Speaker
Description
This presentation explores how generative AI can function as scaffolding in EAP classrooms rather than as a substitute for student thinking and writing. Drawing on classroom practice and research with advanced university learners, it examines a structured approach in which AI supports learners at carefully designed stages of the academic writing process. The presentation considers how purposeful AI scaffolding can develop academic writing, critical AI literacy, and learner agency while maintaining students’ ownership of their ideas and written work.
Abstract section 4: Outcomes/results
This honors program admits students with diverse English proficiency, emphasizing their potential contributions to global society rather than language level. This means there is an enormous gap in linguistic abilities, and tailoring feedback to the individual student is challenging and timeconsuming. Findings from this study, however, indicate that this personalized integrated approach can support mixed level classes in strengthening linguistic proficiency, organizational skills, editing abilities, and critical thinking for each independent learner. Teacher evaluations confirmed these improvements, highlighting the potential of scaffolded AI use to complement peer- and self-review while fostering learner autonomy in academic writing.
Abstract section 2: Contribution/research questions
The study tracked and evaluated student changes in attitude towards the use of MT and AI in academic writing. It also examined how an integrated approach towards different types of guidance and/ or feedback – MT, self-evaluation check list, peer evaluation, Writing Development Desk (WDD), and finally AI --- can help students develop stronger structure, organizational, and linguistic skills.
Abstract section 1: Relevance
The integration of Artificial Intelligence (AI) into higher education presents opportunities and challenges, particularly in Second Language Acquisition (SLA). While machine translation (MT) and AI are widespread in informal learning, their classroom use raises concerns of academic integrity. This final phase of a two-year study examines MT as a bridge to the transparent, structured use of ChatGPT as a feedback tool in essay writing within an EAP curriculum. Conducted in a year-long honors program at a Japanese university, the mixed-method study used questionnaires, interviews, and writing analysis with students of diverse English proficiency selected for their global potential.
Abstract section 3: Content/method
Conducted in a year-long honors program at a Japanese university, the study employed a mixed-method design combining pre- and post-semester questionnaires, student interviews, and writing analysis. As part of a nine-step essay-writing protocol, ChatGPT was introduced at the final stage. Students engaged with the MT suggestions, peer evaluations, Writing Development Desk feedback, as well as CEFR C1 and C2 versions with feedback in easy English to revise their drafts before final submission.
Abstract section 5: References
Ohashi, L. (2022). The use of machine translation in L2 education: Japanese university teachers’ views and practices. In B. Arnbjörnsdóttir, B. Bédi, L. Bradley, K. Friðriksdóttir, H. Garðarsdóttir, S. Thouësny, & M. J. Whelpton (Eds), Intelligent CALL, granular systems, and learner data: short papers from EUROCALL 2022 (pp. 308-314). Research-publishing.net. https://doi.org/10.14705/rpnet.2022.61.1476
| Title | A Scaffolded Approach to AI in EAP Classrooms |
|---|---|
| Teaching Context | College and university education |