Comparing face-to-face and online delivery of AI-supported instructional material preparation training for special education teachers

It can be argued that artificial intelligence (AI) has initiated significant transformations in special education, as it has across all fields of education. AI can be used in special education particularly for diagnosis, assessment, individualized instruction, and material development. The aim of this study is to compare the effectiveness of face-to-face and online delivery formats of an AI-supported material development training package designed for special education teachers, and to identify how teachers use these AI- supported tools or the reasons why they choose not to use them. Additionally, the study seeks to examine in depth teachers' reflections on the training package and its impact on their students. This research was designed using an embedded mixed-methods approach. The quantitative component employed a true experimental design based on the Solomon Four-Group model, while the qualitative component was conducted using a phenomenological design. The quantitative and qualitative findings were integrated in accordance with a merging design. The results indicated that AI-supported material development training was effective in both face-to-face and online formats, with no significant difference detected between the two. Qualitative findings revealed themes indicating that special education teachers were satisfied with the training, gained knowledge about AI-supported tools, and used these tools to create instructional materials for their students. Furthermore, one month after the training, teachers continued to use AI-supported tools to prepare various materials for their classrooms and students, and they reported presenting these materials to their learners. Teachers emphasized that students showed interest in the materials developed with AI-supported tools. The study concludes by discussing the combined quantitative and qualitative findings and their implications for students. Recommendations for researchers, practitioners, and policymakers are also provided. Keywords: Artificial intelligence, Special education teachers, Material preparation, Individuals with special needs.