AI in education: a sociological exploration of technology in learning environments

Artificial Intelligence (AI) is fundamentally reshaping contemporary education, not merely as a technical tool but as a transformative sociotechnical force. While often promoted for its potential to personalize learning and improve efficiency, this paper argues that AI's deeper impact lies in its capacity to reorganize relations of power, authority, and inequality within educational systems. This study offers a sociological analysis, drawing on Actor-Network Theory and Critical Digital Sociology to examine how intelligent systems mediate teacher-student relationships, redistribute agency, and contribute to new forms of digital stratification. Through a thematic synthesis of recent literature (2017–2024) and critical analysis of global case examples, the findings demonstrate that AI can intensify existing disparities—through algorithmic bias, surveillance, and uneven access—while generating new dependencies that challenge teacher autonomy and human-centered pedagogy. The analysis further reveals that the dominant techno-optimistic narrative often obscures these power dynamics. In response, this paper concludes by proposing a novel Sociotechnical-Ethical-Pedagogical (STEP) framework, designed to guide the equitable and accountable adoption of AI in education. The STEP model emphasizes transparency, educator agency, and social equity as non-negotiable conditions for responsible innovation, positioning sociological critique as essential for a just educational future.