How teachers perceive AI in their profession and classroom: professional visions and practical problems
OA Version
Citation
Abstract
Although artificial intelligence (AI) technology has long existed, only recently has it broken into public consciousness. The hopes and fears surrounding it range from catastrophic nightmares to utopian dreams. As a communication and information technology, AI is particularly relevant to the educational enterprise. Already, there’s much discussion about what the proper role should be of AI in education and how it will affect the roles of teachers. Given the big stakes, it's important for communication scholars to devote attention to this emerging technology. To take up this challenge, this study explores how teachers perceive AI in education, focusing on its impact on professional identity, values, and pedagogical autonomy. Traditional functionalist models like the Technology Acceptance Model (TAM) often overlook the deeper psychological and contextual factors shaping educators’ attitudes. The study adopts an interdisciplinary approach that integrates the sociology of professions with functionalist models under a critical realism (CR) framework. This approach provides a multi-layered lens to explore educators’ acceptance or resistance to AI, addressing factors that single-paradigm models overlook. Methodologically, the research employed semi-structured interviews with 51 K–12 educators, followed by a CR-guided thematic analysis to uncover underlying patterns and causal mechanisms. The analysis was augmented by an innovative use of large language models (LLMs) to assist in qualitative coding and theme identification under careful researcher oversight, demonstrating a novel AI-assisted approach to data analysis within a CR paradigm. Findings reveal that teachers’ professional identity, which includes their sense of autonomy, ethics, and purpose, emerged as a key causal mechanism influencing attitudes toward AI. When educators perceived AI tools as reinforcing their professional values and enhancing their autonomy, they were inclined to adopt them; if the tools threatened these values or autonomy, educators showed resistance.
Based on these insights, the study proposes a refined conceptual model of AI adoption in education that combines task-oriented factors (e.g. perceived usefulness, ease of use, organizational support) with profession-oriented factors (e.g. value alignment, professional identity, ethical considerations). This model significantly extends conventional technology acceptance theories by embedding the moral and professional dimensions of teaching into adoption frameworks. Theoretical contributions include expanding educational technology (EdTech) adoption models with professional identity and ethics constructs, while a key methodological contribution is illustrating how LLM-assisted qualitative analysis can be conducted rigorously under a CR approach. Practically, the findings provide insights for teacher training, school leadership, and policymaking. They highlight that successfully integrating AI into K–12 schools requires targeted professional development programs that clearly illustrate how AI can enhance teaching practices while preserving teacher autonomy and student-teacher relationships. Additionally, schools should establish explicit ethical guidelines and policies to ensure responsible AI use aligned with teachers' professional values, particularly concerning academic integrity, fairness, and student privacy. It is also essential to foster collaborative professional communities that enable educators to experiment with AI, share effective practices, and collectively address emerging ethical concerns. Finally, ensuring equitable access to AI resources across diverse school settings is critical to preventing the widening of gaps in educational equity.
Description
2025
License
Attribution-NoDerivatives 4.0 International