Mixed-methods analysis reveals AI's impact on higher-order thinking and metalinguistic awareness among ESL learners.
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.
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Jurayeva Zuhra (2025) studied this question.
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