Artificial Intelligence–Driven Adaptive Learning and Microlearning Integration in Enhancing Self-Regulated Learning and Critical Thinking among Adult Digital Learners

Tetri Hariyanti

Authors

Tetri Hariyanti Universitas PGRI Palembang, Indonesia Author

Keywords:

Adaptive Learning, Artificial Intelligence, Microlearning, Self-Regulated Learning, Critical Thinking, Big Data Analytics

Abstract

This study aims to provide an in-depth analysis of the influence of Artificial Intelligence (AI)-based Adaptive Learning and Microlearning integration on the development of critical thinking skills and self-regulated learning methodology among adult learners in e-learning environments. The rapid advancement of educational technology supported by Big Data Analytics has enabled extreme personalization, allowing systems to automatically adjust content, pacing, and learning pathways based on individual performance patterns. This research employed an interpretive qualitative approach using an Exploratory Sequential Mixed-Methods design, beginning with a screening questionnaire and followed by in-depth semi-structured interviews with 25 active digital learners. The findings reveal that AI-driven adaptive systems significantly enhance cognitive efficiency by minimizing time spent on previously mastered material, thereby enabling learners to allocate greater cognitive resources toward analytical reasoning, conceptual application, and complex problem-solving tasks. Furthermore, hyper-personalization contributes to improved metacognitive awareness, better identification of conceptual gaps, and stronger self-regulation strategies. However, a minority of participants expressed concerns that highly optimized adaptive systems may reduce exploratory trial-and-error experiences that are essential for creativity development. This study proposes a Holistic Cognitive Assessment (HCA) framework that integrates adaptive performance metrics with qualitative evaluation as a more comprehensive approach to measuring higher-order cognitive skill development within AI-supported learning systems.

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