Exploring the Psychometric Validity of AI-Generated Student Responses: A Study on Virtual Personas' Learning Motivation
This addresses the problem of generating realistic educational data for researchers, though it is incremental as it applies an existing method to a new domain.
The study investigated whether large language models (LLMs) can simulate valid student responses for educational measurement, finding that GPT-4o reproduced the Academic Motivation Scale structure and distinct motivational subgroups in 2000 virtual personas.
This study explores whether large language models (LLMs) can simulate valid student responses for educational measurement. Using GPT -4o, 2000 virtual student personas were generated. Each persona completed the Academic Motivation Scale (AMS). Factor analyses(EFA and CFA) and clustering showed GPT -4o reproduced the AMS structure and distinct motivational subgroups.