Artificial Intelligence (AI)-Based Digital Learning: The Impact on Students' Learning Motivation and Digital Literacy in Riau

Abstract

The rapid development of digital technology, particularly Artificial Intelligence (AI), has transformed educational practices and learning environments. This study investigates the impact of AI-based digital learning on student learning motivation and digital literacy in Riau.A quantitative research design was employed using a questionnaire administered to 45 students in Riau. Data were analyzed using Structural Equation Modeling (SEM) with Path Analysis (version 3.0) to examine the relationships between AI-based digital learning, learning motivation, and digital literacy.The findings reveal that AI-based digital learning does not have a statistically significant effect on student learning motivation (β = -0.607; T = 0.607 < 1.97; p = 0.544 > 0.05). In contrast, AI-based digital learning has a significant positive effect on students’ digital literacy (β = 0.360; T = 3.047 > 1.97; p = 0.000 < 0.05). These results indicate that while AI integration enhances students’ digital competencies, it does not necessarily foster their motivation to learn.The study suggests that AI-based learning should be complemented with interactive pedagogical strategies—such as collaborative learning, gamification, and reward-based approaches—to effectively enhance student motivation. Despite its limited influence on motivation, AI demonstrates substantial potential in improving digital literacy, enabling educators to promote advanced digital skills through smart learning applications, data-driven learning, and AI-supported platforms. These findings highlight the importance of balancing technological integration with pedagogical innovation to maximize learning outcomes.