The complexity of healthcare services and technological advances today have necessitated the adoption of innovative approaches in nursing education. Among these innovative approaches, artificial intelligence (AI) has established itself as a technology that is increasingly present in nursing education processes, offering a supportive, personalized, and interactive learning experience. AI's contributions to nursing students' acquisition of fundamental competencies such as clinical decision-making, skill development, and critical thinking are rapidly increasing. Especially in high-risk, invasive, and clinically skill-intensive applications, AI-supported educational models both enhance learning quality and support patient safety. Intramuscular and subcutaneous injections are among the basic invasive skills that nursing students must learn. These applications require a high level of cognitive and psychomotor competence from students. Incorrect injection practices can lead to complications such as drug absorption problems, nerve damage, hematoma, or infection, making it critically important to teach these skills correctly and safely. In this context, AI-supported education systems stand out as an effective tool for teaching injection skills. Artificial intelligence-based chatbots provide students with both theoretical knowledge and practical guidance. For example, before injecting a muscle group, a student can learn about the anatomy of the muscle, determine the correct angle, and remember precautions against potential complications through the chatbot. Artificial intelligence also reinforces the learning process by instantly answering students' questions, preventing the acquisition of incorrect information. Recent studies emphasize that AI-supported learning tools positively influence students' attitudes toward learning, increasing their motivation and academic satisfaction levels. Accordingly, the integration of AI-based technologies in the process of training future nurses is no longer an option but a necessity. Particularly in complex and delicate skills such as intramuscular and subcutaneous injections, AI-supported chatbots can facilitate student learning, increase skill accuracy, and support clinical safety. Therefore, it is crucial for nursing education programs to combine artificial intelligence technologies with pedagogical foundations to provide student-centered, safe, and effective learning environments.
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AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.
Objective Structured Clinical Examination score
Timeframe: A week after IM and SC injections training in control group; a week and a month after IM and SC training in study group
Clinically Oriented Reasoning Exam score
Timeframe: A week after IM and SC injections training in control group; a week and a month after IM and SC training in study group
Subcutaneous and Intramuscular Injection Theoretical Knowledge Pre-Test
Timeframe: Before IM and SC injections training in control and study groups.
Subcutaneous and Intramuscular Injection Theoretical Knowledge Post-Test
Timeframe: A week after IM and SC injections training in control and study groups; a month after IM and SC training in only study group.
Productive Artificial Intelligence Usage and Competence Scale Score
Timeframe: A month after IM and SC injections training in only study group.