Developing an Educational GenAI Usage Motivation Scale: A Comparative Study of Factor Structures Generated by Artificial Intelligence and Human Experts

Objective This study compares the psychometric properties of scale structures developed by human experts and various generative artificial intelligence (GenAI) models to measure motivation for using GenAI in education.Method Grounded in a theoretical framework, six different item pools were generated by human experts and GenAI prompt bots based on five different language models. Based on the reviews conducted by human experts and GenAI bots, the three forms demonstrating the strongest psychometric performance were selected for the final analysis.Result The confirmatory factor analysis indicated that all three scale structures demonstrated acceptable and good model fit, and high internal consistency and convergent validity. The high correlations between the structures revealed that both human- and AI-generated factors measure similar structures.Conclusions GenAI models can generate psychometrically sound scales; however, human expertise remains essential for ensuring theoretical depth and cultural contextualization. Therefore, hybrid human–AI approaches appear to offer the most robust outcomes.