Artificial Intelligence-Based Applications for Improving Learning Outcomes of Cardiovascular Tech Students

Abstract

This paper examines how Artificial Intelligence (AI) can be applied to improve the
classroom performance of cardiovascular technology (CVT) students. As the cardiovascular
diagnostics and interventions become more complex and sophisticated, the traditional teaching
approach usually cannot provide students with the necessary skills. AI-powered tools like intelligent
tutoring systems, predictive analytics, virtual simulations, and adaptive learning platforms give
students personalized, interactive, real-time feedback that can greatly improve participation and
performance. This study highlights several practical uses of AI in cardiovascular education and
suggests a framework for bringing these technologies into the curriculum. Both quantitative and
qualitative results show that students gained a better understanding of concepts, became more
accurate in performing procedures, and improved their retention of knowledge. The paper also
addresses the limitations of using AI in health education, its impact on real-world practice, and the
future potential of these technologies in training healthcare professionals.