Date of Award

2025

Document Type

Dissertation

Degree Name

Doctor of Education (EdD)

Department

Education

First Advisor

Dr. Joseph Piro

Second Advisor

Dr. Thomas Troisi

Third Advisor

Dr. Shaireen Rasheed

Abstract

Grounded in the Technology Acceptance Model (TAM), this study examined middle school teachers’ adoption of artificial intelligence (AI) tools, emphasizing how perceptions, instructional support, and integration strategies shape classroom use. The sample comprised 56 teachers across grades 6–8, representing multiple subject areas. Quantitative analyses revealed notable trends by teaching experience and subject specialization. Teachers with 0–5 years of experience reported the highest mean AI use scores, while those with more than 16 years of experience reported the lowest. Subject-specific differences were also observed, with mathematics teachers demonstrating the most favorable perceptions of AI tools and English teachers reporting the least favorable perceptions. Although the ANOVA results did not reveal statistically significant differences across groups, the observed trends suggest meaningful variation in AI adoption across both subject areas and teaching tenure. A multiple regression analysis further indicated that teachers’ Perceptions of AI Tools in General (PAITG), Perceptions of AI Tools on Student Performance (PAISP), and Support for AI Integration (SAIN) were significant predictors of AI Use (AIUN). Complementary qualitative findings reinforced these statistical results, emphasizing the critical roles of professional development, reliable infrastructure, and institutional support in fostering meaningful and sustained AI integration.

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