AI-Assisted Writing: How Gemini Reduces Cognitive Load among ESL Learners

Writing in a second language imposes a heavy dual-task burden, causing extraneous cognitive overload that hinders higher-order composition goals. This study investigated the efficacy of Gemini in reducing intrinsic, extraneous, and germane cognitive load among English as a Second Language (ESL) learners. Data were collected through a quantitative survey design using a 10-section questionnaire administered to 135 respondents across different genders and academic disciplines (science and technology, and social sciences). The results show that Gemini significantly reduces the unnecessary cognitive load, especially in terms of translation (M = 4.16) and linguistic support. Moreover, the tool improves relevant loads by increasing student engagement (M = 4.01) and stimulating critical thinking through the evaluation of different perspectives. Similar cognitive benefits were observed for all demographic characteristics. Ultimately, Gemini works as a “cognitive partner” that takes learners from localised error monitoring to the overall rhetorical techniques. This study promotes the incorporation of AI-assisted scaffolding into ESL curriculum to shift writing teaching from basic mechanical accuracy to critical assessment and creative synthesis.

Gemini AI, ESL Writing, Cognitive Load Theory, Generative AI

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