The rapid diffusion of generative artificial-intelligence (AI) tools such as ChatGPT is reshaping language-learning ecologies. While early adopters have focused on gains in fluency and accuracy, a more compelling pedagogical question is whether AI can cultivate higher-order thinking skills (HOTS)—analysis, evaluation and creative synthesis—in English as a Second Language (ESL) learners. The present study examines an intervention in which undergraduate ESL students completed a sequence of argumentative and reflective writing tasks mediated by an AI co-writer that provided dynamic scaffolding, metacognitive prompts and automated discourse analysis. Grounded in Bloom’s revised taxonomy and socio-constructivist learning theory, the mixed-methods design combined quasi-experimental pre- and post-testing with thematic analysis of learner journals. Quantitative results showed statistically significant improvements (p < 0.05) in students’ HOTS rubric scores compared with a control group engaged in traditional peer-review cycles. Qualitative data revealed heightened metalinguistic awareness and strategic risk-taking in idea development. The findings suggest that, when carefully orchestrated, AI-supported writing can transcend mere linguistic assistance and become a catalyst for deeper cognitive processing. Pedagogical implications and design principles for AI-enhanced assessments that preserve academic integrity are discussed.  

Higher-order thinking, AI-supported writing, ESL pedagogy

Wu Y., Li S., Chen H. Effects of ChatGPT on students’ learning performance // Humanities & Social Sciences Communications. – 2024. – Vol. 11, № 5. – P. 1–14.

Lu K., Zhang J., Gao M. ChatGPT-assisted teacher training and higher-order thinking outcomes // International Journal of Educational Technology in Higher Education. – 2024. – Vol. 21, № 2. – P. 45–63.

Khan R., Ahmad N. Impact of ChatGPT as a formative feedback tool on ESL academic writing skills // Smart Learning Environments. – 2023. – Vol. 10, № 31. – P. 1–18.

Oregon State University E-Campus. Bloom’s taxonomy revisited – artificial intelligence tools: faculty guide. – 2024. – Mode of access: https://ecampus.oregonstate.edu. – Accessed: 05.06.2025.

Jackson B. Higher-order prompting: applying Bloom’s revised taxonomy to the age of AI // Scholarship of Teaching and Learning in the East. – 2025. – Vol. 4, № 1. – P. 23–38.

Chen Q., Lee S. Human–AI collaborative writing strategy effects on EFL argument essays // Computer Assisted Language Learning. – 2025. – Vol. 38, № 6. – P. 589–607.

Rahman J., Lim W. Meta-analysis of ChatGPT in L2 writing instruction // International Review of Research in Open and Distributed Learning. – 2024. – Vol. 25, № 3. – P. 120–139.

Smith T., O’Connor D. Triad of artificial intelligence, Bloom’s taxonomy and critical assessment literacy // Education and Information Technologies. – 2025. – Vol. P. 4115–4134.

Pérez L., Santos V. AI-resistant assessments in higher education: practical insights from the Global South // Frontiers in Education. – 2024. – Vol. 9. – Article 1499495. – P. 1–17.

Ali M., Zhang Y. Evaluating ChatGPT in EFL writing assessment through G-theory // Humanities & Social Sciences Communications. – 2024. – Vol. 11. – P. 1–13.

Brown E. Exploring the impact of AI on critical thinking development in ESL settings. – Rochester, NY: SSRN, 2025. – 28 p.

Bloom B. S. Taxonomy of educational objectives. Handbook I: Cognitive domain. – New York: David McKay, 1956. – 207 p.