AI-assisted feedback in CLIL courses as a self-regulated language learning mechanism: students’ perceptions and experiences - Campos, Miguel (European Public & Social Innovation Review, 2025)
Introduction: The integration of AI in educational settings offers significant potential for enhancing learning experiences, particularly in Content and Language Integrated Learning (CLIL) contexts. AI tools, such as ChatGPT, provide personalized feedback on writing, addressing issues like unclear content, grammatical errors, or poor vocabulary. This study examines students' perceptions of AI-assisted feedback in a business CLIL course and evaluates the actual improvements in their writing based on the feedback provided by AI. Methodology: University students (n=205) participated in a 15-week Data Description writing course, using ChatGPT to receive specific criteria-based feedback on weekly compositions. Students revised their drafts based on this feedback before their submission. A survey (n=192) assessed their experiences and the perceived impact on writing skills and task efficiency. Additionally, a sample (n=336) of the writing compositions was coded and analyzed to evaluate linguistic enhancement. Results: Results indicate that students found AI feedback beneficial for improving writing skills and appreciated its immediacy and specificity. However, concerns were noted about the complexity and relevance of the feedback. Discussions: Despite these issues, students responded positively, showing significant improvement in content accuracy and linguistic proficiency. Conclusions: The study highlights the potential of AI tools and the need for refining AI feedback mechanisms.