ArticleVeterinary medicine and science2026
From Tradition to Future in Veterinary Public Health Education: Students' Attitudes, Anxiety and Experiences With AI-Supported Learning.
Article in Veterinary medicine and science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundArtificial intelligence (AI) has the potential to reshape learning processes, especially through tools such as ChatGPT.
objectivesThis study aims to evaluate veterinary students' attitudes towards AI-supported veterinary public health education applications, their anxiety levels and their experiences regarding the education process.
methodsThe study adopted a mixed method design in which quantitative and qualitative methods were used together. The study was conducted with final-year veterinary students (n = 60) enrolled in the Veterinary Public Health course. This study consisted of four phases: (1) the Artificial Intelligence Anxiety Scale (AIAS) was administered as a pre-test, (2) traditional face-to-face training was given, (3) the same topic was repeated with a ChatGPT-based AI-supported exercise and (4) after the trainings, the AIAS was administered again and post-test was conducted and a questionnaire consisting of closed and open-ended questions was administered to the students. Factor analysis revealed that the scale had high internal consistency (Cronbach's α > 0.90).
resultsAnalysis of the scale scores revealed that veterinary students exhibited moderate anxiety towards AI and that AI-focused education did not significantly alter this anxiety in the short term. In the content analysis of qualitative data, students stated that they benefited from the aspects of AI such as fast access to information, practicality and time-saving; the same time, they expressed concerns about ethical concerns, information reliability and professional role change.
conclusionOverall, the findings indicate a duality in students' potential attitudes towards AI. These findings indicate the applicability of AI-based educational practices in the context of veterinary public health education and point to the need for multidimensional evaluation of student attitudes.
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