ARTIFICIAL INTELLIGENCE USE AND PERCEPTIONS AMONG NURSING STUDENTS: A CROSS-SECTIONAL STUDY

TAKA, Ilda and HASALLA, Elona and SULA, Albana and BAHITI, Blerina and HIDA, Rajmonda and BANI, Blerina (2026) ARTIFICIAL INTELLIGENCE USE AND PERCEPTIONS AMONG NURSING STUDENTS: A CROSS-SECTIONAL STUDY. In: INTERNATIONAL CONFERENCE “FROM RESEARCH TO APPLICATION”, 20 May, 2026.

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Abstract

Introduction: Artificial intelligence is being increasingly integrated into education and healthcare, offering innovative opportunities to improve the learning process, the understanding of clinical cases, and the self-confidence of students. However, it remains necessary to assess nursing students’ perceptions of AI and its impact on their academic and professional development. The aim of the study was to assess the use of AI, students’ perceptions of it, and its impact on academic performance and professional preparation among nursing students. Methods: A descriptive cross-sectional study was conducted at the Faculty of Medical Sciences in Elbasan. Data were collected through a structured online questionnaire assessing demographic characteristics, AI use, perceptions, and its impact. The data were analyzed using SPSS 23.0, including descriptive statistics, the chi-square test, and crude odds ratios (COR). Results: A total of 279 students participated in the study. Most of them (83.9%) reported using AI, mainly for information searching (92.3%) and understanding lectures (41%). Virtual assistants such as ChatGPT were the most commonly used tools (78.2%). Academic average was a factor significantly associated with AI use, whereas place of residence and cycle of study did not show significant associations. Students reported a moderate impact on understanding lectures and exam preparation, but a limited impact on practical skills, critical thinking, and empathy. Conclusions: AI represents an effective supportive tool in nursing education by improving theoretical understanding and academic efficiency. However, its impact on human competencies remains limited. In order to optimize its benefits and prevent dependency, a structured and ethical integration is needed.

Item Type:	Conference or Workshop Item (Paper)
Subjects:	Q Science > Q Science (General)
Divisions:	Faculty of Law, Arts and Social Sciences > School of Social Sciences
Depositing User:	Unnamed user with email zshi@unite.edu.mk
Date Deposited:	10 Sep 2026 11:28
Last Modified:	10 Sep 2026 11:28
URI:	http://eprints.unite.edu.mk/id/eprint/2381

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