into learning progression-based learning systems to support student knowledge-in-use: Opportunities and challenges (pp. 461-487). In Jin, H., Yan, D., & Krajcik, J. Handbook of Research in Science Learning Progressions. DOI: 10.4324/9781003170785-31.
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 (pp. 350-372). In Zhai, X & Krajcik, J. Uses of Artificial Intelligence in STEM Education. Oxford University Press. DOI: 10.1093/oso/9780198882077.003.0016.
He, P., Shin, N., & Krajcik, J. (2024). Developing three-dimensional learning progressions of energy, interaction, and matter at middle school level: Design-based research (pp. 197-281). In Jin, H., Yan, D., & Krajcik, J. Handbook of Research in Science Learning Progressions. DOI: 10.4324/9781003170785-14.

He, P., Zhai, X., Shin, N., Krajcik, J. (2023). Applying Rasch measurement to assess knowledge-in-use in science education. In: Liu, X., Boone, W.J. (eds) Advances in Applications of Rasch Measurement in Science Education. Contemporary Trends and Issues in Science Education, vol 57. Springer, Cham. https://doi.org/10.1007/978-3-031-28776-3_13.
Li, T., Miller, E. A., & Krajcik, J. S. (2023). Theory into practice: Supporting knowledge-in-use through project-based learning. In G. Bansal & U. Ramnarain (Eds.), Fostering Science Teaching and Learning for the Fourth Industrial Revolution and Beyond (pp. 1-35). IGI Global. https://doi.org/10.4018/978-1-6684-6932-3.ch001.
Miller. E., Li, T., Chen, I., & Codere, S. (2023). Using flexible thinking to assess student sensemaking of phenomena in project-based learning. In R. Tierney., F. Rizvi., K. Ercikan (Eds.).International Encyclopedia of Education (Fourth Edition), (pp. 444-457). Elsevier. https://doi.org/10.1016/B978-0-12-818630-5.13047-7.

Li, T. (2021). Developing deep learning through systems thinking. In Krajcik, J., & Schneider, B (Eds.). Science Education Through Multiple Literacies: Project-based Learning in Elementary School. (pp. 79-94) Cambridge: Harvard Education Press. https://hep.gse.harvard.edu/9781682536629/science-education-through-multiple-literacies/