Jing Huang (黄婧)
Educational Psychology & Research Methodology
I am a Ph.D. candidate in Educational Psychology and Research Methodology at Purdue University, working under the guidance of Professor Hua-Hua Chang. My research focuses on psychometrics, educational measurement, statistical modeling, and large language models.
With a strong background in Statistics from East China Normal University and ongoing doctoral training at Purdue, I specialize in online calibration, computerized adaptive testing (CAT), and process data analysis. My work aims to bridge methodological rigor with practical applications in educational settings.
My research has been recognized and supported by the Ross Fellowship (2023-2027) and the 2025 Psychometric Society Vector Travel Award.
News
| Oct 1, 2025 | Two AERA and one NCME proposals were accepted. Looking forward to seeing you in LA in 2026! |
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| Aug 1, 2025 | I started working as a Graduate Teaching Assistant in the Department of Educational Studies, supporting EDPS 32700: Classroom Assessment. I assist with course activities and instruction under the supervision of Dr. Anne Traynor. |
| Jul 1, 2025 | I received the 2025 Psychometric Society Vector Travel Award for my work on automatic item generation. |
| Aug 12, 2024 | I began my role as a Graduate Research Assistant in the School of Engineering Education (August 12, 2024 - May 31, 2025), focusing on data collection, analysis, and research dissemination under the supervision of Dr. Jason Morphew. |
| Mar 1, 2023 | I was awarded the Purdue University Ross Fellowship, which provides four years of funding, including a stipend and full tuition support. |
Selected Publications
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Adaptive CUSUM Charts for Real-Time Detection of Item Parameter Drift in CD-CATPsychometrika,Under review
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A Cognitive Design System Approach to Enhancing Cognitive Alignment and Difficulty Control in Gen-AI Item GenerationApplied Measurement in Education,Under review
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Two-phase Content-balancing CD-CAT Online Item CalibrationJournal of Educational Measurement, 2025
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The Application of Machine Learning to Educational Process Data Analysis: A Systematic ReviewEducation Sciences, 2025