Cengiz Zopluoglu is an academic expert in educational and behavioral data analysis, specializing in integrating machine learning and artificial intelligence with classical and modern measurement and psychometric theory. His research primarily focuses on item response theory, psychometrics, and latent variable modeling, areas where he has made significant contributions through various publications. Zopluoglu excels in transforming complex educational data into insightful, actionable information. He can speak on the application of advanced statistical methods in educational research and the role of technology in enhancing educational assessments. Zopluoglu's can also comment on how data can effectively improve educational outcomes and assessment strategies.
Cengiz Zopluoglu, College of Education
Associate Professor, Special Education
Practice Areas: Educational Data Science, Educational Measurement, Machine Learning, Artificial Intelligence, Quantitative Methods in Education