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

Paper Title

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

Publication Info

• Topic area: Generative AI integration in K–12 education
• Keywords: generative AI, K–12 education, teacher adaptation, sociotechnical systems, educational technology, professional development, AI literacy, classroom practices, teacher values, policy frameworks

Background and Problem

• Problem / challenge: Despite the rapid introduction of generative AI (genAI) in classrooms, there is limited understanding of how teachers integrate these tools into their practices, reconcile them with pedagogical goals, and navigate associated challenges such as inequities, lack of training, and ethical concerns.
• Significance: Understanding teachers' experiences is critical for designing genAI tools that align with classroom realities and for ensuring responsible, equitable, and sustainable adoption in education.
• Motivation and related work: Prior research has explored genAI's technical capabilities and potential applications in education but has largely overlooked how teachers interpret, adapt, and negotiate these tools in practice. This study builds on frameworks like the Teacher Response Model (TRM) to examine the sociotechnical dynamics of genAI integration.

Solution

• Proposed approach: A teacher-centered, sociotechnical analysis of genAI integration in K–12 education, focusing on teachers' perceptions, adaptations, and boundary-setting practices.
• Novelty:
  1. Examines how teachers navigate tensions between genAI's potential to alleviate workload and its risks of displacing intellectual and relational aspects of teaching.
  2. Highlights the role of institutional policies, peer networks, and professional norms in shaping genAI adoption.
  3. Identifies conditions necessary for sustainable genAI integration, including clear policies, professional development, and relational pedagogy.
  4. Provides design implications for genAI tools that support teachers' evaluative and adaptive work.
• Procedure and key techniques:
  • Conducted semi-structured interviews with 22 teachers from a large U.S. school district.
  • Used Reflexive Thematic Analysis (TA) to analyze interview data, guided by the TRM framework.
  • Explored teachers' motivations, challenges, and boundary-setting practices in genAI use, as well as systemic conditions for sustainable adoption.

Results

• Concrete findings:
  • Teachers valued genAI for time-saving, burnout prevention, and expanding instructional possibilities but expressed concerns about over-reliance, loss of human connection, and ethical issues like data privacy and environmental impact.
  • Adoption was influenced by institutional incentives, peer networks, and the need to support multilingual learners.
  • Reluctance stemmed from time barriers, stigma, preference for traditional methods, and environmental concerns.
  • Teachers actively set boundaries to preserve professional judgment, ensure data privacy, and balance genAI use with relational teaching.
• Advantage over baselines:
  • Provides a nuanced understanding of teachers' decision-making processes and the sociotechnical factors influencing genAI integration, which are often overlooked in prior studies focused on technical capabilities or student outcomes.
• Experiments / evaluation:
  • Study conducted in a diverse school district with 22 participants representing various roles, grade levels, and subject areas.
  • Data collected through in-depth interviews and analyzed using a structured thematic approach.
• Limitations and future work:
  • Study limited to a single school district, which may not generalize to other contexts with different resources or policies.
  • Future research should explore longitudinal and participatory approaches across diverse educational settings to examine broader institutional and cultural influences.

Summary

This study provides a teacher-centered analysis of how K–12 educators are integrating generative AI into their professional practices. Teachers appreciated genAI's potential to alleviate workload and support instructional creativity but expressed concerns about over-reliance, ethical risks, and the erosion of relational teaching. Adoption was shaped by institutional policies, peer networks, and systemic inequities, while reluctance stemmed from time constraints, stigma, and environmental concerns. Teachers actively negotiated boundaries to align genAI use with their pedagogical values and professional judgment. The findings highlight the need for clear policies, targeted professional development, and AI literacy curricula to ensure responsible and sustainable genAI integration in schools.