Alison Cheng

How can Data Science ensure standardized tests are useful, valid and fair? Professor Ying (Alison) Cheng is a psychologist whose research focuses on quantitative methods in educational and psychological measurement research, particularly item response theory (IRT) and cognitive diagnostic modeling. Her research seeks to improve the precision, validity, fairness, and usefulness of large-scale standardized tests such as the GRE and statewide student assessments.

Professor Cheng has published extensively on computerized adaptive testing (CAT), test equity across different ethnicity/gender groups (formally known as differential item functioning or DIF), classification accuracy and consistency with licensure/certification exams, and formative assessment using cognitive diagnostic modeling. Her research seeks to improve the precision, validity, fairness, and usefulness of large-scale standardized tests such as the GRE and statewide student assessments. Professor Cheng’s research complements the other aspects of her work as associate professor in Notre Dame’s Department of Psychology, such as teaching of undergraduate statistics and graduate courses in Item Response Theory, Psychological Measurement, and Test Development. For Professor Cheng, it is extremely exciting and gratifying when research ideas are generated from classroom teaching. Besides scholarly work, Professor Cheng enjoys writing children’s science fiction, and reading it to her daughter.