Integrating flipped learning in AI-enhanced language learning: Mapping the effects on metacognitive awareness, writing development, and foreign language learning boredom

The increasing integration of Artificial Intelligence (AI) within educational contexts is fostering significant pedagogical shifts, with flipped learning concurrently gaining prominence as a dynamic, student-centered instructional model. Despite their individual merits, there remains a paucity of empirical research on the synergistic effects when AI enhances flipped learning, particularly concerning crucial EFL learner variables such as metacognitive awareness, writing development, and foreign language boredom. This study, therefore, aimed to address this gap by examining the impact of an AI-enhanced flipped learning environment. To this end, a quasi-experimental design was implemented involving 70 intermediate Iranian EFL learners, selected through convenience sampling and subsequently assigned to either an experimental group, which experienced AI-enhanced flipped instruction, or a control group that received AI-enhanced instruction without the flipped component. The required data were gathered via validated questionnaires and pre- and post-intervention writing tasks. Following this, a one-way ANCOVA was employed for data analysis to ascertain inter-group differences while controlling for pre-existing variations. The results revealed that AI-enhanced flipped learning significantly improved learners' metacognitive awareness. Furthermore, the findings indicated that this pedagogical approach significantly promoted writing development among students in the experimental group. Additionally, the outcomes showed a substantial reduction in foreign language learning boredom for learners engaged in the AI-enhanced flipped classroom. These findings lend support to the potential of strategically embedding AI within flipped learning models to cultivate more autonomous, engaged, and effective language learning