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Artificial Intelligence in K-12 Education: An Investigation of Educators’ Stages of Concern, Perception, and Adoption


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dc.contributor.advisorPendola, Andrew
dc.contributor.authorWilliams, Glory
dc.date.accessioned2026-08-17T20:21:47Z
dc.date.available2026-08-17T20:21:47Z
dc.date.issued2026-08-17
dc.identifier.urihttps://etd.auburn.edu/handle/10415/10648
dc.description.abstractGenerative artificial intelligence is transforming K-12 education, creating new advantages and significant challenges for educators. Guided by the Concerns-Based Adoption Model (CBAM), this quantitative study examined K-12 educators’ stages of concern regarding AI integration in education; differences in concerns by educator characteristics; the relationships among the stages of concern, perceptions of AI benefits and challenges in education, and adoption intentions. Participants included certified educators from a single public school district in the western United States who completed an adapted version of the Stages of Concern Questionnaire (SoCQ), along with additional survey items on demographics, AI tool use, and two open-ended questions. Quantitative data were analyzed using the SoCQ manual (George et al., 2006), descriptive statistics, Pearson correlations, independent-samples t tests, and one-way analyses of variance. Qualitative responses were analyzed using content analysis. Results indicated that most educators remained in the early stages of concern. AI experience showed stronger relationships with stages of concern than traditional demographics. Educators who reported being in the advanced stages of concern also reported increasingly positive perceptions of AI’s instructional benefits, greater willingness to adopt AI tools designed for educators, and more unease as it relates to ethical AI use. The findings suggest that educators’ responses to AI represent an evolving process rather than simple acceptance or resistance to innovation, even though a cross-sectional design methodology was employed. This study provides several AI implementation recommendations for school leaders, as well as several directions for further research. By applying the Concerns-Based Adoption Model to the emerging field of artificial intelligence, this study contributes to the growing body of knowledge on AI implementation in K-12 framework to support educators through a significant technological innovation.en_US
dc.subjectEducation Foundation, Leadership, and Technologyen_US
dc.titleArtificial Intelligence in K-12 Education: An Investigation of Educators’ Stages of Concern, Perception, and Adoptionen_US
dc.typePhD Dissertationen_US
dc.embargo.statusNOT_EMBARGOEDen_US
dc.embargo.enddate2026-08-17en_US
dc.contributor.committeeSerafini, Amy
dc.contributor.committeeHur, Jung Won
dc.contributor.committeeWang, Chih Hsuan
dc.contributor.committeePark, Yuhyun
dc.creator.orcid0009-0006-6076-7221en_US

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