Artificial Intelligence Assisted Instructional Design Readiness Scale for Teacher Candidates: Development and Validation

Artificial intelligence technologies reshape instructional design processes not only technically but also pedagogically and ethically. In this context, determining the readiness levels of pre-service teachers for this process is critical for the development of contemporary teacher competencies. The aim of this study is to develop a valid and reliable scale to measure the readiness levels of pre-service teachers towards artificial intelligence-supported instructional design. In this quantitative research design, exploration and confirmatory factor analyses and reliability studies were conducted in line with the scale development process. The first application was conducted with 325 pre-service teachers and the confirmatory application was conducted with a different sample of 256 students. The developed scale consists of 32 items in total and four sub-dimensions: Cognitive Readiness, Affective Readiness, Technological Integration Competence and Perceptual Confidence. The construct validity was proved by exploration and confirmatory factor analyses and Cronbach's Alpha reliability coefficients were quite high in both samples. The findings show that pre-service teachers are highly prepared for artificial intelligence-supported teaching processes. This scale can be considered as a functional tool in restructuring teacher education programs, planning in-service trainings and evaluating teacher competencies.