Jul 2026· Life Science· Vol 7, pp. 8· 0 citations· 23 references
TL;DR
Although foundational AI literacy domains were generally well developed, students demonstrated notably lower scores in advanced domains, particularly AI creation.
Abstract
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
Nursing students had a wavier level of artificial intelligence literacy of knowledge, attitude and practice and its application in nursing learning, which foster effective integration of artificial intelligence in nursing education.
Haider Mohammed Majeed, Ali Hussein Alek Al-Ganmi, Ali Dhahir Abdulyemmah et al.· F1000Research· 0 citations
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.
Waghachavare Vivek B., Dhobale Randhir V., Gore Alka D. et al.· International journal of com...· 0 citations
Background: Artificial intelligence (AI) is increasingly being used in medical education, offering opportunities for personalized learning, rapid access to information, and support for academic activities. However, concerns regarding accuracy, overdependence, and reduced critical thinking remain.
Objectives: To assess the perceptions, attitudes, perceived benefits and concerns regarding the use of AI tools among undergraduate medical students.
Methods: A cross-sectional study was conducted among 767 undergraduate medical students at a tertiary care teaching institution in Bharuch, Gujarat, India, from January to March 2026. Students from all MBBS years who provided informed consent were included. Data were collected using a pre-tested, semi-structured questionnaire administered through Google Forms. Descriptive statistics were used to summarize the findings as frequencies and percentages.
Results: Among 767 participants, AI use was reported daily by 207 (27.0%) students, on a few days per week by 282 (36.8%), and occasionally or rarely by 278 (36.2%). ChatGPT was the most commonly used AI tool reported by 698 (91.0%) students, followed by Google Gemini 398 (51.9%). The most common academic purpose of AI use was clarifying difficult concepts, reported by 561 (73.1%) students, followed by obtaining quick summaries or notes 460 (60.0%). AI was considered very helpful for understanding concepts by 445 (58.0%) students, while 515 (67.1%) reported faster learning. Nearly half 367 (47.8%) supported integrating AI into medical teaching. However, inaccurate information 334 (43.4%), reduced critical thinking 327 (42.6%), and overdependence 252 (32.8%) were major concerns.
Conclusions: AI tools are widely used and positively perceived by medical students. Structured and responsible integration of AI into medical education may maximize its benefits while minimizing potential risks.
Keywords: Artificial Intelligence, ChatGPT, Medical Education, Medical Students
Vaishali Patel, Vallari Jadav, Kuntal Patel· International journal of sci...· 0 citations
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.
M. Çil, Berna Eren Fidancı, D. Yildiz· Journal of Education and Res...· 0 citations
Artificial intelligence (AI) is increasingly influencing dental education, clinical decision-making, diagnostics, and treatment planning. However, cohort-level differences in AI-related perceptions and use among dental students from consecutive academic years remain insufficiently explored, particularly among international students enrolled in English-language dental programs.
This exploratory study aimed to describe and compare AI-related perceptions, usage patterns, perceived benefits, concerns, and educational expectations between two independent cohorts of third-year undergraduate dental students surveyed in 2025 and 2026 using an identical questionnaire.
Two anonymous cross-sectional questionnaire surveys were conducted among independent cohorts of third-year undergraduate dental students enrolled in an English-language dental medicine program. The same questionnaire was administered in both years. The 2025 cohort included 109 respondents, and the 2026 cohort included 92 respondents. Collected demographic variables included gender, age, and country of origin. Categorical variables were compared using chi-square tests, and ordinal responses were analyzed using Mann–Whitney U tests. Because no primary outcome was prespecified, all inferential analyses were considered exploratory. The Holm step-down procedure was applied across the reported inferential tests to address multiple testing, and statistical interpretation was based on Holm-adjusted P values.
A total of 201 students participated. A higher proportion of the 2026 cohort reported frequent self-reported AI use from 22 of 109 students (20.2%) in 2025 to 27 of 92 students (29.3%) in 2026, while “rarely or never” responses decreased from 35 of 109 students (32.1%) to 19 of 92 students (20.7%). In unadjusted analyses, AI-use frequency differed between the cohorts (Mann–Whitney U = 4243.5; unadjusted
P
=.042;
r
=.14), and the distribution of perceived benefits also differed (χ²₃=8.27; unadjusted
P
=.041; Cramér’s V=0.20). However, both effect sizes were small, and neither comparison remained statistically significant after Holm correction (adjusted
P
≈.82 for both). Familiarity with regulations and legal guidelines remained limited: 68 of 109 students (62.4%) in 2025 and 46 of 92 students (50%) in 2026 reported being “not familiar” with such guidelines. Perceived institutional preparedness remained low, with 69 of 109 students (63.3%) in 2025 and 62 of 92 students (67%) in 2026 reporting that their institution did not provide sufficient AI-related training.
Descriptively, the 2026 cohort reported more frequent AI use and more often identified treatment planning as the principal perceived benefit of AI. These small cohort-level differences did not remain statistically significant after adjustment for multiple testing and should be interpreted as exploratory rather than confirmatory evidence of temporal change. Ethical, legal, and institutional training gaps were evident in both cohorts, supporting the need for structured AI literacy, regulatory awareness, and clinically oriented AI training within dental curricula in Bulgaria.
V. Stefanova, K. Zhekov· BMC Medical Education· 0 citations
Background: Dentistry is increasingly adopting AI technology; however, the preparedness of dental students for embracing the technology is still poorly known.
Objective: To examines the perception, attitude, and knowledge of the fourth-year dental students at Islamabad about the application of AI technology in dentistry and to evaluate the understanding of AI and its dental applications among final?year undergraduate dental students in a multi?center setting.
Methods: This cross-sectional survey was conducted from March to July 2025 including 165 Bachelor of Dental Surgery Final year students. After seeking ethical approval and informed consent, Participants were recruited using stratified random sampling with equal allocation from five dental institutions located in Islamabad. Data were collected using questionnaire consisting of 19 items, using a 5-point Likert scale. Statistical analysis was performed with SPSS version 26 including descriptive statistics and inferential tests i.e independent samples t?test (Welch's correction applied where variances were unequal) and one?way ANOVA. Effect sizes (Cohen's d) were calculated for significant t-test results. Assumptions of normality and homogeneity of variance were verified prior to ANOVA.
Results: 73.3% female participants showed strong familiarity with the AI concept (mean 4.36±0.87) but only moderate understanding of machine learning (3.36±1.09) and deep learning (3.27±1.10). Ethical concerns scored the lowest (2.98±1.02). Attitudes were predominantly positive; the highest agreement was for willingness to integrate AI into practice (3.95±0.81) and interest in AI training (3.92±0.80). Males demonstrated significantly higher total knowledge (23.25±2.94 vs 21.21±3.50, p=0.001) and more favorable attitudes (51.20±8.72 vs 48.46±5.73, p=0.047) than females. No statistically significant inter?institutional differences were observed.
Conclusion: Final?year dental students in Islamabad have basic knowledge and an optimistic attitude towards AI. However, deficiencies in technical and ethical knowledge, along with gender?related discrepancies, support the need to incorporate AI education into the dental curriculum.
M. Ali, Muhammad Talha, Sohaib Ahmad Zamir et al.· Proceedings· 0 citations
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