Episodes
Key points episode 25
- Incremental prompting: Emphasizes training ChatGPT4 with step-by-step prompts in each new session.
- Brainstorming & outlining: Highlights its ability to generate outlines, titles, and summaries to overcome writer’s block.
- Editing & refinement: Demonstrates how it can review and improve clarity, while requiring your unique voice for creative tasks.
- Task differentiation: Distinguishes between routine writing tasks for AI assistance and the creative, personal aspects of writing.
- Policy awareness: Advises checking target journals’ policies on generative AI before incorporating its output.
Key points episode 27
- Examines the role of ethics statements in academic publishing.
- Explains why Appendix 3 is essential for crafting thorough ethics statements.
- Highlights key elements that should be included to ensure ethical integrity.
- Discusses common pitfalls and how to avoid vague or insufficient statements.
- Considers the broader impact of ethics statements on research transparency.
Key points episode 28
- Showcases the work of early career scholars in health professions education.
- Highlights diverse research topics, including curriculum design, assessment, feedback, and professional identity.
- Features scholars from across the world tackling global health education challenges.
- Encourages collaboration and engagement with emerging education researchers.
- Part one of a two-part series spotlighting innovative contributions to the field.
Key points episode 32
- Showcases the work of early career scholars advancing medical education.
- Highlights research on power dynamics, clinical reasoning, and narrative analysis.
- Features scholars tackling issues like assessment, feedback, and professional identity.
- Emphasizes interdisciplinary collaboration to enrich health professions education.
- Part two of a two-part series spotlighting emerging researchers in the field.
Key points episode 51
- Explores how big national datasets could improve graduate medical education (GME).
- Discusses the lack of comprehensive, longitudinal HPE data and the barriers to data aggregation.
- Highlights the potential for AI and machine learning to enable precision education.
- Proposes a model for data-sharing infrastructure with common standards and identifiers.
- Outlines next steps, including data inventory, pilot projects, and governance frameworks to support data collaboration
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Methods Consult resources:
A bunch of episodes that give you expert advice and insights from our hosts about medical education research and scientific methods.