A Qualitative Multi-District Study of the Integration of AI - Khanmigo

• In Event: AERA Roundtable Session Wednesday 9:45 am
  In Roundtable Session: Artifical Intelligence: Opportunities and Ethical Dilemmas for Student Learning & Systems Change

Abstract

This multi-district qualitative study investigates how K–12 educators across eleven diverse school districts integrate Khanmigo, an AI-powered tutor and teaching assistant, into classroom practice. Guided by the Technology Acceptance Model and Diffusion of Innovation Theory, the research examines educator perceptions, professional learning supports, and systemic factors shaping adoption. Findings reveal that teacher-led experimentation, district-level infrastructure, and alignment with instructional needs, such as differentiated instruction and student absenteeism, facilitated ethical and effective integration of the AI in classrooms. Early adopters of the AI tool played key roles in spreading use, while contextual factors influenced adoption speed. The study offers scalable, context-sensitive insights into AI implementation that center educator agency and address real-world classroom challenges.

Authors

• Dominic Siami Egure, Oklahoma State University

• Katherine A. Curry, Oklahoma State University

• Jentre J. Olsen, Oklahoma State University

• Daniel Hamlin, University of Oklahoma