Call for papers - Breaking disciplinary silos in medical education: advancing interprofessional collaboration in the era of AI

Guest Editors

Fraide Ganotice, PhD, FHEA, The University of Hong Kong, China
Dragan Gasevic, PhD, Monash University, Australia
Maura Polansky, PhD, MHPE, MS, University of Illinois, USA
Sarah Wojkowski, PhD, MSc(PT), HBKin, McMaster University, Canada

Submission Status: Open | Submission Deadline: 8 January 2026

BMC Medical Education welcomes submissions to our Collection, Breaking disciplinary silos in medical education: advancing interprofessional collaboration in the era of artificial intelligence (AI). This collection aims to foster discussions within the community of practice to identify best practices in interprofessional collaboration in the Generative AI era, addressing the urgent need for a cohesive and adaptable approach to interprofessional education.

New Content Item This Collection supports and amplifies research related to SDG 4: Quality Education.

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Meet the Guest Editors

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Fraide Ganotice, PhD, FHEA, The University of Hong Kong, China

Dr Ganotice is an Associate Professor at The University of Hong Kong. He specializes in educational psychology, measurement and evaluation, group processes, and interprofessional sciences. He serves as the Director of the Bau Institute of Medical and Health Sciences Education, Programme Director of Global Interprofessional Education and Collaborative Practice, Programme Director of Research and Scholarship, and Programme Director of the Student Teaching and Reflection Programme. Dr Ganotice's research is dedicated to dismantling educational silos to achieve optimal patient-centered care. He focuses on examining individual and group-level variables that explain interprofessional education outcomes among students, and the use of technology to facilitate student engagement, collaboration, and achievement. His dedication to teaching and research in medical education has been recognized with numerous awards, including the 2023 Teaching Excellence Award from the U21 Health Sciences Group, the Gold Winner at the 2023 Times Higher Education Awards Asia, the Gold Award at the 2021 Quacquarelli Symonds Reimagine Education Awards, the 2021 Teaching Innovation Award, and the U21 Fellowship to Amsterdam University in 2024.

Dragan Gasevic, PhD, Monash University, Australia

Dr Gasevic is a Distinguished Professor of Learning Analytics and Director of Research in the Department of Human Centered Computing of the Faculty of Information Technology and the Director of the Centre for Learning Analytics at Monash University. Dragan’s research interests center around data analytic, AI, and design methods that can advance understanding of self-regulated and collaborative learning. He is a founder and served as the President (2015-2017) of the Society for Learning Analytics Research. He is a recipient of the Life-time Member Award (2022) as the highest distinction of the Society for Learning Analytics Research and a Distinguished Member (2022) of the Association for Computing Machinery. In 2019-2022, he was recognized as the national field leader in educational technology in The Australian’s Research Magazine that is published annually. He led the EU-funded SHEILA project that received the Best Research Project of the Year Award (2019) from the Association for Learning Technology.

Maura Polansky, PhD, MHPE, MS, University of Illinois, USA

Dr Polansky is an educator, scholar, and leader in health professions education. She began her career as a physician assistant following her training at Baylor College of Medicine in Houston, Texas. Dr Polansky went on to earn a master’s degree in Health Professions Education from the University of Illinois Chicago and a PhD in Health Professions Education from the Massachusetts General Hospital Institute of Health Professions in Boston. Dr Polansky had a distinguished career in clinical education and continuing professional development while at the University of Texas MD Anderson Cancer Center. She later joined the George Washington University where she held leadership roles in education and research and developed novel curricula in health professions leadership and interprofessional practice. She has served on the editorial board of the Journal of Oncology Practice and is a regular reviewer for various health professions journals. Dr Polansky is currently a Clinical Professor at the University of Illinois College of Medicine. She teaches and advises graduate students on topics related to interprofessional learning, clinical education, curriculum development and program evaluation. Her scholarly interests focus on interprofessional learning and leadership.

Sarah Wojkowski, PhD, MSc(PT), HBKin, McMaster University, Canada

Dr Wojkowski is a registered physiotherapist and holds the positions of Vice Dean & Executive Director, School of Rehabilitation Science, and Director, Program for Interprofessional Practice, Education and Research (PIPER) at McMaster University. Sarah completed a Leadership in Teaching and Learning Fellowship with MacPherson Institute at McMaster. Sarah's areas of interest include interprofessional education, simulation, innovative/role emerging clinical placements, student evaluation, and curriculum development. Sarah has been privileged with access to post-secondary education and is committed to continually educating herself and being an ally in equity, diversity, inclusion, and indigenous reconciliation efforts.

About the Collection

BMC Medical Education invites submissions to our Collection, Breaking disciplinary silos in medical education: advancing interprofessional collaboration in the era of AI. This Collection seeks innovative research and perspectives on preparing learners and healthcare teams for collaborative practice in the era of artificial intelligence and advanced digital technologies.

The digital transformation of healthcare presents a unique opportunity to reimagine interprofessional practice and learning. As AI tools become fundamental to clinical practice, they create shared working spaces where healthcare professionals must collaborate and develop a common understanding. This evolution calls for new educational approaches that prepare healthcare teams to work effectively with technology while maintaining patient-centered care. Furthermore, the integration of AI into interprofessional education (IPE) offers unprecedented opportunities for leveraging learning analytics to enhance educational outcomes. Large-scale IPE, especially with increasing calls for internationalization, may benefit significantly from AI-driven analytics. These tools may provide deep insights into learner behaviors, identify gaps in knowledge, and tailor educational experiences to meet the diverse needs of healthcare students worldwide.

We welcome contributions addressing but not limited to:

Evidence-based teaching models that use AI-related technology to enhance interprofessional learning and improve educational outcomes
Approaches to building shared AI competencies across healthcare disciplines to ensure cohesive and effective team-based care
Methods for assessing team performance in AI-enhanced healthcare learning environments to identify best practices and areas for improvement
Sustainable frameworks for AI-supported collaborative learning in healthcare education that can be adapted and scaled across various institutions
Impact studies examining how AI-supported teamwork influences patient outcomes, with a focus on improving quality of care and patient safety
Institutional strategies for implementing AI-enhanced medical education, including policy development, faculty training, and resource allocation
Utilization of AI-driven learning analytics to personalize and optimize educational experiences, facilitate international collaboration, and track long-term outcomes of IPE initiatives

We invite educators, researchers, and practitioners to contribute work that advances our understanding of effective interprofessional collaboration and interprofessional learning in the era of AI. This Collection aims to provide evidence-based guidance for breaking down professional barriers while preparing healthcare teams for collaborative practice in an AI-enhanced healthcare system.

All manuscripts submitted to this journal, including those submitted to collections and special issues, are assessed in line with our editorial policies and the journal’s peer review process. Reviewers and editors are required to declare competing interests and can be excluded from the peer review process if a competing interest exists.

This Collection supports and amplifies research related to SDG 4: Quality Education.

There are currently no articles in this collection.

Submission Guidelines

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This Collection welcomes submission of original Research Articles. Should you wish to submit a different article type, please read our submission guidelines to confirm that type is accepted by the journal. Articles for this Collection should be submitted via our submission system, Snapp. During the submission process you will be asked whether you are submitting to a Collection, please select "Breaking disciplinary silos in medical education: advancing interprofessional collaboration in the era of AI" from the dropdown menu.

All manuscripts submitted to this journal, including those submitted to collections and special issues, are assessed in line with our editorial policies and the journal’s peer review process. Reviewers and editors are required to declare competing interests and can be excluded from the peer review process if a competing interest exists.