Reconstructing The Concept Of Self Actualisation In Artificial Intelligence Based Learning : An Integrative Literature Review
TL;DR
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.
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.
