Emotional Engagement in AI-Supported Online English Learning: A Mixed-Methods Study Among Indonesian EFL Students
Keywords:
emotional engagement, Artificial Intelligence, online English learning, affective computing, multimodal feedbackAbstract
This study explores how emotional engagement shapes learners’ experiences in AI-supported online English learning environments. Using a mixed-methods design, this research combines quantitative surveys, learning analytics, and qualitative interviews to investigate the relationship between emotional states, motivation, and learning performance among 60 Indonesian EFL students aged 18–24. Results reveal that emotion-based feedback, adaptive chatbots, and multimodal instructional design significantly enhance students’ enjoyment, confidence, and motivation while reducing anxiety. Multimodal feedback integrating visual and verbal cues proved particularly effective in fostering positive emotions and sustaining long-term engagement. However, excessive reliance on AI may limit opportunities for social interaction and the development of critical thinking. These findings emphasize the need for a hybrid pedagogical model that balances human empathy with technological adaptability. Overall, this study contributes to affective computing in education by promoting emotion-sensitive learning design to create inclusive, engaging, and human-centered digital learning environments. Future research is recommended to employ longitudinal and experimental designs to examine the long-term impact of emotional engagement on learning outcomes.
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