Teacher-Mediated Integration of Artificial Intelligence Tools in Special Education: A Phenomenological Study of Inclusive Classroom Practices
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Abstract
Background and Aim: Artificial Intelligence (AI) integration has great potential to improve personalized and inclusive education. In Special Education (SPED), this potential is especially significant for meeting the diverse and individual needs of learners with disabilities. Guided by the Technology Acceptance Model (TAM) and Universal Design for Learning (UDL) principles, this study explored the lived experiences of SPED teachers in using AI tools, focusing on their practical applications, challenges encountered, and the support systems necessary for successful implementation.
Materials and Methods: A qualitative phenomenological design was employed, involving semi-structured in-depth interviews with ten special education teachers. Their accounts of using AI tools in the classroom were collected and transcribed verbatim. The data were then analyzed thematically to identify significant patterns and lived experiences.
Results: Three main themes emerged from the analysis: (1) teacher-mediated integration, where educators used AI tools as extensions of their expertise to support differentiated instruction rather than as autonomous substitutes; (2) ambivalent experiences characterized by both empowerment through time savings and frustration due to inadequate infrastructure, insufficient training, and lack of cultural relevance; and (3) socio-technical and infrastructural barriers that positioned AI implementation as an organizational process requiring systemic support. The findings demonstrate that successful AI integration depends on strong institutional support while preserving teacher professional judgment—a finding consistent with TAM's emphasis on perceived usefulness and UDL's focus on flexible, learner-responsive design.
Conclusion: The study concludes that AI tools have significant potential to promote inclusive education when used as assistive tools mediated by teacher expertise. Their successful and ethical adoption, however, depends on systemic interventions including specialized training, reliable infrastructure, and supportive institutional structures. Rather than replacing teachers, AI serves as a valuable enhancement to educators' capacity to meet diverse learner needs. These findings highlight that AI integration in special education is fundamentally a technological education management issue requiring coordinated organizational support.
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