Brazilian Education, Discipline, and Algorithms: Tensions Between Control and Autonomy in the Digital Era

Objective: This study presents the Algorithmic Discipline Recalibration Model (ADRM), a theoretically integrated framework that articulates the critical tradition of discipline with the contemporary literature on algorithmic governance to examine how artificial intelligence systems reconfigure institutional dynamics within Brazilian education. It investigates whether the incorporation of AI represents a rupture, an intensification, or a recalibration of historically sedimented disciplinary mechanisms, as well as how this process generates structural tensions between institutional governance and pedagogical autonomy. Method: A structured integrative conceptual review combined with comparative conceptual analysis was employed. Foundational works in genealogical theory, sociology of reproduction, critical data studies, and AI-in-education research were systematically mapped and analyzed to identify convergences and theoretical tensions. Concepts were organized into analytical categories, allowing cross-traditional comparison and synthesis into a unified interpretative model. Findings: The analysis indicates that AI integration does not displace disciplinary rationality but digitally recalibrates it through datafication, predictive analytics, continuous visibility, and performance metrics. Algorithmic mediation translates normalization and classification into statistically mediated governance mechanisms. This transformation produces a structural tension between professional autonomy and institutional oversight, with outcomes contingent upon regulatory design, institutional architecture, and ethical safeguards. Value: This study contributes an original conceptual framework (ADRM) that reframes AI in education as a process of digitally mediated disciplinary recalibration. By integrating classical critical theory with contemporary AI governance debates, it advances a context-sensitive interpretation of algorithmic integration in Brazilian education. Practical Implications: The ADRM offers policymakers, administrators, and educators a theoretically grounded lens to design participatory governance structures, safeguard professional discretion, and implement ethically responsible AI strategies within educational systems.