The Role of Learning Analytics in Language Learning: Understanding Learner Behavior and Personalizing Language Education Experiences - Petrus Jacob Pattiasina; Merlyn Rutumalessy (Yayasan Adra Karima Hubbi, 2026)
Background. The use of learning analytics in education has gained significant traction in recent years, with the potential to revolutionize language learning by providing insights into learner behavior and progress. Learning analytics allows educators to monitor and analyze student data to better understand individual learning patterns, identify areas of struggle, and tailor educational experiences accordingly. Despite its growing use in general education, the specific application of learning analytics in language learning remains underexplored. Purpose. This study aims to investigate the role of learning analytics in language learning, specifically how it can be used to understand learner behavior and personalize language education experiences. The research seeks to examine how data-driven insights can inform teaching strategies, enhance learner engagement, and improve language acquisition outcomes. Method. A mixed-methods approach was employed, combining quantitative analysis of learning data from a digital language learning platform and qualitative interviews with language learners and educators. The study focused on identifying patterns of learner behavior, engagement, and performance, and exploring how these insights could be used to personalize learning experiences. Results. The findings reveal that learning analytics can effectively identify areas where learners struggle, enabling instructors to provide targeted interventions. Personalized learning paths based on analytics lead to increased learner engagement and improved language proficiency. Conclusion. Learning analytics offers significant potential to personalize language education, enhancing both teaching effectiveness and learner outcomes by providing data-driven insights into learner behavior.