CULTIVATING IDENTITY, WORKFORCE READINESS, AND HEUTAGOGICAL LIFELONG LEARNING: THE CASE FOR STUDENT-TRAINED AI AGENTS IN POSTSECONDARY EDUCATION​

Abstract

The accelerated integration of human-centered artificial intelligence and human–computer intelligent interaction (HCII) into postsecondary education has inaugurated a paradigm shift in how learners develop cognitive, socio-emotional, and professional competencies. This article argues that requiring students to iteratively build and refine custom AI agents—digital “clones” or GPTs trained on their evolving beliefs, knowledge, values, and interests—addresses three pressing challenges facing contemporary higher education. First, the process of self-modeling via agent training compels deep self-reflection, fostering socio-emotional development and identity formation during the critical neurodevelopmental period that extends into the mid-twenties. Second, as industry trends increasingly prioritize the creation of personal skill and knowledge agents to automate routine tasks and augment human productivity, students who graduate with a mature agent clone are directly prepared for workforce demands in knowledge-intensive sectors. Third, the longitudinal, reflective construction of these agents naturally embeds heutagogical and metacognitive practices, equipping learners with cognitive flexibility, resilience, and the adaptive self-regulation necessary for lifelong learning in a volatile labor market. Drawing on empirical findings from collaborative AI literacy and metacognition research, as well as recent advances in HCII and distributed agent design, this article outlines a transformative educational model that aligns identity work, career preparedness, and adaptive expertise. Such an approach not only individualizes learning but also democratizes access to scalable, context-sensitive cognitive support for a diverse student population