Meghan Reading Turchioe
Assistant Professor of Nursing
“Research synthesis through the visualization of health data and information” (N9550) is a course offered in the School of Nursing. It is required for all second-year PhD students at the School of Nursing and most students are nurses, but it is also open to other interested graduate students across the university. The course’s average enrollment is approximately 10 students. The course aims to provide a hands‐on introduction to delivering data visualizations to serve as a critical lens through which individual- and population-level health can be examined. The course design involves both didactic lectures focusing on concepts and case studies describing how to scope and manage complex data science projects, as well as lab work focused on gaining competency with data science/visualization tools and techniques.
Approach to teaching and learning in the age of AI
Currently, generative AI and its applications in healthcare are not covered in the PhD curriculum, creating a gap in knowledge for the future leaders of nursing science and practice. Typically, prior to entering the course, nurses typically have limited exposure to programming and report lower self-rated competency on coding assignments. We felt there were exciting opportunities to explore whether and how generative AI may further assist nurses in gaining the competencies they will require for their future work. Bloom’s Taxonomy of Learning, which orders cognitive skills by complexity, provided the conceptual basis for this work. Our goal was to provide the cognitive scaffolding needed to help our students engage in the higher-order thinking and cognitive skills at the top of the taxonomy through generative AI.
Course elements that evolved with the integration of AI
AI was integrated across our course. New learning objectives relating to generative AI were integrated into the syllabus. We created assignments in which students used ChatGPT and other generative AI tools to perform healthcare- and research-related case studies, asking them to reflect on strengths and weaknesses. Additionally, we randomized students to use generative AI for support completing course assignments on alternating weeks, creating a small experimental study, allowing us to begin studying the role of AI on learning.
Teaching students to leverage AI and develop their AI literacy
Leveraging AI and developing AI literacy were the main goals of our course redesign, which included two components: (1) a one-week module on generative AI (Aim 1), and (2) the inclusion of ChatGPT as a scaffolding tool to aid lab assignments throughout the semester (Aim 2). In Aim 1, we developed AI literacy by creating a one-week generative AI module in which we defined it and described its current and potential future applications in healthcare, including examples of appropriate and inappropriate applications. In the accompanying lab, students used ChatGPT to understand how they work and potential use cases for their application. To leverage AI, after introducing students to ChatGPT in the module, students were permitted to use ChatGPT as a tool to assist with writing and debugging code for assignments, as described above.
Lessons learned from teaching and learning with AI
Through mixed-methods evaluations of the course redesign, we gained important insights about how AI may be useful for teaching and learning. First, exposure to generative AI through example case studies, even in a brief laboratory assignment, can help students develop their opinions and expertise on the strengths and weaknesses of generative AI’s applications in healthcare. Second, ChatGPT and other generative AI tools are useful for novice students learning programming, particularly in “raising the floor” and ensuring all students were able to advance to higher levels of cognitive work. However, these tools may produce errors and should be used in conjunction with other educational tools.
Advice for colleagues on leveraging AI for teaching and learning
As AI models and capabilities rapidly evolve, it will be essential to continue exploring various uses of AI for teaching and learning purposes. Students are likely already using these tools. Rather than shying away, we should recognize that we have a unique opportunity to study how they can and should be used to facilitate student learning.