Skip to content
Open access

Generative artificial intelligence use in nursing bachelor's theses: A qualitative study of students' technology integration and learning.

Jul 2026 · Nurse Education Today · Vol 167, pp. 107263 · 0 citations · 41 references
Medicine

TL;DR

GenAI significantly shapes how nursing students construct knowledge and develop academic practice in the BT, and may support autonomy and critical thinking, provided its use remains reflective, ethically grounded and aligned with the discipline's educational objectives.

Abstract

Aim

To explore nursing students' generative artificial intelligence (GenAI) related practices during Bachelor Thesis (BT) preparation and to analyse their levels of technology integration, links with learning, and perceived barriers and facilitators.

Methods

This descriptive qualitative study adopted a constructivist approach. Participants were 66 final-year nursing students who reported using GenAI tools during the preparation and defense of the BT. Data were collected using a qualitative open-ended questionnaire and analysed using thematic analysis. Findings were interpreted using the SAMR model (Substitution, Augmentation, Modification and Redefinition).

Results

GenAI use spanned different levels of technology integration. At the Substitution and Augmentation levels, it primarily supported language correction, refinement of academic tone, and reference management. At the Modification and Redefinition levels, it supported critical reflection, knowledge reorganisation, integration of complex information, and co-creation of student-produced artefacts, with reports of a transformed learning experience. Nevertheless, students expressed concerns about the reliability of the information generated, the need for verification, and the ethical implications of using these tools.

Conclusions

GenAI significantly shapes how nursing students construct knowledge and develop academic practice in the BT. When integrated more fully, it may support autonomy and critical thinking, provided its use remains reflective, ethically grounded and aligned with the discipline's educational objectives. These findings have implications for curriculum design, academic supervision and pedagogical approaches that encourage responsible GenAI use in nursing education.

Read PDF

Similar papers

Review Open access Aug 2026

Nurses' and Nursing Students' Experiences With Generative Artificial Intelligence in Educational and Clinical Settings: A Scoping Review

Thematic analysis revealed that various factors underpinning their attitudinal, normative, and control beliefs are critical determinants of nurses' and students' overall experiences with GenAI and their intentions to use GenAI technologies.

Ming Wei Jeffrey Woo, Adrian Heng Tsai Tan · 0 citations
Review Open access Jul 2026

A Meta-synthesis of nursing students’ experiences with generative artificial intelligence-assisted learning

Nursing students’ experiences with generative AI are shaped by both the opportunities and challenges associated with its use in learning, highlighting the need for nursing educators to strengthen students’ AI literacy, critical thinking, and ethical awareness.

Shanshan Du, Sha Wang, Feng-ming Yan et al. · 0 citations
Review Aug 2026

Mapping the evidence on generative artificial intelligence for higher-order thinking skills in nursing students: A scoping review.

The dual role of GenAI in HOTS development indicates that nursing education should integrate GenAI judiciously, and efforts should focus on improving the quality of human-AI collaboration, with particular attention to humanistic care, thereby helping students positively reshape their professional perceptions.

Yan Ning, Shanshan Sun, Yingkun Lu et al. · 0 citations
Review Open access Aug 2026

Nursing students' critical engagement with generative AI in evidence-based practice education: A qualitative descriptive study.

It is suggested that structured AI-comparison tasks offer the opportunity to develop AI and digital health literacy in nursing students and offer practical guidance for educators seeking to support graduates to be AI-critical and well-equipped to leverage the efficiencies of these tools.

Ashlyn Sahay, Adeniyi O Adeleye, Katrina Lane‐Krebs · 0 citations
Review Open access Aug 2026

Artificial Intelligence in Nursing Education: A Scoping Review of Academic Perspectives.

Nursing academics appear to adopt AI selectively, prioritising preservation of core professional values while embracing applications perceived to enhance, rather than replace, educational practice, providing evidence for nursing education programs globally regarding faculty development, institutional policy frameworks,...

Natasha Hawkins, Anthea Fagan, Yumiko Coffey et al. · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.