Empirical Study on Generative Artificial Intelligence-Driven Project-Based Learning in Health Big Data Course Education

The growth of the health big data that is exponential in nature is going to require new opportunities of education preparing future medical workers and data scientists. This elaborate empirical research focuses on the disruptive power of generative artificial intelligence (GenAI) technologies in transforming project-based learning (PBL) pedagogy in teaching health big data courses. We created and deployed an advanced GenAI-based learning system that uses GPT-4, model-based on domain-specific health knowledge, and intelligent tutoring systems to develop individualized and adaptive learning situations. The high standard of our experimental inquiry was established by means of 120 undergraduate respondents across 4 academic institutions during the course of 2 consecutive semesters, through the application of the randomized controlled trial methodology and a thorough pre- and post-assessment design. The PBL framework that was equipped with GenAI showed the considerable change in various learning aspects: There was a 34-percent increment in student engagement, 28-percent increment in critical thinking capacities, 41-percent improvement in health data analytics technical proficiency, and 31-percent improvement in problem-solving capabilities. Also, the instructor workload decreased by 45% with no drop in the superior educational quality and a 89% student satisfaction level. Such empirical outcomes are the convincing evidence that generative AI technologies have a potential to successfully enhance the traditional pedagogy methods and generate the scalable, individualised learning environments and, therefore, a bridge between theoretical knowledge and practical skills of working with complex health care data.