Artificial Intelligence Literacy and Educational Impact among Iraqi Nursing Students: A Cross-Sectional Survey

The Relationship Between Artificial Intelligence Literacy and Attitudes Toward Artificial Intelligence Among Nursing Students

The findings indicate that nursing students had generally positive levels of AI literacy and attitudes toward AI, and higher AI literacy was associated with more positive attitudes toward AI.

Determinants of medical students' attitudes toward artificial intelligence: a cross-sectional study and implications for medical education.

BACKGROUND Artificial intelligence (AI) has emerged as one of the most rapidly evolving technologies in recent years and is increasingly being integrated into healthcare, education, and everyday life. Examining university students' attitudes toward this technology is important for understanding their future professional orientations and adaptation to technological change. This study aimed to identify medical students' attitudes toward artificial intelligence and the determinants of these attitudes, and to develop educational implications for medical training based on the findings. METHODOLOGY This descriptive cross-sectional study was conducted between January 22 and May 28, 2025, among 198 final-year medical students at Pamukkale University Faculty of Medicine in Denizli, Türkiye. Data were collected using a Descriptive Information Form, which assessed students' sociodemographic characteristics and their knowledge and experiences regarding AI, and the General Attitudes toward Artificial Intelligence Scale (GAAIS, Turkish version). Since the negative subscale is reverse-coded, higher scores in both indicate more positive attitudes toward AI. Data were analyzed using SPSS v25 with descriptive statistics, Mann-Whitney U, Kruskal-Wallis, and multiple linear regression analyses. RESULTS The mean age of participants was 24.47 ± 0.98 years; 56.1% were female. A total of 74.2% of the participants reported general knowledge about AI, and 76.3% reported experience using AI in daily life. A total of 63.1% viewed AI developments positively, 69.7% believed AI changes work and daily life, and 52.0% felt emotionally unaffected by it. The mean positive attitude score was 45.01 ± 9.17, and the negative attitude score was 26.41 ± 6.22. Multiple linear regression analysis showed that positive attitudes toward artificial intelligence were significantly associated with father's education level (university vs. primary school), having an interest in technology, perceptions regarding developments in artificial intelligence, and the belief that AI has an emotional impact (p < 0.05). For the negative attitude subscale, only perceptions regarding developments in artificial intelligence were found to be significantly associated (p < 0.05). CONCLUSION Medical students demonstrated generally positive attitudes toward AI. Higher paternal education, technological interest, perceiving AI as emotionally influential, and evaluating AI developments positively were predictors of favorable attitudes. In addition, more positive evaluations of AI-related developments were also associated with higher scores on the reverse-coded negative attitude subscale, indicating lower negative attitudes toward AI. These findings suggest that students' attitudes toward AI are shaped not only by technological interest but also by perceptual factors related to AI. Therefore, integrating clinically oriented AI content and awareness-building activities into medical education may support the development of more balanced and informed attitudes toward AI.

Knowledge, Attitudes and Perception of Nursing Students about Artificial Intelligence in India

In recent times, nursing students have been utilizing artificial intelligence (AI) technology, as they perceive it boosts learning outcomes and academic performance and transforms several facets of healthcare. This study aimed to explore nursing students' knowledge, attitudes and perceptions concerning the adoption of AI in their academic and clinical areas. It applied an exploratory study design to cover the study population of all undergraduate students, including interns from selected private nursing colleges in Tamil Nadu, India (N = 440). A self-designed online questionnaire was distributed via Google Forms to the target population and 317 responded. The results showed that 81.3% were familiar with the term "AI" (81.3%). 76.3% recognized that AI would revolutionize the nursing field. Most nursing students consented that AI should be included in undergraduate (67.2%) and postgraduate (71.3%) nursing curricula. 77.9% perceived that AI would be helpful for their future career. A significant variation was observed in nursing students' knowledge, attitude and perception scores across age categories, but not for gender and year of study. This study concluded that female nursing students, especially those aged 17-19, demonstrated strong knowledge, an optimistic attitude and had a better perception of AI. The findings suggest that nursing students in India possess adequate knowledge about AI, indicating a positive perception that AI plays a transformative function in nursing education and practice, with a need for more focused training and integration into the curriculum.

A Study on the Knowledge and Attitudes regarding Artificial Intelligence among Medical, Dental, and Nursing Students from Sangli (Maharashtra), India

Healthcare students had unsatisfactory awareness of AI, and their overall attitude was negative, highlighting an urgent need for an integrated AI curriculum tailored to their actual needs.

Artificial Intelligence Literacy Among Undergraduate Dental Students: A Cross Sectional Study from a Single Academic Institute in Lahore

Objective: To assess AI literacy among undergraduate dental students using the domains of the Meta AI literacy scale. Also, the use of ethical consideration regarding AI, AI persuasion literacy and emotional regulation.Study Design: A cross-sectional study.Place and Duration of Study: The study was conducted at the Fatima Memorial Medical and Dental College, Lahore, Pakistan, from May 2025 to June 2025.Methods: Undergraduate students from all academic years were included using convenience sampling. The Meta AI Literacy Scale (MAILS), which consists of seven domains, was used to evaluate AI literacy. The Shapiro Wilk test was used to assess the normality of the composite scores. To assess the group differences across the demographics, the One-Way ANOVA and Kruskal–Wallis Test were used. Mann-Whitney U tests and independent t-tests were conducted to compare differences between genders.Results: A total of 160 undergraduate dental students (mean age 20.48 ± 1.90 years; 62.5% female) participated in the study. AI literacy varied across the seven MAILS domains, with higher scores in Use and Apply AI (mean: 5.39–6.55), Ethical considerations regarding AI (mean: 5.40–5.98), and AI persuasion literacy (mean: 5.94–6.30). On the other hand, the Create AI domain demonstrated the lowest score (mean 2.66–3.22). Students with increased self-rated computer skills were highly efficient in understanding AI, detecting AI, AI self-efficacy, and the practical use of AI (p < 0.05). The academic year was associated with the AI persuasion and Create AI domains (χ² = 8.50, P= 0.037), whereas no significant gender differences were identified. Correlational analysis showed a positive association between understanding AI and use and application of AI (r = 0.79).Conclusion: Although foundational AI literacy domains were generally well developed, students demonstratednotably lower scores in advanced domains, particularly AI creation. How to cite this: Gul M, Amin M. Artificial Intelligence Literacy Among Undergraduate Dental Students: A Cross-Sectional Study from a Single Academic Institute in Lahore. Life and Science. 2026; 7(3): 387-394. doi: http://doi.org/10.37185/LnS.1.1.955    

Professional Attitude among Nursing Students in AL-Hasahisa