Simmons School Postdoctoral Fellows
Yanjun Pan, Ph.D.
Education
Ph.D., Instructional Systems and Learning Technologies, Florida State University, 2019
M.S., Educational/Instructional Media Design, Florida State University
B.A., English Linguistics, Zhejiang University
Research Interests
Current research interests include game-based learning (GBL), immersive learning, multimodal learning analytics, educational data mining, and participatory learning experience design. More specifically, interests include designing and researching comprehensive learning systems that use learning-oriented mechanics; design-based pedagogy; data-driven learning assessment; and adaptive learning support in PreK-20, particularly in the fields of science, technology, engineering, and mathematics education (STEM). Currently involved in an NSF-funded project: STEM+C.
Representative Publications
Dai, C-P, Ke, F., Pan, Y., & Liu, Y. (2023). Exploring students' learning support use in digital game-based math learning: A mixed-methods approach using machine learning and multi-cases study. Computers & Education. 194, 104698. doi: 10.1016/j.compedu.2022.104698 [SSCI, IF:11.182]
Pan, Y., & Ke, F. (2023). Effects of game-based learning supports on students' math performance and perceived game flow. Educational Technology Research and Development. 71, 459-479. doi: 10.1007/s11423-022-10183-z [SSCI, IF:5.580]
Pan, Y., Ke, F., & Dai, C-P. (2023). Patterns of using multimodal external representations in digital game-based learning. Journal of Educational Computing Research. 60(8), 1918-1941. doi: 10.1177/07356331221087771 [SSCI, IF:4.345]
Dai, C-P., Ke, F., & Pan, Y. (2022). Narrative-supported math problem solving in digital game-based learning. Educational Technology Research and Development. 70, 1261-1281. doi:10.1007/s11423-022-10129-5 [SSCI, IF:5.580]
Pan, Y., Ke, F., & Xu, X. (2022). A systematic review of the role of learning games in fostering mathematics education in K-12 settings. Educational Research Review. 36, 100448. doi: 10.1016/j.edurev.2022.100448 [SSCI, IF:10.207]
Supplementary
Professional Experience
Before coming to ÃÛÌÒ½´as a Post-Doc, worked as a graduate research assistant in a game-based learning project called E-Rebuild that included the design of conceptualization, prototyping, user testing, data gathering, and data analyzing.
Gozde Sirganci, Ph.D.
Education
Ph.D. focused on Educational Measurement and Evaluation, Ankara University, 2019
M.S., Educational Measurement and Evaluation, Izzet Baysal University
Bachelor's in Mathematic Education, Dokuz Eylul University
Research Interests
My research focuses on advanced psychometric models, including mixture IRT and SEM, and their applications in educational and behavioral sciences, with a particular emphasis on differential item functioning (DIF) analysis and measurement invariance in both large- and small-scale assessments. My dissertation examined an extended mixture item response model incorporating a covariate variable. More recently, my work integrates psychometrics with artificial intelligence (AI), including automated item generation (AIG), AI-driven assessment validation, and large language model (LLM) applications in educational testing, with an overarching aim of developing adaptive assessments, detecting item bias, and enhancing fairness and efficiency across diverse learner populations.
Representative Publications
Sirganci, G., Kara, Y., Fong, M., Kamata, A. (2025). Modeling Variational DIF for Different Ability Levels with Moderated Mediation Approach. Paper accepted at the NCME Annual Meeting, Denver, Colorado, April 2025.
Kara Y., Sirganci G., Qiao, X., Kamata A., Sumsong, S. Fong, M. (2025). Exploring Fairness of Next-Generation Items: Differential Item Action Analysis on Process Data. Paper accepted at the NCME Annual Meeting, Denver, Colorado, April 2025.
Sirganci, G., Pan, Y. Mese, C. (2025). Equity in STEM Pathways: Machine Learning for Predicting Underrepresented Students' STEM Major Choices. Paper accepted at the AERA Annual Meeting, Denver, Colorado, April 2025.
Sırgancı G., Sarunya S. & Kamata A. (2024). Artificial Intelligence Approach to Classifying Oral Reading Fluency Performances. Paper presented at the NCME Annual Meeting, Philadelphia, Pennsylvania, April 2024.
Çimke, S., Gürkan, D. Y., & Sırgancı, G. (2023). Determination of the psychometric properties of the digital addiction scale for children. Journal of Pediatric Nursing, 71, 1-5.
Sırgancı, G. (2023). Comparison of GPCMlasso and Alignment Methods in Detecting Differential Item Functioning, International Journal of Eurasian Education and Culture, 8(23), 2270-2299.
Sirganci, G., Uyumaz, G. & Yandi, A. (2020). Measurement Invariance Testing with Alignment Method: Many Groups Comparison. International Journal of Assessment Tools in Education, 7(4), 657-673.
Supplementary
Professional Experience
Served as a research assistant in the Educational Measurement and Evaluation department at Ankara University during PhD. program. Served thereafter as an assistant professor in Educational Measurement and Evaluation at Bozok University.
Additional Information
Enjoys creating music and painting.
Fangli Xia, Ph.D.
Education
Ph.D., Educational Psychology (Learning Sciences), University of Wisconsin – Madison, 2025
M.S., Learning and Developmental Sciences (Learning Sciences), Indiana University Bloomington
B.A., Political Science, East China Normal University, China
Research Interests
My research interest lies at the intersection of embodied cognition, technology-enhanced learning, and mathematics education. I focus on two main areas: (1) investigating how bodily movements shape thinking and learning to better understand the mechanisms of embodied learning; (2) applying these insights to design immersive, technology-supported environments (e.g., motion capture, AR, and VR) that foster meaningful learning in real educational settings. To pursue this work, I use a mixed-methods approach that integrates speech, movement, cognitive performance, and demographic data to examine the multimodal nature of learning. My goal is to advance both theories of learning and practical innovations in education. Currently, I am involved in the VR-based De-escalation Training for Law Enforcement project (PI: Dr. Eric G. Bing) and the NSF Generative AI in STEM Education Project (PI: Dr. Candace Walkington).
Representative Publications
Xia, F., Nathan, M. J., Schenck, K. E., & Swart, M. I. (2025). Action Predictions Facilitate Embodied Geometric Reasoning. Cognitive Science, 49(3), e70055. https://doi.org/10.1111/cogs.70055
Xia, F., Kim, C., Beier, J. P., Swart, M. I., Schenck, K. E., & Nathan, M. J. (2025). Embodied Transfer of Mathematical Ideas Through Gestural Replay. In Proceedings of the 19th International Conference of the Learning Sciences-ICLS 2025, pp. 917-925. International Society of the Learning Sciences.
Kim, C., Swart, M. I., Beier, J. P., Xia, F., Grondin, M. M., Kim, D., & Nathan, M. J. (2025). Doctoral Colloquium—A Comparison of Teachers and Students in Categorizing and Representing Geometric Conjectures Using AR Simulations. Immersive Learning Research-Academic, 168-175. [Best Doctoral Colloquium Paper Award]
Xia, F. & Nathan, M.J. (2024). Imagination and Action in Mathematical Reasoning and Transfer. In Proceedings of the 18th International Society of the Learning Sciences-ISLS 2024, pp. 162-163. International Society of the Learning Sciences.
Xia, F., Schenck, K. E., Swart, M. I., Grondin, M., Kim, D., Kwon, O. H., ... & Nathan, M. J. (2024). How Pedagogical Hints Impact Embodied Geometric Reasoning. In Proceedings of the 18th International Conference of the Learning Sciences-ICLS 2024, pp. 123-130. International Society of the Learning Sciences.
Professional Experience
Before joining ÃÛÌÒ½´as a Postdoctoral Fellow, I worked as a graduate project assistant in the Department of Educational Psychology at the University of Wisconsin–Madison during my PhD program. In this role, I contributed to two Institute of Education Sciences (IES)–funded grants that explored how gestures and actions support mathematical reasoning about geometry through embodied technologies such as 3D motion capture and virtual reality. As part of my doctoral training, I also served for three years as an instructor for a large undergraduate-level course, How People Learn, at UW-Madison.