Abstract
Special education teachers face instructional, documentation, and compliance demands that often impede the fidelity of High-Leverage Practices (HLPs). While HLPs are central to promoting positive academic and behavioral growth for students with disabilities, a significant research-to-practice gap persists because educators lack the time and resources to implement these evidence-based strategies consistently within increasingly complex classrooms. Artificial intelligence (AI) offers emerging opportunities to mitigate systemic burdens by serving as a collaborative partner rather than a replacement for professional judgment. This manuscript examines AI’s potential to enhance HLP implementation across the domains of instruction, data-driven practice, collaboration, and intensive intervention. Drawing upon research on evidence-based practices, inclusive education, and culturally responsive pedagogy, this writing proposes a conceptual framework for the ethical integration of AI in special education. Key considerations regarding ethical use, equity implications, and language accessibility are addressed. Finally, the manuscript provides practical applications and recommendations for in-service educators and teacher preparation programs, concluding with implications for future research and professional development in diverse educational contexts.
Recommended Citation
Porter, K., Grant, V., & Gonzales, D. A. (2026). Artificial Intelligence as a Tool to Enhance High-Leverage Practices in Special Education. The Journal of the Research Association of Minority Professors, 28(2). Retrieved from https://digitalcommons.pvamu.edu/jramp/vol28/iss2/1
Included in
Disability and Equity in Education Commons, Disability Studies Commons, Special Education and Teaching Commons, Teacher Education and Professional Development Commons