Teachers’ AI Literacy and Agency in AI Integration: A Qualitative Study of Teachers in Delhi Private Schools
Source: Frontiers in Education
Author: Frontiers in Education
Original source: https://www.frontiersin.org/journals/education/articles/10.3389/feduc.2025.1651217/full#s8
Published: 2025-08-14
Source type: research
Private backup: the full article text is archived in the private repository at archives/articles/frontiersin-org-full.source.md. It is not published on the public Quartz site.
Summary
This qualitative study examines how 20 elementary and middle school teachers from two private schools in Delhi, India experience and incorporate AI into their teaching. Using semi-structured interviews and thematic analysis grounded in AI Literacy and Ecological Teacher Agency frameworks, the study finds that teachers are both optimistic and concerned. They use AI for administrative efficiency and pedagogical support, but worry about student over-dependence, weakened critical thinking, and ethical gaps. The study argues that AI integration reshapes teachers’ professional beliefs, identities, and agency, and that policy and professional learning should position teachers as active partners rather than passive recipients of top-down AI mandates.
Pull quotes
Contextually constructed beliefs
“Teachers’ beliefs about AI are contextually constructed and dynamically evolving rather than fixed dispositions.”
Agency and identity renegotiation
“Beyond surface-level tool adoption, AI integration fundamentally reshapes teachers’ professional beliefs and sense of agency, prompting ongoing renegotiation of their pedagogical identities and classroom authority.”
Partners, not passive recipients
“policymakers must prioritize collaborative frameworks that position teachers as partners in AI integration design rather than passive recipients of top-down mandates.”
Big ideas
- Schools should start with learning values before choosing AI tools
- District AI work is a long-term redesign project
- Students need to check AI answers against real evidence
- AI tools should be judged by the work they will actually do
- AI literacy has to be taught inside real subjects
Claims
- AI literacy takes system capacity, not just tool access
- AI adoption in schools is mostly a people-change problem
- AI literacy should teach students what to do with AI, not just what to think about it
- AI can undermine learning when students use it without guidance
Key evidence and examples
- Participants were 20 elementary and middle school teachers from two private schools in Delhi’s National Capital Region.
- The study used semi-structured interviews and thematic analysis grounded in AI Literacy and Ecological Teacher Agency frameworks.
- Teachers used AI for reports, documentation, summaries, correspondence, progress documents, content generation, and instructional design.
- Findings emphasize uneven AI literacy: growing technical competence but weaker critical evaluation and ethical application.
Education relevance
High for teacher professional learning, AI literacy frameworks, implementation policy, teacher agency, Global South education contexts, and the difference between tool access and meaningful pedagogical integration.
Durability note
The sample is context-specific to Delhi private schools, but the teacher-agency frame is durable for comparing AI implementation across settings.