Harnessing Artificial Intelligence: A Paradigm Shift in Health Professions Education
by Andrew Bates, PharmD, University of Mississippi Medical Center, PGY1 Patient Care Resident
Artificial intelligence (AI) is rapidly transforming various fields, including healthcare and education. There are several ways that health professions education might benefit from incorporating AI into its curriculum. This integration offers some advantages that can significantly enhance the learning experience. The conversation around AI in education is ongoing and complex, but it is clear that this technology has the potential to revolutionize how we train future health professionals.
One of the potential benefits of AI in health professions education is to create personalized learning experiences. AI systems can analyze students' performance and learning styles and then tailor educational content to the student’s individual needs.1 For instance, AI-driven platforms can identify content areas where students struggle and provide additional resources or practice problems to help them improve. This personalized approach can, at least in theory, lead to a deeper understanding of complex concepts and better overall academic performance. A recent systematic review of the literature described the use of AI’s to design adaptive learning systems and personalizing tutoring to each student.2
AI can also offer students practical experience through simulations. AI-powered virtual simulations can mimic real-world healthcare scenarios, such as patient interactions, interprofessional teams, and decision-making scenarios. These simulations would allow students to practice and refine their skills in a controlled environment without the risk of real-world consequences. This hands-on simulated experience could help build confidence and competence before entering clinical settings. This could augment the existing practice of using standardized patients for learning exercises and structured clinical examinations, but potentially at a much lower cost.
AI can significantly enhance the efficiency of educational processes. For instance, AI can automate administrative tasks, such as grading and scheduling, allowing faculty to focus more on teaching and mentoring students. In 2021, AI software PackBack was used to grade discussion posts in graduate classes.3 Using AI in this way resulted in more revision and deeper reflections (based on student comments) as well as a higher overall satisfaction rate without making the class seem more difficult.3 By reducing the administrative burden on educators, AI enables a more interactive and engaging learning environment. The increased efficiency can also lead to more timely feedback to students, helping them to quickly identify and address their weaknesses. When reviewing engagement data, AI systems were able to identify students at higher risk of failing courses within the first month of school, and then create a customized learning plan.4 These students were identified based on a score derived from attendance and assignment completion, and the system then alerted tutors to reach out to the student. This kind of support can accelerate learning and improve overall educational outcomes.
Ethical and privacy issues are also important considerations, but these can be addressed with robust data governance frameworks. AI systems often require large amounts of data to function effectively, raising concerns about the security and confidentiality of student and patient information. Ensuring that AI applications comply with privacy laws and ethical standards is paramount. The issues of privacy and avoiding bias in the algorithm must be planned out before implementation to ensure the benefits of AI without endangering student welfare5.
Another concern is the significant investment required to implement AI. Developing and maintaining AI-driven educational tools will be expensive (at least initially), and institutions must also invest in training faculty to use these technologies effectively. This may require educational institutions to slowly implement and expand AI in order to overcome the financial barriers.
Keeping up with rapid technological advancements is essential but manageable with a proactive approach. AI technology evolves quickly, and educational institutions must continuously update their systems and curricula to stay current. This need for continual updates can strain resources, but it also ensures that students receive the most up-to-date and relevant education possible.
Ensuring equitable access to AI technology in education must also be considered. Smaller schools or those in rural areas may lack the infrastructure to support AI integration, widening the gap between institutions with different levels of resources. However, initiatives to promote equity in educational technology can help bridge this gap. By advocating for funding and support for under-resourced institutions, the education community can work towards providing all students and their faculty with access to AI tools.
Integrating AI into health professions education offers numerous benefits, such as personalized learning, practical simulations, and enhanced efficiency. While challenges like potential over-reliance on technology, ethical and privacy concerns, and resource requirements exist, these can be mitigated through careful planning and robust frameworks. For health professionals, it is essential to advocate for the thoughtful integration of AI to harness its full potential and improve the training and preparedness of future professionals. With careful consideration and balanced integration, AI can be a powerful tool, providing students with the skills and knowledge they need to succeed. By staying informed and engaged with these developments, we can help shape the future of education in a way that benefits everyone.
References:
1. Rutner SM, Scott RA. Use of artificial intelligence to grade student discussion boards: An exploratory study. Information Systems Education Journal 2022; 20(4): 4-18.
2. Zawacki-Richter O, Marín VI, Bond M, Gouverneur F. Systematic review of research on Artificial Intelligence Applications in higher education – where are the educators? International Journal of Educational Technology in Higher Education. 2019;16(1): 39.
3. Alsariera YA, Baashar Y, Alkawsi G, Mustafa A, Alkahtani AA, Ali N. Assessment and evaluation of different machine learning algorithms for predicting student performance. Computational Intelligence and Neuroscience. 2022;1:14151487.
4. Gray CC, Perkins D. Utilizing early engagement and machine learning to predict student outcomes. Computers & Education. 2019;131:22–32.
5. Nguyen A, Ngo HN, Hong Y, Dang B, Nguyen B-PT. Ethical principles for artificial intelligence in education. Education and Information Technologies. 2022;28(4):4221–41.