Abstract
The integration of artificial intelligence (AI) into education has expanded mentoring practices toward technology-supported guidance systems. Although prior studies have examined AI acceptance, attitudes toward AI, and AI literacy, limited research has focused on AI-based mentorship as a perceived source of pedagogical and developmental support. This study aimed to develop the Artificial Intelligence Mentorship Perception Scale and provide initial psychometric evidence regarding its use with preservice teachers. A scale development design was employed. The process included construct definition, item pool generation, expert review, pilot testing, exploratory factor analysis (EFA), confirmatory factor analysis (CFA), item discrimination analysis, and reliability testing. The initial pool included 33 items based on mentoring, e-mentoring, AI-supported learning, and teacher education literature. Following expert evaluation and pilot testing, the form was reduced to 18 items. The EFA sample included 233 preservice teachers, and the CFA sample included 240 preservice teachers. EFA suggested a four-factor structure explaining 65.12% of the variance: Pedagogical Planning, Performance Evaluation, Academic Guidance, and Professional Development. During CFA, one item was removed, and the revised 17-item model showed acceptable but not optimal fit. Reliability coefficients ranged from .79 to .91 across subdimensions and .955 for the overall scale. The findings provide preliminary psychometric evidence for the scale within a Turkish preservice teacher sample.
| Keywords: | Artificial Intelligence AI-Based Mentorship Preservice Teachers Scale Development Psychometric Validation |