Impact of AI gamification on EFL learning outcomes and nonlinear dynamic motivation: Comparing adaptive learning paths, conversational agents, and storytelling

The study examines the impact of artificial intelligence (AI)-enhanced gamification on learning outcomes and motivation in English as a Foreign Language (EFL) contexts. A mixed-methods approach and quasi-experimental design were employed to compare the effectiveness of three instructional strategies: adaptive learning paths, conversational agents, and interactive storytelling. The research involved 486 undergraduate students, with evaluations conducted on their language proficiency and dynamic motivation before and after engaging with AI-enhanced gamification interventions. Statistical analysis using ANOVA demonstrated that adaptive learning paths were significantly more effective than other strategies and control groups in improving language proficiency (F(3, 482) = 1131.607, p < .000) and dynamic motivation (F(3, 482) = 529.318, p < .000). The findings highlight the superior efficacy of adaptive learning paths in addressing learners’ motivational needs and fostering language acquisition. The research provides practical implications for language instructors by underscoring the importance of adaptive learning paths in designing personalized and engaging learning experiences. The results suggest that AI-driven instructional strategies can transform conventional teaching methodologies to better accommodate the diverse needs and preferences of contemporary learners. Furthermore, the study advances the theoretical understanding of AI gamification in language education by offering a comprehensive framework for integrating adaptive, interactive, and personalized approaches into pedagogical practices.