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Artificial Intelligence Applications in Psychometrics: From Scale Development to Response Analysis
Thu, April 24, 9:50 to 11:20am MDT (9:50 to 11:20am MDT), The Colorado Convention Center, Floor: Meeting Room Level, Room 703Session Type: Paper Session
Abstract
This session explores diverse artificial intelligence applications in psychometrics and educational research. Five papers showcase AI-driven approaches including embedding techniques for scale pre-validation, GPT-assisted item creation, bimodal data analysis for cognitive style identification, Large Language Models for coding responses, and Structural Topic Modeling for uncovering latent constructs. These studies illustrate AI's potential to enhance efficiency and accuracy in psychometric research while addressing reliability, validity, and the integration of human expertise with AI capabilities.
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Papers
An Embedding-Based Pre-Validation Tool for Scale Development - Shicong Feng, Peking University; Zhehan Jiang, Peking University
Expansion and Adaptation of a University Belonging Questionnaire Through the Generative Pretrained Transformer - Mingfeng Xue, University of North Carolina - Greensboro; Huaxia Xiong, Beijing Normal University
Research on Intelligent Recognition of Online Learning Cognitive Styles Based on Bimodal Data - Zhan Chen, East China Normal University; Yaofeng Xue, East China Normal University; Yisheng Qiu, East China Normal University
The Three-Body Solution: Evaluating Reliability of Large Language Models for Coding Open-Ended Responses - Bill Altermatt, University of Utah; Rachel Barnett, University of Utah; Jeremy Acree, University of Utah; Andrea K. Rorrer, University of Utah
Uncovering Career Interests From Open-Ended Responses: Integrating Topic Modeling and Large Language Models - Yuxiao Zhang, Purdue University; Tugce Karatas, Purdue University; Nielsen Pereira, Purdue University/Gifted Education Research & Resource Institute; Sarah J. Bright, Purdue University; Hua-Hua Chang, Purdue University