張華華 教授
Dr. Hua-hua Chang

現職：美國普渡大學教育學系 教授

學歷：美國伊利諾伊大學香檳分校(UIUC) 數理統計系 哲學博士

E-mail：chang606@purdue.edu

TEL：(765) 494-9625

專長：Educational Psychology and Research Methodology, Educational Studies

經歷：美國普渡大學教育學系 教授

美國伊利諾伊大學香檳分校(UIUC)數理統計哲學 教授

美國國家醫學考試中心(NBME)高級心理測驗專家和電腦化考試技術研究所 主任

美國教育考試服務中心(ETS) 研究員

德克薩斯大學奧斯丁分校 終身副教授

香港中文大學 副教授

詳情請參閱美國普渡大學教育學系網站

https://education.purdue.edu/about/directory/hua-hua-chang/

研究成果

1. Huang, J., Xin, Y., & Chang, H-H. (2025). The application of machine learning to educational process data analysis: A systematic review. Education Sciences, 15(7), 888. https://doi.org/10.3390/educsci15070888
2. Zhang, Y., Pereira, N., Arthur, D., Castillo-Hermosilla, H., Ozen, Z., & Chang, H-H. (2025). Using topic modeling in gifted education research: Drawing insights from open-ended survey responses. Gifted Child Quarterly.
3. Le, V., Nissen, J., Tang, X., Zhang, Y., Mehrabi, A., Morphew, J., Chang, H-H., & Dusen, B (2025). Applying cognitive diagnostic models to mechanical concept inventories. Physical Review Physics Education Research, 21, 010103. https://doi.org/10.1103/PhysRevPhysEducRes.21.010103
4. Wang, X., Yukiko, M., & Chang, H. H. (2024). Development and Techniques in Learner Model in Adaptive e-Learning System: A Systematic Review. Computers & Education, 105184.
5. Zhu, Z. & Chang, H-H. (2024). Using MLP-F in three different aberrant behaviors in education. Journal of Educational and Behavioral Statistics.
6. Le, V., Van Dusen, B., Nissen, J. M., Tang, X., Zhang, Y., Chang, H. H., & Morphew, J. W. (2024). Mechanics Cognitive Diagnostic: Mathematics skills tested in introductory physics courses. 2024 Physics Education Research Conference Proceedings, 243–249. https://doi.org/10.1119/perc.2024.pr.Le
7. Chang, H-H. (2024). Harnessing AI for educational measurement: standards and emerging frontiers. Journal of Educational and Behavioral Statistics. In Press.
8. Tang, X., Zheng, Y., Wu, T., Hau, KT, & Chang, H-H. (2024). Utilizing response times for item selection in on-the-fly multistage adaptive testing. Journal of Educational Measurement. DOI: 10.1111/jedm.12403
9. Arthur, D. & Chang, H.H. (2023) DINA-BAG: A Bagging Algorithm for DINA Model Parameter Estimation in Small Samples. Journal of Educational and Behavioral Statistics. DOI: 10.3102/ 10769986231188442
10. Li, X., Xu, H., Zhang, J., & Chang H-H. (2022). Deep reinforcement learning for adaptive learning system. Journal of Educational and Behavioral Statistics. DOI: 10.3102/10769986221129847.
11. Du, Y., Zhang. S., & Chang, H-H. (2022). Compromised item detection: A Bayesian change-point perspective. British Journal of Mathematical and Statistical Psychology. DOI: 10.1111/ bmsp.12286
12. Zhu, Z., Arthur, D., & Chang, H-H. (2022). A new person‐fit method based on machine learning in CDM. British Journal of Mathematical and Statistical Psychology. doi.org/10.1111/bmsp.12270.
13. Wu, X., Wu, R., Zhang, Y., Arthur, & Chang, H-H. (2021). Research on construction method of learning paths and learning progressions based on cognitive diagnostic assessment. Assessment in Education: Principles, Policy & Practice. DOI:10.1080/0969594X.2021.1978387.
14. Chang, H-H., Wang, C., & Zhang, S. (2021). Statistical applications in educational measurement. Annual Review of Statistics and Its Application. doi.org/10.1146/annurev-statistics-042720-104044
15. Li, X., Xu, H., Zhang, J., & Chang, H-H. (2021). Optimal hierarchical learning path design with reinforcement learning. Applied Psychological measurement. DOI: 10.1177/0146621620947171
16. Wu, X., Chang, H-H. (2021) A comparative study on cognitive diagnostic assessment of mathematical key competencies and learning trajectories — PISA data analysis based on 19, 454 students from 8 countries. Current Psychology. DOI:10.1007/s12144—020-01230-0