Factors Influencing the Educational Technology Integration of Robots by Preservice Special Education Teachers for Students with Autism Spectrum Disorder

This study examines the psychological, social, and professional factors that can influence preservice special education teachers’ (PSETs) intentions to integrate educational robots (EDRs) into teaching students with autism spectrum disorder (ASD). Using structural equation modeling (SEM) and the extended technology acceptance model (TAM), the study examines the roles of perceived usefulness (PU), perceived ease of use (PEOU), attitude toward integration robot (ATIR), robot self-efficacy (RSE), job relevance (JOR), social influence (SI), and robot anxiety (RANX). This study addresses a research gap, as it is, to the best of our knowledge, the first conducted in an Arab context. A quantitative research design was adopted. The researcher gathered responses from 595 PSETs through an online survey platform at three public universities in Jordan. The results revealed that PU was the strongest predictor of positive attitudes toward EDR integration, and ATIR significantly affected behavioral intention. SI and JOR had significant effects on both PU and PEOU. RSE affected PEOU but not PU, while RANX negatively affected PU without significantly impacting PEOU. These findings guide decision-makers and institutions on how to effectively support special education teachers (SETs) in integrating robots into teaching students with ASDs.