Relief or displacement? How teachers are negotiating generative AI's role in their professional practice

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Authors: Aayushi Dangol, Smriti Kotiyal, Robert Wolfe, Alex J. Bowers, Antonio Vigil, Jason C Yip, Julie A. Kientz, Suleman Shahid, Tom Yeh, Vincent Cho, Katie S. Davis
Cited by: 1
References: 158

Abstract

As generative AI (genAI) rapidly enters classrooms, accompanied by district-level policy rollouts and industry-led teacher trainings, it is important to rethink the canonical “adopt and train” playbook. Decades of educational technology research show that tools promising personalization and access often deepen inequities due to uneven resources, training, and institutional support. Against this backdrop, we conducted semi-structured interviews with 22 teachers from a large U.S. school district that was an early adopter of genAI. Our findings reveal the motivations driving adoption, the factors underlying resistance, and the boundaries teachers negotiate to align genAI use with their values. We further contribute by unpacking the sociotechnical dynamics—including district policies, professional norms, and relational commitments—that shape how teachers navigate the promises and risks of these tools.

Fields of Study & Subjects

Ethics and Social Impacts of AI Teaching and Learning Programming Artificial Intelligence in Healthcare and Education

Publication details

Journal / source
Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems
Publisher
ACM
Pages
1–21
Publication date
13 April 2026