CAME Webinar - Pan-Canadian Consensus on Big Data in Medical Education Research: The Promises and Perils | OPDES | Queen's University | OPDES

When

Tue May 3rd 2022, 12:00 pm to Tue May 3rd 2022, 4:00 pm

Where

Online

, , Ontario, , Canada

Fee: $0.00 (Base Price)

Registration for this program has closed.

Details

Once you have registered you will receive a confirmation email.

Problems registering or didn't receive the confirmation email? Please contact healthsci.support@queensu.ca

CAME invites you to join them for their webinar sessions, designed to bring practical, evidence and experience based advice to Canadian health educators. The webinars are delivered by CAME using the Zoom platform, allowing full audio and visual communication and interaction between presenter and participants. The webinars offer an exciting opportunity to engage online with an expert and with colleagues in a live discussion on a key topic in medical education.

Dr. Kulasegaram (Mahan)’s research examines educational assessment as an opportunity to enhance learning and in particular, how to support transfer of learning. This involves reexamining the entire context of assessment – the objectives, process, tools, learners, and raters – from theoretical perspectives informed by theories from psychology and educational measurement. This program of work has led to significant changes in the practice and design of assessment at multiple levels of the education continuum for physicians. Currently, he is advancing this work through examining assessment data as one fact of the educational big data. His current focus is on how data across the continuum of training – and across multiple institutions – can be linked and utilized to gain insights that can benefit learners, education programs, and society. In July 2021 he was appointed as the inaugural Temerty Chair in Learner Assessment & Program Evaluation. In this role, Mahan will continue to advance the science of assessment and lead national collaborations in education big data. His other interests also include research methods and instructional design to support transfer of learning, clinical reasoning, and other important education outcomes. He also works in advancing the science and practice of admissions and selection in HPE.

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Lawrence Grierson, PhD is an education scientist and associate professor with the Department of Family Medicine, Program for Educational Research, Innovation, and Theory (MERIT), Program for Community and Rural Education (Mac-CARE), and the Undergraduate MD Program at McMaster University; appointments through which he leads interdisciplinary research pertaining to the theory and practice of education for future health professionals. Through this multi-faceted position, Dr. Grierson works to develop lines of inquiry that foster a better understanding of the downstream impacts that education reform has on patient, hospital, and health system outcomes.

Overview: Dr. Kulasegaram and Dr. Grierson led a recent SSHRC project that engaged Canadian medical education stakeholders and data stewards in building consensus on the ethical use of inter-institutional education data for research. During this webinar, Drs. Kulasegaram and Grierson will describe this knowledge synthesis project, highlighting the perspectives of representatives of physician training, physician licensure, physician certification, physician regulation, training program accreditation, and physician and physician-in-training advocacy organizations involved in the medical professional development trajectory, the risks inherent to this work, and a set of shared values that underpin best practice recommendations for data-driven education research in Canada.

***Please note there will be two presentations***

Delivery 1: 12:00pm - 1:00pm ET
Delivery 2: 3:00pm - 4:00pm ET

Zoom link will be sent the morning of May 3, 2022

At the end of this webinar, participants will be able to:

Understand the process by which a consensus agreement for inter-institutional data-driven medical education research was developed.
Articulate the shared values that medical education stakeholders and data stewards in Canada believe are fundamental to ethical conduct of inter-institutional data-driven medical education research.
Develop research approaches that are consistent with best practice recommendations.

Wed Jan 15th 2025, 7:39 am