Reconstructing The Concept Of Self Actualisation In Artificial Intelligence Based Learning : An Integrative Literature Review
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Abstract
The development of Generative Artificial Intelligence (GenAI) has transformed the learning ecology by positioning AI as a cognitive partner that supports personalisation, feedback, problem-solving, and creativity. This transformation necessitates a reconstruction of the concept of self-actualisation, as some human cognitive activities can be delegated to AI. This study aims to analyse the transformation of self actualisation, identify the conditions that strengthen or hinder it, and formulate a conceptual framework for self-actualisation in AI-based learning. This study employs a qualitative library research approach using an integrative literature review design. The findings indicate that GenAI is paradoxical in nature: it can serve as a cognitive scaffold that strengthens autonomy, competence, self-regulation, creativity, metacognition, and epistemic agency, while also potentially encouraging cognitive offloading, dependence, and the weakening of cognitive autonomy. This study proposes the Reflective-Relational Self Actualisation Framework in AI Learning Ecologies (RRSA-AILE), which encompasses autonomy, competence, relatedness, epistemic agency, metacognitive reflexivity, generative creativity, and ethical responsibility. Theoretically, RRSA-AILE integrates humanism, Self-Determination Theory, Self-Regulated Learning, and learner agency. Practically, the framework provides a foundation for AI-enhanced learning that is augmentative, reflective, and centred on human agency.
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References
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