Artificial Intelligence, Motivation, and Investment in EFL Learning - Mira Tania; Cindy Amalia Mughni (J-CEKI : Jurnal Cendekia Ilmiah, 2026)
This study examines the role of artificial intelligence (AI) in shaping learner motivation and investment in English as a foreign language (EFL) learning through a narrative systematic review of studies published between 2015 and 2025. Drawing on a dataset of 23 selected studies from Scopus, the review synthesizes evidence on how AI-driven technologies influence both cognitive and affective dimensions of language learning. The findings reveal that AI significantly enhances learner motivation through personalized learning pathways, real-time feedback, and interactive environments. In addition, AI contributes to learner investment by fostering identity development, commitment, and sustained engagement. The results also indicate improvements in language proficiency, increased participation, and reduced anxiety, highlighting the dual impact of AI on performance and learner experience. However, the review identifies key challenges, including technological limitations, teacher readiness, and pedagogical misalignment, as well as fragmentation across existing research. The study argues for a holistic, ecosystem-based approach that integrates technological, pedagogical, and sociocultural perspectives. By addressing these dimensions, the study provides theoretical and practical insights into optimizing AI-supported EFL learning and offers directions for future research toward more integrated and sustainable learning environments.