EDUCATION
| Ph.D. | Educational Psychology | University of Maryland |
| M.S. | Statistics | University of Maryland |
| B.S. | Psychology | Peking University |
AWARDS AND HONORS
| Year | Award |
|---|---|
| 2024 | National Council on Measurement in Education (NCME) Alicia Cascallar Outstanding Paper Award |
| 2023 | America Educational Research Association and the Journal of Educational and Behavioral Statistics Outstanding Reviewer |
| 2022-2023 | Excellence in Academic Advising Faculty Award |
| 2022 | National Council on Measurement in Education (NCME) Brenda H. Loyd Outstanding Dissertation Award |
| Support Program for Advancing Research Collaboration (SPARC) Grant Award | |
| 2017-2018 | Harold Gulliksen Psychometric Research Fellowship (ETS) |
AREAS OF EXPERTISE
Statistics and measurement in education and psychology, focusing on developing new statistical models to quantify test-takers’ behaviors and characteristics in technology-enhanced digital assessments (TEDA)
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.
RESEARCH INTERESTS
Test security, specifically detecting aberrant testing behaviors, including cheating, through multimodal data fusion
Applying advanced statistical techniques like joint modeling and machine learning to various fields
HIGHLIGHTED PUBLICATIONS
- 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.
- Man, K. (2024). Multimodal Data Fusion to Detect Preknowledge Test-Taking Behavior Using Machine Learning. Educational and Psychological Measurement, 84(4), 753-779.
PROFESSIONAL ACTIVITIES
Man has served as the principal investigator on multiple federally funded research projects, including work with the Army Research Institute. He has also been involved in interdisciplinary collaborations, leveraging his expertise in statistical modeling to solve diverse research problems across civil engineering, linguistics, and more.
BIOGRAPHY
Dr. Kaiwen Man is an Assistant Professor at the University of Alabama’s College of Education. His research focuses on advancing psychometric methods to enhance test security and fairness in technology-enhanced digital assessments (TEDA). He specializes in multimodal data fusion, utilizing tools like eye-tracking and response time to detect cheating in computer-based and online exams. His groundbreaking work in educational measurement has earned him national recognition, including the prestigious NCME Alicia Cascallar Research Award. Kaiwen is also dedicated to teaching and mentoring graduate students, guiding them to become independent scholars in statistics and educational measurement. He frequently collaborates on interdisciplinary research and has successfully secured significant external funding for his projects.
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.