Academic Self-Regulation Reimagined in Digital Era
Author(s): Dr. Rafi Mohmad
Publication #: 2601009
Date of Publication: 12.12.2025
Country: India
Pages: 1-9
Published In: Volume 11 Issue 6 December-2025
DOI: https://doi.org/10.62970/IJIRCT.v11.i6.2601009
Abstract
The digital era, accelerated by the widespread adoption of online platforms, blended learning, and generative artificial intelligence (GenAI) tools since 2020, has transformed academic learning into highly autonomous, flexible, and personalized yet demanding environments. Academic self-regulated learning (SRL)-the active, goal-directed process of planning, monitoring, controlling, and reflecting on cognition, motivation, behaviour, and context—has become an indispensable competency for success in these settings, where learners face constant distractions, information overload, algorithmic influences, and reduced external structure.
This conceptual paper critically evaluates and reconceptualizes three foundational SRL models—Zimmerman’s cyclical model (forethought, performance, self-reflection), Pintrich’s motivational framework (phases×cognitive/motivation/behavior/context areas), and Boekaerts’s dual-processing model (mastery/growth vs. well-being/coping pathways)—in the context of AI-driven and online learning environments. While these models remain robust in their emphasis on agency, motivation, and iterative adaptation, they reveal critical limitations when applied to contemporary digital realities: insufficient theorization of technological co-regulation, algorithmic impact on agency, emotional dysregulation from constant interruptions, and challenges in dynamic, multimodal measurement.
The paper proposes a Digital-Augmented SRL (DA-SRL) hybrid framework that integrates the strengths of the three models with a new "AI co-regulation layer," expanded technological context regulation, and digital appraisal mechanisms. This reconceptualization preserves learner autonomy while leveraging GenAI affordances (personalized prompts, analytics, feedback loops) and mitigating risks (over-reliance, cognitive offloading, motivation decline). Practical implications for educators (embedding metacognitive scaffolds), learners (AI literacy and intentional toggling), and designers (transparent, regulation-focused tools) are discussed, alongside persistent barriers (digital divide, measurement ethics) and a future research agenda emphasizing longitudinal, multimodal, and equity-focused studies.
By bridging classic theory with the realities of AI-saturated education, this work contributes to educational psychology and technology-enhanced learning, offering pathways to cultivate resilient, self-directed learners in the digital age.
Keywords: Self-regulated learning, academic self-regulation, Zimmerman model, Pintrich model, Boekaerts model, digital era, AI-driven learning, generative AI, online learning, blended learning, metacognition, motivation regulation, digital co-regulation, technological context
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