An idiodynamic study of EFL learners’ motivational dynamics during oral practice on an ASR-based website with automatic feedback

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ABSTRACT Purpose Guided by Complex Dynamic Systems Theory, this study explores the motivational dynamics of EFL learners during oral practice on an Automatic Speech Recognition website with automatic feedback. Methodology Five undergraduate students participated in oral task experiments, followed by self-rating of task motivation and stimulated recall interviews. Findings Linguistic, cognitive, metacognitive, affective, and contextual dimensions were primary variables interacting to shape learners’ motivation. Diverse and non-linear interaction patterns emerged. The study highlights the complex interplay between learner variables and AI-generated feedback, demonstrating how learners’ perceptions and expectations influence their engagement with automated learning tools. Value The findings suggest that educators should enhance learners’ critical thinking skills when using AI tools to foster adaptive interpretation of AI feedback. AI developers are encouraged to improve AI feedback accuracy and personalize support to enhance learning experiences. This research deepens understanding of motivational dynamics in AI-assisted language learning and offers implications for pedagogy and AI tool design.