How to Prepare Students for a Technology-Driven Society? The Case of Digital Fluency, Self-Regulated Learning, and AI Metacognition in 21st-Century Adaptive Performance

Abstract

Modern soeciety requires individuals to adapt to the rapidly evolving digital landscape. Adaptability in modern society is becoming inscreasingly critical for growing workforce. This study examined how adaptive performance is being influenced by digital fluency, self-regulated learning, and collaborative AI metacognition. Data were collected through an online survey among science students from North Eastern Mindanao State University. The variables were measured using validated scales, including the 19-item multidimensional scale for adaptive performance (Charbonnier-Voirin & Roussel, 2012). PLS-SEM (Partial Least Squares Structural Equation Modeling) was employed to analyze the relationships between digital fluency, self-regulation, collaborative AI metacognition, and adaptive performance. Statistical analysis showed that digital fluency significantly influenced adaptive performance (β= 0.203, p < 0.001), albeit with a moderate effect size, suggesting it works well with other cognitive factors. Self-regulation was found to significantly mediate the relationship between digital fluency and adaptive performance (β= 0.134, p < 0.001), emphasizing the importance of self-regulatory strategies in applying digital skills effectively. Furthermore, collaborative AI metacognition had a substantial direct effect on adaptive performance (β= 0.410, p < 0.001), showing the importance of reflection with AI tools in building adaptability. Essentially, students are more likely to adapt effectively to technological advancements when they develop digital fluency, self-regulated learning skills, and the ability to critically evaluate AI-generated information. This study empahasized the notion that preparing students for a technology-driven society requires cultivating competencies that enable them to respond to rapid changes, navigate emerging digital environments, and distinguish reliable information from potentially misleading sources.