Akgun, S., Haudek, K. C., Kaldaras, L., & Krajcik, J. (2025). Collaborating with Teachers to Generate ML-Based Feedback: Contextualizing and Developing Meaningful and Relevant Feedback. In NARST Annual Conference. National Harbor, MD: NARST. (Original work published March 2025)

Franovic, C. G.-C., Kaldaras, L., Tang, W., Akgun, S., Krajcik, J., & Haudek, K. C. (2026). Designing and validating three-dimensional, learning-progression-aligned cognitive feedback for AI-generation. In National Association for Research in Science Teaching Annual Conference. Seattle, WA: NARST. (Original work published April 2026)

Kaldaras, L., Haudek, K. C., & Krajcik, J. (2024). Employing automatic analysis tools aligned to learning progressions to assess knowledge application and support learning in STEM. International Journal of STEM Education, 11(1). http://doi.org/10.1186/s40594-024-00516-0 (Original work published November 2024)

Zeng, M.-R., Haudek, K. C., Kaldaras, L., & Krajcik, J. (2026). Exploring object detection approaches to analyze students’ drawn scientific models. Proceedings of the 6th Annual Meeting of the International Society of the Learning Sciences. Irvine, CA: International Society of the Learning Sciences. Retrieved from https://2026.isls.org/docs/ICLS%20Volume%202026.pdf (Original work published June 2026)

Zeng, M.-R., Haudek, K. C., Kaldaras, L., & Krajcik, J. (2026). Exploring object recognition approaches to analyze students’ draw models. In National Association for Research in Science Teaching Annual Conference. Seattle, WA: NARST. (Original work published April 2026)

Li, T., Kaldaras, L., Haudek, K. C., & Krajcik, J. (2025). Feedback on Utilizing Deep Learning AI to Analyze Scientific Models. In NARST Annual Conference. National Harbor, MD: NARST. (Original work published March 2025)

Kaldaras, L., Li, T., Djagba, P., Haudek, K. C., & Krajcik, J. (2025). Learning Progression-Guided AI Evaluation of Scientific Models To Support Diverse Multi-Modal Understanding in NGSS Classroom. In NARST Annual Conference. National Harbor, MD: NARST. (Original work published March 2025)

Kaldaras, L., Franovic, C. G.-C., Tang, W., Li, T., Djagba, P., Krajcik, J., & Haudek, K. C. (2026). Learning Progression-Guided AI Evaluation to Support Feedback on Multimodal Scientific Modeling Tasks. In AERA Annual Conference. Los Angeles, CA: AERA. (Original work published April 2026)

Kaldaras, L., Franovic, C. G.-C., Chu, Y., Tang, J., Krajcik, J., & Haudek, K. C. (2026). Training AI To Produce Guiding and Meaningful Feedback To Support Learning and Foster Knowledge-In-Use. In National Association for Research in Science Teaching Annual Conference. Seattle, WA: NARST. (Original work published April 2026)

Li, T., Haudek, K. C., & Krajcik, J. (2025). Utilizing Deep Learning AI to Analyze Scientific Models: Overcoming Challenges. Journal of Science Education and Technology. http://doi.org/10.1007/s10956-025-10217-0