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Jess L. Gregory, Southern Connecticut State University, United StatesAbstract
A 6-week online Learning-Theories course for 17 U.S. post-master’s leadership candidates embedded critical analyses of AI’s role in professional and student learning. Participants were educators seeking public school administrator certification. Grounded in Davis’s Technology Acceptance Model (TAM), this study contends educator attitudes toward AI are shaped primarily by perceived usefulness (PU) and perceived ease of use (PEOU), which together predict their behavioral intention to integrate generative AI tools into instruction. A pre/post TAM-aligned survey (4-point Likert) tracked perceived usefulness (PU), ease-of-use (PEOU), and ethical-intent-to-use (EIU) measuring perceptions regarding educative tasks (e.g. AI supports differentiating lessons; AI is damaging to education; Students mostly use AI to cheat; AI supports learning). Paired t-tests revealed selective shifts: large PU gains for AI-driven lesson differentiation (d = 0.68, p = .029) and PD planning (d = 0.47, p = .033); no change in PU for time-saving (d = 0.00) or PEOU for implementation (d = 0.12). EIU declined solely on the “students will cheat” item (d = –0.82, p < .001). There was some positive, non-significant drift for several items (lesson-planning, assignment-planning, general “supports learning”). Candidates accepted utility claims that matched prior pedagogical goals and rejected those lacking concrete classroom examples. Results situate media cues as boundary conditions within TAM: headline ecological validity predicted attitude change better than technical affordances. Programs should couple AI headline critique with sustained, supported classroom practice before adoption. Classroom experiences must overcome prevailing narratives in the media to shift the ethical intention to use generative AI to support learning.
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Conference: ACEID2026Stream: Innovation & Technology
This paper is part of the ACEID2026 Conference Proceedings (View)
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To cite this article:
Gregory J. (2026) Headlines in the Classroom: Media Narratives and the Selective Shifts in Teachers’ AI Judgments ISSN: 2189-101X – The Asian Conference on Education & International Development 2026 Official Conference Proceedings (pp. 709-724) https://doi.org/10.22492/issn.2189-101X.2026.57
To link to this article: https://doi.org/10.22492/issn.2189-101X.2026.57
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