Artificial Intelligence

John McCahan Medical Campus Education Conference Focused on AI In Health Sciences Education

Artificial Intelligence can be a significant tool for educators.

If you were a little late to the 21^st Annual McCahan Day keynote lecture on artificial intelligence, you would have encountered the sound of metal rings clanking on tabletops. You might have wondered if you’d accidentally wandered into a meeting of amateur magicians as more than 100 attendees, mostly PhDs, struggled to figure out the “magic” of a ring sliding down a metal chain suspended from the magician’s fingers that stops short of the tabletop, held by a knot that mysteriously appears at the last second.

This is not math, just a simple sleight of hand and the value is not in finding the answer, but in the process of discovery, said keynote speaker Thomas “TJ” McKenna, PhD, a clinical assistant professor of science education, program director of AI and Education, and director of the Center for STEM Professional Learning at Scale at BU’s Wheelock College of Education and Human Development.

McKenna is focused on how artificial intelligence can support, not replace, teacher expertise. His lecture, “Learning Endures, Tools Evolve: Teaching and Learning in the Age of AI,” made the case that decisions about AI should start with how people learn, not with what the technology can do.

Noting that some in his audience quickly turned to their phones for the answer, McKenna likened that to employing a robot to do your gym workout.

“You’re not going to get muscles. The work still happens, but it’s not me doing it, and it’s not me benefiting from it,” he said.

The John F. McCahan Medical Campus Education Conference is an annual two-day event highlighting research in health sciences education and held to honor McCahan, who served as associate dean for academic affairs at the medical school for three decades. This year’s theme focused on the use of artificial intelligence in health sciences education.  

AI use in education is often perceived as a monolithic entity, but McKenna said it is composed of different tools with varied purposes and outcomes. The architecture of an AI model – what it was built to answer and how it gets its answers – is itself a pedagogical choice, McKenna said, and faculty need to be involved in design and procurement decisions rather than serve as end users of choices made elsewhere.

McKenna, who received Boston University’s 2026 Gitner Family Award for Innovation in Teaching with Technology, speaks from experience as a designer. He has built AI coaching tools used by science educators in more than 33 states that demonstrate his central argument: design decides pedagogy. Some coaching tools provide answers only from expert-vetted curriculum knowledge, while other tools are built to sustain inquiry, coaching teachers and students to stay in the question to better understand its complexity and layers.

Think of AI as a moderator, a dialogue coach, a critic, and not just as an answer machine.”

TJ McKenna, PhD

“The educational unit of value moves away from a polished answer into something where you can feel comfortable staying in the question long enough for something deeper to emerge, and to be comfortable engaging, talking, arguing with people to get to those answers,” said McKenna. “Think of AI as a moderator, a dialogue coach, a critic, and not just as an answer machine.”

Caroline Brinkert, MS, CCC-SLP, a lecturer at BU’s Sargent College of Health & Rehabilitation Sciences, along with Benjamin Keating, PhD, David Farelo, PhD, and Erin Baumann, PhD, from BU’s Institute for Excellence in Teaching & Learning, discussed “Creating A Game Plan for AI in Teaching and Learning.” Through lectures, a case study and a roundtable discussion, they presented the TILT framework (Transparency in Learning and Teaching) as a tool to ensure that students understand the rationale behind assignments, how an assignment is relevant to their learning, what steps are needed to complete the assignment, and how the work will be evaluated. Brinkert’s case study used the AI Assessment Scale, supplemental to the TILT framework, to openly communicate with students about the role of AI in a given assignment and the rationale for accepted use. 

McCahan Day includes faculty, fellows and students from the Chobanian & Avedisian School of Medicine, Goldman School of Dental Medicine and School of Public Health. The first day of the conference was devoted to online presentations by educational AI vendors. The second day included lectures, workshops, vendor exhibits and awards presentations. Workshops included:   

• LLM’s Go Head-to-Head: Large Language Models vs. Legitimate Librarian Methods for Advanced Database Searching.
• When the Algorithm Disagrees: teaching Clinical Judgement in the Age of AI.
• Integrating Artificial Intelligence into Health Sciences Education: A Framework for Teaching and Learning.
• Funding Health Professions Education Innovation & Shipley Academic Innovation Fund.

Seven John McCahan Educator Awards were presented:

• Graduate Medical Sciences Faculty Recognition Award – Sean Tallman, PhD, associate professor anatomy & neurobiology.
• Henry M. Goldman Faculty Appreciation Award Predoctoral Category – Bruce Robinson, DDS, clinical assistant professor of general dentistry
• Henry M. Goldman Faculty Appreciation Award Postdoctoral Category – Reem Mohamad Al Shaltoni, DDS, DAGS, MSc, clinical assistant professor of restorative sciences & biomaterials.
• Crest Oral-B P&G Professional Oral Health Excellence in Teaching the Basic Sciences Award – Monica Pessina, PhD, clinical associate professor of anatomy & neurobiology.
• Chobanian & Avedisian School of Medicine Affiliate Teaching Award – Travis Braithwaite, MD, assistant professor of medicine.
• Chobanian & Avedisian School of Medicine Kaiser Permanente Silicon Valley Affiliate Teaching Award – Alec Uy, MD.
• School of Public Health Educational Innovation Award – Emily Goldmann, PhD, clinical associate professor of epidemiology.

Abstracts award winners were selected from nearly 30 submissions.

• Best Faculty & Staff Abstract – “Preparing Students to Utilize Artificial Intelligence in Clinical Decisions,” John Weinstein, PhD, MS.
• Best Resident & Fellow Abstract— Integrating Point-of-Care Ultrasound Curriculum into a Fourth-Year Internal Medicine Internship Preparation Course,” Jaeine Lee, MD.
• Best Student Abstract— “A Pilot Pre-Post Study of Applied Improvisation to Enhance Psychosocial Skills in Genetic Counseling Students,” Chloe Evans, BS.