معرفی
Dr. Kamal Chawla is an Assistant Professor of Education and Applied Quantitative Methods at the University of Maine, affiliated with the College of Education and Human Development. His research bridges machine learning, meta-analysis, and missing data methodologies to address educational challenges. He focuses on developing robust statistical techniques and applying them to improve K-12 teaching strategies for diverse student needs. Dr. Chawla holds a Ph.D. in Educational Statistics from the University of Delaware, an M.Sc. in Industrial Mathematics from IIT Roorkee, and a B.Sc. (Honors) in Mathematics from the University of Delhi.
- Ph.D., 2024: Educational Statistics & Research Methods, University of Delaware
- M.Sc., 2016: Industrial Mathematics & Informatics, IIT Roorkee
- B.Sc., 2013: Mathematics (Honors), University of Delhi
His research interests include leveraging advanced quantitative methods to enhance educational outcomes through:
- Machine learning for missing data imputation
- Meta-analytic approaches to synthesize educational research
- Data-driven strategies to reduce educational inequities
Recent publications highlight trends in:
- Optimizing imputation techniques for educational datasets
- Deep learning solutions for unbalanced survey data
- Meta-analytic evaluation of worked examples in mathematics instruction
Dr. Chawla teaches courses like Statistical Methods in Education and Educational Data Analysis with R, emphasizing practical applications of quantitative tools. His vision focuses on creating inclusive learning environments through data-informed pedagogy.
