AI-BASED LEARNING TOOLS AND EFL STUDENTS’ ENGAGEMENT, MOTIVATION, ENJOYMENT - Lina Ardi (Universitas Negeri Semarang, 2026)
An emerging concern in higher education for second language learning of English is the considerable inadequacy of traditional teaching practices in supporting students’ motivation, enjoyment, and engagement. This study aims to examine whether learning with artificial intelligence (AI) can enhance students’ motivation, enjoyment, and engagement compared to traditional learning methods. A total of forty-nine college students participated in the experiment, divided into two groups: twenty-four students in the experimental group (EG) and twenty-five students in the control group (CG). During a ten-week intervention, all participants were assessed using three affective scales at both the beginning and the end of the study period. To control for initial score differences between groups, multiple analytical techniques were applied, including response matching, outlier identification, aggregation analysis, and ANCOVA. The results revealed significant improvements in all three affective variables in the experimental group. Motivation increased significantly (F = 10.574, p = 0.002, ηp² = 0.186), enjoyment showed a strong increase (F = 35.366, p < 0.001, ηp² = 0.435), and engagement also improved significantly (F = 29.451, p < 0.001, ηp² = 0.390). These findings suggest a consistent positive effect of AI-based learning tools, indicating that AI may be more effective than traditional teaching methods in enhancing learners’ affective outcomes in language learning