Clinical Research Directory

The Effect of Simulation-Based ECG Training on ECG Reading Skills of Nursing Students

Accurately analyzing ECG rhythms is a critical competency for nursing students. However, many students fail to achieve an adequate level of knowledge and skill in this area. Therefore, simulation-based learning approaches and innovative, interactive teaching strategies can be effective in improving students' ECG interpretation skills. Furthermore, continuous professional education and hands-on experiences are crucial to ensure the sustainability of these competencies in clinical practice. This study is designed as a randomized controlled trial to determine the effect of simulation-based education on the ECG reading skills of nursing students. The study sample is planned to consist of 60 participants, with 30 in the intervention group and 30 in the control group. Data collection tools will include the Participant Information Form, the ECG Knowledge Test, and the Simulation-Based Learning Evaluation Scale. After administering pre-tests, students will be randomly assigned to the intervention and control groups using a simple randomization method. Both groups will receive ECG training. Following the training, students in the intervention group will receive hands-on, simulation-based ECG training in a simulation lab. In contrast, students in the control group will reinforce their ECG knowledge and skills through interactive games developed using Web 2.0 tools such as Wordwall and Nearpod. After the training, both groups will be tested, and a post-test will be administered in the fourth week to evaluate learning retention and knowledge permanence. As a result of this study, it will be determined whether simulation-based education is more effective than traditional digital methods in enhancing nursing students' ECG knowledge and skill levels.

The Effect of Artificial Intelligence-Supported Intramuscular and Subcutaneous Injection Training on Nursing Students

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.