Nine in Ten Nursing Students in Kuwait Now Use AI to Write in English, Study Finds

Generative artificial intelligence has become an almost universal companion to academic writing among nursing and health sciences students in Kuwait, according to a new mixed methods study conducted at the Public Authority for Applied Education and Training (PAAET). Of 241 undergraduate students surveyed, 94.6 percent reported having used generative AI tools such as ChatGPT, Gemini, Claude, and Copilot, and 83.4 percent said they used them for academic purposes at least occasionally. The findings, published in Discover Education, offer one of the most detailed portraits yet of how future healthcare professionals in an English-medium instruction (EMI) context are weaving large language models into the daily mechanics of learning.

The study, carried out by Abdullah M. Alazemi of PAAET’s Language Center, used a convergent mixed methods survey design, collecting quantitative and qualitative data simultaneously through a single questionnaire administered in Arabic. The quantitative strand captured patterns of use, perceived benefits, and concerns on five-point Likert scales, while six open-ended questions invited students to describe in their own words how AI shaped their writing practices. The two datasets were analyzed separately, using descriptive statistics in SPSS and reflexive thematic analysis respectively, and then compared for convergence. The subscales showed good internal consistency, with Cronbach’s alpha values of 0.85 for AI use, 0.90 for perceived benefits, and 0.77 for concerns.

What the numbers reveal is striking in its consistency. Students reported using AI most often for language-related functions: 72.5 percent used it to correct grammar, 73.1 percent to enhance vocabulary, and 75.3 percent to express ideas more clearly in English. Meanwhile, 65.3 percent turned to AI for idea generation, 66.7 percent for summarizing academic materials, and 73.2 percent agreed that AI helped them complete writing tasks more efficiently. In other words, the technology is not primarily a shortcut for producing finished assignments; it functions across the entire arc of the writing process, from brainstorming and outlining through paraphrasing, drafting, and final revision.

The qualitative strand added texture to these patterns. Four interrelated themes emerged from the thematic analysis: AI as a facilitator of English academic writing, AI as a cognitive and academic efficiency tool, AI as a confidence-building resource, and students’ active negotiation of the opportunities and risks of AI use. Many students described a familiar frustration that AI helped resolve: knowing what they wanted to say but struggling to express it in academic English. One participant wrote that AI had helped them learn new vocabulary, formulate sentences more clearly and professionally, and increased their confidence in writing. Another described how it enabled faster organization of ideas and easier review of mistakes.

That efficiency dimension deserves particular attention. Students described using AI to condense long searches, summarize dense lectures, simplify complicated material, and organize information into manageable forms. One participant noted that AI had shortened a long journey of searching, reviewing, and writing. From a cognitive standpoint, this suggests students perceive the technology less as a ghostwriter and more as a form of cognitive support, a tool that reduces the extraneous linguistic and organizational load of academic work so that attention can shift toward understanding disciplinary content. The study interprets these practices through sociocultural learning theory, which treats tools as facilitators of participation in learning activities, positioning AI as a kind of linguistic scaffolding within students’ zone of proximal development.

Perhaps the most psychologically significant finding concerns confidence. Writing in a second language is notoriously anxiety-inducing, and 62.3 percent of participants believed AI increased their confidence in writing English, while 61.6 percent agreed it reduced writing-related anxiety. Students described having access to immediate, judgment-free feedback at any hour, something traditionally available only from teachers, peers, or writing centers during limited windows. The study draws on self-efficacy theory to interpret this pattern: as students perceived themselves becoming more capable of producing grammatically correct, coherent texts, their willingness to engage with writing tasks grew. Confidence, in these accounts, emerged not from the mere existence of AI but from a perceived reduction in the linguistic barriers that made writing feel daunting.

Yet the students themselves were far from uncritical. The fourth theme revealed a sophisticated awareness of AI’s risks. Approximately 63.4 percent of participants expressed concern about overreliance on AI tools, 58.6 percent believed AI may weaken independent writing skills, and 72.4 percent agreed that AI-generated information may sometimes be inaccurate. Some students reported deliberately reviewing, evaluating, and verifying AI outputs before using them, while others worried that habitual reliance might erode their ability to recall vocabulary or construct grammar independently. One participant cautioned that excessive dependence may reduce a student’s ability to think and solve problems independently, while another insisted that AI should serve as a supporting tool rather than a replacement for personal effort.

Notably, students intertwined ethical concerns with educational ones. Beyond worries about violating academic integrity policies, participants feared that heavy AI use would cost them opportunities to develop their own writing skills and critical thinking. The study found that 64.2 percent of participants reported concerns about the ethical use of AI in academic writing. Students effectively drew a line between responsible use, checking information, revising AI suggestions, and using AI to support understanding, and irresponsible use, copying content without verification or outsourcing thinking entirely. The issue, as they framed it, is not whether AI should be used but how.

The convergence between the quantitative and qualitative strands was strong, with no major contradictions between them. The survey data mapped the breadth of use and concern, while the open-ended responses explained the underlying experiences of language support, efficiency, and confidence. This alignment strengthens the study’s central claim: generative AI has moved beyond being an occasional educational technology and is now embedded in students’ everyday writing practices, functioning simultaneously as language tutor, cognitive assistant, and psychological buffer.

The implications reach well beyond Kuwait. The author argues that institutions should respond not with blanket prohibitions but with AI literacy frameworks that teach students to question, evaluate, and refine machine-generated content. In nursing and health sciences education specifically, guidance must address field-specific hazards, including fabricated or inaccurate clinical information and threats to patient confidentiality, and should encourage verification of any health-related content AI produces. The study’s limitations warrant caution: it was conducted at a single institution using convenience sampling and self-reported perceptions, the predominantly male sample may limit transferability, and no objective writing performance data were collected. Whether AI-assisted confidence translates into genuine long-term gains in writing competence remains an open question, one the author argues demands longitudinal research. What the study establishes firmly is that the debate over AI in higher education has shifted decisively from whether students will use these tools to how educators can ensure they use them well.

Subject of Research: Generative AI use for English academic writing among nursing and health sciences students in Kuwait

Article Title: Generative artificial intelligence use for academic writing in English among Kuwaiti nursing and health sciences students in a mixed methods study

Article References: Alazemi, A. M. (2026). Generative artificial intelligence use for academic writing in English among Kuwaiti nursing and health sciences students in a mixed methods study. Discover Education, 5(1), Article 1159. https://doi.org/10.1007/s44217-026-02297-w

Image Credits: AI Generated

DOI: 10.1007/s44217-026-02297-w

Keywords: generative AI, academic writing, nursing education, health sciences, English medium instruction, higher education, Kuwait, ChatGPT, mixed methods, AI literacy, self-efficacy, writing anxiety