Kaiwen Man

KEY RESEARCH PROJECTS

• Developed a multilevel-multigroup joint modeling method to assess pre-knowledge cheating via innovative measures across groups. 
• Created a finite mixture model that jointly analyzes item responses, response times, and visual fixation counts to detect pre-knowledge cheating in unsupervised online assessments.

HIGHLIGHTED PUBLICATIONS

1. Man, K. (2024). Multimodal Data Fusion to Detect Preknowledge Test-Taking Behavior Using Machine Learning. Educational and Psychological Measurement, 84(4), 753-779.
2. Man, K., & Harring, J. R. (2023). Detecting preknowledge cheating via innovative measures: A mixture hierarchical model for jointly modeling item responses, response times, and visual fixation counts. Educational and Psychological Measurement, 83(5), 1059-1080.  
3. *Zhan, P., *Man, K., Wind, S. A., & Malone, J. (2022) Cognitive diagnosis modeling incorporating response times and fixation counts: Providing comprehensive feedback and accurate diagnosis. Journal of Educational and Behavioral Statistics, 47(6), 736-776. 
4. Man, K., Harring, J. R., & Zhan, P. (2022). Bridging models of biometric and psychometric assessment: A three-way joint modelingapproach of item responses, response times and gaze fixation counts. Applied Psychological Measurement, 46(5), 361-381.
5. †Peng, S., Man, K., Cai, Y., & Tu, D. (Accepted).  A Mixture model for random responding behavior in forced‐choice noncognitive assessment: implication and application in organizational research. Organizational Research Methods
6. Man, K., Shumaker, R., Morell, M., & Wang, Y. (2022). Effect of compounded non-normality of residuals in hierarchical linear modeling. Educational and Psychological Measurement. 82(2), 330-355.

PROFESSIONAL ACTIVITIES

Man has served as the principal investigator on multiple federally funded research projects, including collaborations with the Army Research Institute and the Institute of Educational Sciences. He has also contributed to interdisciplinary research, applying his expertise in statistical modeling to address diverse challenges in fields such as civil engineering and linguistics. Additionally, he is the elected Chair and Co-Chair of the AERA Cognition and Assessment SIG (2024-2027) and the NCME Test Security SIGMME.

BIOGRAPHY

Dr. Kaiwen Man is an Associate Professor at the University of Alabama’s College of Education. His research focuses on developing innovative psychometric models and procedures to address learning and testing challenges in technology-enhanced systems, with an emphasis on detecting cheating behaviors using process data (e.g., response times, eye-tracking indicators, keystrokes). He highly values interdisciplinary collaboration, working with researchers and graduate students across various fields. These collaborations have broadened his portfolio, enabling the application of tools such as machine learning, mixed-effects modeling, and longitudinal modeling to measure and evaluate psychological and cognitive factors in diverse research contexts, including civil engineering, special education, early childhood education, and kinesiology.

Dr. Man’s teaching philosophy emphasizes nurturing critical thinking and effective communication of quantitative methodologies. He believes in fostering an inclusive learning environment where each student’s unique potential is recognized and supported. He aims to equip students with the necessary tools to pursue their research effectively while encouraging creativity and practical application of advanced statistical techniques.