Preparing Generation Z of Health Professions for Artificial Intelligence Revolution Through Hacking Education: An Interventional Study.

BACKGROUND AND AIMS

The integration of artificial intelligence into healthcare is rapidly expanding, yet formal AI education for health profession students remains limited. Generation Z students, as digital natives, require innovative instructional methods tailored to their learning preferences. This study aimed to investigate the effectiveness of an innovative course based on hacking education for Z-generation health profession students about artificial intelligence.

METHODS

This was a single-group pre- and post-test interventional study conducted with 81 health profession students. Educational needs were identified through an expert panel. A 100-h flipped classroom course incorporating group discussions, communities of practice, peer teaching, and gamification was delivered. Pre- and post-course questionnaires assessed students' familiarity with key AI concepts.

RESULTS

Post-course assessments showed a significant improvement in students' familiarity with AI-related domains, including programming languages ( < 0.001), machine learning ( < 0.001), AI applications in healthcare ( < 0.001), data science ( < 0.001), image processing ( < 0.001), deep learning ( < 0.001), neural networks ( < 0.001), and statistics ( < 0.001).

CONCLUSION

The hacking education-based AI course effectively enhanced students' AI competencies. Given the increasing role of AI in healthcare, integrating structured AI training into medical curricula is essential to prepare future healthcare professionals for AI-driven clinical environments.