This study explores the impact of AI on integrative language instruction, specifically comparing Task-based Instruction (TBI) and Content-based Instruction (CBI) through the lens of Bloom’s revised taxonomy. The research examines how AI influences l...
This study explores the impact of AI on integrative language instruction, specifically comparing Task-based Instruction (TBI) and Content-based Instruction (CBI) through the lens of Bloom’s revised taxonomy. The research examines how AI influences language learners' cognitive processes and knowledge acquisition. Data were collected from 17 participants and three instructors using an open-ended questionnaire, semi-structured interviews, and teacher’s reflective notes, and were analyzed using content analysis. Findings revealed three key pedagogical implications: (1) In TBI, learners predominantly used procedural knowledge and applied cognitive processes, while CBI encouraged a broader range of cognitive skills. (2) The integration of AI in these instructional methods activated higher-order thinking skills, particularly for error detection and progress monitoring. (3) Divergent perspectives emerged between learners and instructors; learners appreciated AI’s role in enhancing language learning, whereas instructors expressed concerns about AI potentially undermining learners’independent learning and language competence. The study suggests that while AI can support language learning, it is crucial to ensure that its application complements rather than hinders learners’cognitive and communicative development.