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Description
The rapid advancement of generative Artificial Intelligence (AI) has created new possibilities for language teaching and learning, particularly in task-based and communicative approaches. This paper explores how generative AI can support English as a Foreign Language (EFL) teachers in designing authentic communicative tasks that promote meaningful interaction and language use. The purpose of this study is to investigate the potential of AI-generated tasks to enhance learners’ communicative competence, engagement, and participation in EFL classrooms.
The study adopts a qualitative action research approach conducted in secondary and high school EFL contexts. A series of communicative tasks, including role-plays, problem-solving activities, information-gap tasks, and real-world simulations, are designed using generative AI tools. Data are collected through classroom observations, student questionnaires, reflective journals, and interviews with both teachers and learners. The analysis focuses on students’ interaction patterns, language production, and perceptions of AI-supported learning activities.
The expected findings suggest that generative AI enables teachers to create personalized, contextually relevant, and engaging communicative tasks more efficiently than traditional methods. Students are anticipated to demonstrate increased motivation, greater participation in communicative activities, and improved confidence in using English for authentic purposes. Furthermore, AI-generated tasks are expected to provide opportunities for meaningful communication that align with the principles of Task-Based Language Teaching (TBLT) and Communicative Language Teaching (CLT).
The implications of this study highlight the role of generative AI as a valuable pedagogical tool for enhancing communicative language instruction. The findings may offer practical guidance for EFL educators seeking to integrate AI into task design while maintaining learner-centered, interactive, and authentic language learning environments.
