Personalized Learning Paths: The Impactsof Adaptive Learning Technologies (ALT)andArtificial Intelligence (AI) -Driven Analyticson Language Acquisition

Abstract

Language learners often exhibit unique learning styles that shape how they acquire and understand a new language. Adaptive learning technologies (ALT), coupled with Artificial Intelligence (AI)-driven analytics, offer enhanced virtual platforms that support personalized learning experiences tailored to individual preferences and learning strategies. This study examines the effects of these adaptive learning tools and Artificial Intelligence (AI) analytics on the language acquisition of foreign language learners. Focusing specifically on the Duolingo learning application, the research investigates how its adaptive learning system and Artificial Intelligence (AI) components contribute to more effective language acquisition. A total of 32 English as a Foreign Language (EFL) learners/students were purposively selected to participate in the study. Utilizing a quasi-experimental design, the study found that the control group showed minimal improvement between their pre-test and post-test assessments. In contrast, the experimental group demonstrated a notable increase in performance, with mean scores rising from 19.03 in the pre-test to 23.82 in the post-test. These findings underscore the positive influence of adaptive learning technologies and Artificial Intelligence (AI-driven) analytics on the language learning process. The integration of such tools not only fosters personalized instruction but also enhances overall learning outcomes for foreign language learners.