How Human–AI Collaborative Learning Enhances Adaptive Learning Strategies: The Mediating Role of Metacognition - Lukman Abdul Majid; Adhi Kumara Saddhadhika; Sutiyono Sutiyono; Moses Adeleke Adeoye (LPPM STIAB JINARAKKHITA LAMPUNG, 2026)
This study investigates the influence of Human–AI Collaborative Learning on students’ Adaptive Learning Strategies, with Metacognition serving as a mediating mechanism. A quantitative research design was employed using a survey of university students, with data collected through a structured questionnaire measuring Human–AI Collaborative Learning, Metacognition, and Adaptive Learning Strategies. The data were analyzed using Partial Least Squares Structural Equation Modeling to examine both the direct and indirect relationships among the proposed constructs. The findings reveal that Human–AI Collaborative Learning positively enhances students’ metacognitive abilities and adaptive learning strategies. Furthermore, metacognition exerts a significant positive influence on adaptive learning strategies and functions as a partial mediator in the relationship between Human–AI Collaborative Learning and students’ adaptive learning strategies. The proposed model demonstrates substantial explanatory capability, indicating that collaborative interactions with artificial intelligence contribute meaningfully to students’ capacity for self-monitoring, learning regulation, and strategic adaptation. These findings underscore the importance of integrating artificial intelligence as a collaborative learning partner to strengthen students’ metacognitive development and foster adaptive learning strategies in higher education. The study contributes to the growing literature on human–AI collaboration by providing empirical evidence that metacognition constitutes a key psychological mechanism through which AI-supported learning environments promote adaptive learning.