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Climate-control ChatGPT for EFL writing and AI literacy
Hesham Aldamen1, Salwa Mohammad Alawneh2, Mohamad Almashour1
1Department of English Language and Literature, The University of Jordan, Amman, Jordan.
Frontiers in Artificial Intelligence
|August 6, 2026
Summary
A new climate-control ChatGPT method significantly improved EFL learners' AI literacy and argumentative writing skills compared to standard AI use. This approach fosters greater authorial control and harm-sensitive reasoning in academic writing.
Area of Science:
- Applied Linguistics
- Educational Technology
- Artificial Intelligence in Education
Background:
- Growing use of ChatGPT in English as a Foreign Language (EFL) writing necessitates methods to assess its impact on AI literacy and reasoning.
- Existing research lacks robust frameworks for evaluating AI-assisted learning outcomes in critical thinking and independent writing.
Purpose of the Study:
- To compare the effectiveness of a climate-control ChatGPT intervention against standard ChatGPT use and no-AI instruction.
- To measure gains in learners' AI literacy, harm-sensitive reasoning, and argumentative writing quality.
- To develop and validate a computational framework for analyzing responsible AI literacy.
Main Methods:
- A mixed-methods quasi-experimental study with 120 undergraduate EFL learners.
- Three conditions: no-ChatGPT control, standard ChatGPT, and climate-control ChatGPT.
- Data collection included essays, dialogue logs, reflections, interviews, and HARM-CAL annotated language units.
Main Results:
- The climate-control ChatGPT group showed the greatest improvements in harm-sensitive AI literacy and argumentative writing.
- This condition also led to reduced direct AI uptake, increased self-repair, and enhanced authorial control.
- Benefits were sustained in delayed transfer tasks without AI assistance.
Conclusions:
- Climate-control ChatGPT is an effective intervention for enhancing EFL learners' AI literacy and academic writing.
- The study provides a validated computational framework (HARM-CAL) for analyzing responsible AI literacy in language learning.
- Findings support the development of AI tools that promote critical engagement and independent thought in educational settings.
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