From Moral Formation to Data Governance: Tracing the Evolution of Educational Aims in the Algorithmic Age

Introduction (Context/Justification)
Across centuries, the aims of education have shifted from moral formation and civic virtue to economic productivity and, more recently, data-driven governance. As artificial intelligence (AI) and algorithmic systems become embedded in global education policy, questions arise about how these technologies reorient the purposes of education toward efficiency, prediction, and control. This ongoing study explores the philosophical and political evolution of educational aims in the age of AI, asking how technological rationality reshapes what societies consider “good education.”

Goals and Methods
Guided by Foucault’s genealogy of power/knowledge and Biesta’s notion of the “beautiful risk of education,” this project combines philosophical hermeneutics with qualitative document analysis. It examines key policy frameworks from UNESCO, OECD, China, and Canada to trace shifting discourses around learning outcomes, digital citizenship, and human–machine ethics. Reflexive memoing and iterative coding will be used to identify the conceptual transitions from moral–humanistic to algorithmic–instrumental purposes of education.

Results (Expected)
Preliminary analysis anticipates identifying three paradigmatic stages in the evolution of educational aims: (1) moral and civic formation; (2) economic and human-capital development; and (3) algorithmic optimization and data governance. These shifts reveal how educational policy redefines human agency, autonomy, and the notion of the learner in technologically mediated societies.

Conclusions
This study aims to contribute a conceptual model of educational aims as an evolving moral–epistemic ecology. By historicizing how AI and data logics reshape educational purpose, it invites educators and policymakers to rethink the balance between technological innovation and the enduring human questions of wisdom, justice, and freedom.