ARTIFICIAL INTELEGENCE & MULTIPLE INTELEGENCE REDESIGNING PERSONALIZED LEARNING IN THE ERA SOCIETY 5.0

Abstract

Educational transformation in the Society 5.0 era demands the integration of digital technology with a more humanistic and adaptive learning approach. One of the main challenges is how to accommodate the diversity of student potential according to the theory of Multiple Intelligences (MI), which in manual practice is often hampered by time constraints, the number of students, and the subjectivity of teacher assessments. This study aims to formulate a conceptual framework for the integration of MI with Artificial Intelligence (AI) to support personalized learning and strengthen 21st-century competencies (6Cs). This study uses a systematic literature review approach to relevant international publications (2019–2025), with additional classical literature as a theoretical foundation. A total of 47 selected sources were analyzed and synthesized thematically.

The study results produce a conceptual framework consisting of the following flow: learning data input → AI analysis → MI mapping → adaptive learning strategies → 6Cs reinforcement. Examples of potential implementation are demonstrated through the use of AI in providing automated feedback, adaptive questions, VR/AR simulations, self-reflection, and collaborative projects based on global issues. This study concludes that AI–MI integration has the potential to increase assessment objectivity, strengthen personalization, and accelerate learning feedback. Theoretically, this research contributes to the development of the AI–MI conceptual model, while practically it provides a reference for teachers and policymakers to design inclusive and adaptive learning. However, because it is still conceptual, further research is needed to test the effectiveness of this framework through an empirical approach in schools