Integrating CALL and AIALL for an interactive pedagogical model of language learning

Abstract Given the great potential of integrating Computer-Assisted Language Learning (CALL) and Artificial Intelligence-Assisted Language Learning (AIALL) to enhance language learning outcomes, there is a growing interest in exploring their combined effects. In this vein, the present study aimed to develop and test an interactive pedagogical model of language learning (IPMLL) by integrating CALL and AIALL elements in a combined module. To further investigate the effects of this model, a comprehensive evaluation was conducted, considering various aspects such as learner motivation, personalized learning experiences, and feedback effectiveness. The results indicate that (1) the integration of CALL and AIALL in the IPMLL positively influenced learner motivation, leading to greater involvement and active participation in language learning activities; (2) the personal learning interactions facilitated by the IPMLL, including adaptive instruction and intelligent feedback, contributed to improved language proficiency and learner satisfaction. Theoretically, this integration aligns with established pedagogical theories and frameworks, such as cognitive theories of multimedia learning, emphasizing the significance of interactive and technology-enhanced learning environments. Pedagogically, the IPMLL offers practical implications for teachers, highlighting the benefits of incorporating CALL and AIALL elements in language teaching methodologies. This study contributes to the growing body of research on technology-enhanced language learning and provides insights for future developments in this field.