{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,22]],"date-time":"2026-07-22T06:06:39Z","timestamp":1784700399633,"version":"3.55.0"},"reference-count":51,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,7,22]],"date-time":"2026-07-22T00:00:00Z","timestamp":1784678400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Artif. Intell."],"abstract":"<jats:p>ChatGPT is increasingly used in EFL writing, yet applied linguistics lacks robust methods for measuring whether human-AI dialogue improves learners\u2019 AI literacy, harm-sensitive reasoning, and independent argumentative writing. This mixed-methods quasi-experimental study examines whether climate-control ChatGPT, a prompted interactional design that requires learners to justify, qualify, counterexample, and re-author their own claims, produces stronger gains than standard ChatGPT use and no-ChatGPT instruction. The study involved 120 undergraduate EFL learners in six intact second-year academic writing sections at a public university in Jordan. Participants were assigned to no-ChatGPT control, standard ChatGPT, or climate-control ChatGPT conditions. Data included no-AI diagnostic, pretest, posttest, and delayed transfer essays; ChatGPT dialogue logs; first and final drafts; learner reflections; uptake traces; stimulated-recall interviews; and 9,113 HARM-CAL annotated language units. HARM-CAL, Harm-sensitive Reasoning and Anthropomorphism Calibration in Language, classified learner language for na\u00efve relativism, moral imposition, harm-sensitive reasoning, AI anthropomorphism, calibrated AI literacy, and reflective uncertainty. Results showed that the climate-control condition produced the largest gains in harm-sensitive AI literacy and argumentative writing quality, with advantages maintained on delayed no-AI transfer. It also reduced direct uptake, increased self-repair and authorial control, and strengthened calibrated distinctions between AI output competence and consciousness. The study contributes a classroom-tested intervention and a transparent computational framework that combines reproducible annotation procedures, a fully specified TF-IDF baseline, and archived transformer-family classifier outputs for analyzing responsible AI literacy in second-language argumentation.<\/jats:p>","DOI":"10.3389\/frai.2026.1869343","type":"journal-article","created":{"date-parts":[[2026,7,22]],"date-time":"2026-07-22T05:53:22Z","timestamp":1784699602000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Climate-control ChatGPT for EFL writing and AI literacy"],"prefix":"10.3389","volume":"9","author":[{"given":"Hesham","family":"Aldamen","sequence":"first","affiliation":[{"name":"Department of English Language and Literature, The University of Jordan","place":["Amman, Jordan"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Salwa Mohammad","family":"Alawneh","sequence":"additional","affiliation":[{"name":"Department of Architectural Engineering, Yarmouk University","place":["Irbid, Jordan"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohamad","family":"Almashour","sequence":"additional","affiliation":[{"name":"Department of English Language and Literature, The University of Jordan","place":["Amman, Jordan"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mutasim","family":"Al-Deaibes","sequence":"additional","affiliation":[{"name":"Department of English, American University of Sharjah","place":["Sharjah, United Arab Emirates"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rami","family":"Alsharefeen","sequence":"additional","affiliation":[{"name":"Faculty Affairs, Rabdan Academy","place":["Abu Dhabi, United Arab Emirates"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,7,22]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"1614673","DOI":"10.3389\/feduc.2025.1614673","article-title":"AI vs. teacher feedback on EFL argumentative writing: a quantitative study","volume":"10","author":"Alnemrat","year":"2025","journal-title":"Front. 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