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Workshop Schedule

The Connection series consists of 5 internet-mediated online workshops. All workshops within the series are 3 hours in length and begin with an invited presentation from the field of education, health services research, or library sciences followed by knowledge synthesis activities.

Schedule: Text
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Workshop 5: Building Consensus

Wednesday, April 21st, 2021 at 12PM (noon) ET

Schedule: Schedule

12:00 - 12:05 PM

Welcome & Introductions

12:05 - 12:30 PM

Presentation of Draft Proposal

12:30 - 1:00 PM

Breakout 1: Discussion of the Proposal’s Strengths and Weaknesses

1:00 - 1:10 PM

Break

1:10 - 1:40 PM

Large Group Discussion

1:40 - 2:00 PM

Breakout 2: Discussion of Opportunities and Threats

2:00 - 2:20 PM

Large Group Discussion

2:20 - 2:30 PM

Break

2:30 - 2:45 PM

Trainee Roundtable

2:45 - 3:00 PM

Follow-up Strategy & Wrap-up

March 25, 2021 - 12PM to 3PM ET

Workshop 1: Ethical orientations and student perspectives on inter-institutional data sharing

Invited speakers: Dr. Victoria McKinnon (McMaster University) and Dr. Lisa Schwartz (McMaster University)

This session begins with a dialogue between a medical trainee and a leader from the field of Ethics and Policy. This presentation will challenge the workshop participants to consider their broad responsibilities to stakeholders and the potential consequences of collaborative data-driven education research. The workshop will proceed with critical review of data management case studies and facilitated discussions in support of a consensus statement for the ethical utilization of administrative education data for research in Canadian medical education.

April 1, 2021 - 12PM to 3PM ET

Workshop 2: Best Practices and Potential Challenges to Data Sharing - Experiences from General Education

Invited Speaker: Dr. Daniel Corral (University of Toronto, OISE)

This session begins with an invited presentation regarding successful experiences from the Education field. Through reflection upon the relevant principles identified within the emerging consensus agreement and critical review of data quality and management case studies, participants will continue to provide in support of a consensus statement, while also initiating efforts towards the development of a framework for harmonization.

April 7, 2021 - 12PM to 3PM ET

Workshop 3: Best Practices and Potential Challenges to Data Sharing - Experiences from Health Services Research

Invited Speaker: Dr. Elizabeth Wenghofer (Laurentian University)

This session begins with an invited presentation regarding successful experiences from the Health Services Research field. Through reflection upon the relevant principles identified within the emerging consensus agreement and critical review of data quality and management case studies, participants will continue to provide support of a consensus statement, while also initiating efforts towards the development of a framework for harmonization.

April 14, 2021 - 12PM to 3PM ET

Workshop 4: Best Practices and Potential Challenges to Data Sharing - Experiences from Library Sciences

Invited Speakers: Jeff Gardner (Portage Network) and Nick Rochlin (Portage Network)

This session begins with an invited presentation regarding successful experiences from the Library Sciences field. Through reflection upon the relevant principles identified within the emerging consensus agreement and critical review of data quality and management case studies, participants will continue to provide in support of a consensus statement, while also initiating efforts towards the development of a framework for harmonization.

April 21, 2021 - 12PM to 3PM ET

Workshop 5: Review of the emerging consensus statement and harmonization framework

Facilitators: Lawrence Grierson (McMaster University), Mahan Kulasegaram (University of Toronto)

Through reflection upon the drafts generated through the first 4 workshop’s activities, Session 5 challenges participants to refine the consensus agreement and standards framework, and asks participants to establish an approach to evaluating the intended and unintended consequences associated with data-driven education research.

Schedule: Schedule
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