When Professions Meet GenAI: Patterns of Self-Regulated Learning

As Generative Artificial Intelligence (GenAI) becomes integrated into professional and educational contexts, understanding its role in self-regulated learning (SRL) is essential. This study examined the engagement of 1265 adults from seven occupational sectors with GenAI for SRL, focusing on personal skills, cognitive perceptions, motivation, and contextual factors. The results indicated that the metacognitive application of GenAI is shaped by individual and contextual variables rather than solely on professional affiliation, with distinct patterns emerging across groups. Lecturers and high-tech professionals tend to use GenAI metacognitively when strong self-regulation skills are aligned with high perceived usefulness. Educators, despite high motivation, avoid GenAI unless its advantages are clear. Among healthcare professionals, concerns can either hinder or promote their use, depending on metacognitive readiness. For the general public, its use remains largely functional. This study extends the Technology Acceptance Model (TAM) by identifying perceived usefulness as a mediator between motivation and meaningful engagement, underscoring the need to address both skills and perceptions to foster equitable, informed, and strategic adoption of GenAI in diverse learning environments.