Dr. Hailey Kuang is an Assistant Professor of Measurement and Statistics in the Department of Educational Psychology and Learning Systems at the Florida State University. She received her Ph.D. in Research and Evaluation Methodology in 2023 and an M.S. in Computer Science with a specialization in machine learning in 2021, both from the University of Florida. She also received an M.Ed. in Higher Education from the University of Hong Kong in 2013. Earlier in her career, Dr. Kuang worked as a quantitative research methodologist at the University of Hong Kong from 2014 to 2016. She also served as a research intern for the NAEP program at the American Institute of Research in 2020.

Dr. Kuang specializes in developing and applying psychometric and statistical methods to measure cognitive and psychological traits. Her methodology research seeks to advance computational psychometrics by integrating machine learning techniques, with the goal of ensuring the fair and valid use of test scores. As a psychometrician and methodologist, she also analyzes real-world data across educational, behavioral, and health domains. Dr. Kuang’s research has been published in academic journals, such as Large-scale Assessments in Education, Computers & Education, and Structural Equation Modeling. Her recent research has particularly focused on three main areas:

1. Using deep neural networks to analyze response process data from online assessments.
2. Applying natural language processing and machine learning techniques to refine automatic grading models for open-ended math questions.
3. Personalizing learning content, assessments, and guidance for STEM education through AI.

Additionally, Dr. Kuang collaborates with scholars across various disciplines at FSU, including education, sociology, food science, nursing, and engineering. She has been working with ASSISTments, Virtual Learning Lab, and the Clinical and Translational Science Institute at the University of Florida. She offers methodological consultation for research grants and projects, covering research design, data collection, measurement instrument validation, and program evaluation.

At Florida State University, she teaches graduate-level courses, including Measurement Theory I, Item Response Theory, Machine Learning for Education, Health, and Human Sciences, as well as Basic Descriptive and Inferential Statistics Applications.

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