The integration of Artificial Intelligence (AI) in education offers potential for inclusive practices aligned with Universal Design for Learning (UDL). However, teachers’ perceptions of AI remain underexplored. This non-experimental, descriptive, and crosssectional study developed and validated a questionnaire to assess teachers’ views on AI in inclusive education. The instrument was constructed through a literature review and expert evaluation using the Aggregated Judgments Technique. Eight experts assessed content validity, and a pilot study was conducted with 55 in-service teachers from public schools in four Italian regions. The instrument demonstrated strong psychometric properties: high internal consistency (α = .90–.96), excellent content validity (V ≥ .90), and acceptable structural adequacy (KMO = .74). Most teachers reported basic digital skills, limited AI use, and minimal formal training in UDL, though they acknowledged AI’s inclusive potential. The validated instrument is reliable and suitable for evaluating teachers’ perceptions of AI as a tool for inclusive education. Findings highlight the need for targeted training and support to enhance AI integration in schools.
Assessing teachers’ perceptions of AI and Universal Design for Learning: design and validation
Ludovico Vespasiani
2025
Abstract
The integration of Artificial Intelligence (AI) in education offers potential for inclusive practices aligned with Universal Design for Learning (UDL). However, teachers’ perceptions of AI remain underexplored. This non-experimental, descriptive, and crosssectional study developed and validated a questionnaire to assess teachers’ views on AI in inclusive education. The instrument was constructed through a literature review and expert evaluation using the Aggregated Judgments Technique. Eight experts assessed content validity, and a pilot study was conducted with 55 in-service teachers from public schools in four Italian regions. The instrument demonstrated strong psychometric properties: high internal consistency (α = .90–.96), excellent content validity (V ≥ .90), and acceptable structural adequacy (KMO = .74). Most teachers reported basic digital skills, limited AI use, and minimal formal training in UDL, though they acknowledged AI’s inclusive potential. The validated instrument is reliable and suitable for evaluating teachers’ perceptions of AI as a tool for inclusive education. Findings highlight the need for targeted training and support to enhance AI integration in schools.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


