Leveraging Learning Analytics in Medical Education

Date:                    Sunday 25th August

Half Day:              0930-1230

Level:                    Introductory


  1. Vania Dimitrova, Leeds Institute of Medical Education & School of Computing, University of Leeds, UK
  2. David Topps, University of Calgary, Canada
  3. Rachel Ellaway, University of Calgary, Canada
  4. Tamsin Treasure-Jones, Leeds Institute of Medical Education, University of Leeds, UK
  5. Martin V. Pusic, NYU Langone Health, USA
  6. Olivier Palombi, University of Grenoble Alpes, France

Summary of theme and why it is important:  The widespread use of digital technologies in medical education means that we are capturing more and more digital data about teaching and learning activities, use of resources, decision making, assessment, feedback and so on. Learning analytics are increasingly being seen as a key driver for innovating education. However, while great progress has been made in learning analytics and learning analytics tools in mainstream education, health professions education is only now starting to use these approaches. The adoption of learning analytics in the real world brings a new spectrum of socio-technical challenges, e.g. data availability and reliability, potential for oversimplifications and misinterpretations, ownership, privacy and security, ethics, institutional barriers.
Through participation in a series of highly interactive activities, workshop participants will explore a series of key questions related to adoption of learning analytics:

  • Data: availability, quality, governance
  • Tools: collection, integration, analysis
  • Practice: ecosystem, strategy, constraints
During the interactive activities, the presenters will share their critical reflection on the potential of learning analytics, share opportunities and pitfalls they have faced, and point at lessons learnt. This will draw upon an ensemble of experience in adopting learning analytics across a range of medical education contexts, including:
  • specific programmes - workplace learning, residency, visual diagnosis;
  • medical education institutions - continuous longitudinal data-driven insights to inform strategic decisions and innovative practice;
  • cross-institutional national programme – integrating data across institutions to standardise assessment and personalise learning.
The workshop will also use the Learning Toolbox, (the platform used for the AMEE e-posters in 2017 and 2018) to provide participants with a collection of resources to take away with them and a space in which further discussions can be continued.

Who should participate in the Pre-Conference Workshop? 

  • Medical educators
  • Researchers
  • Medical programme managers and administrators
  • Faculty developers in medical education
  • Faculty interested in adopting technologies in medical education to enhance their practice
  • Medical education leaders

What will they gain from participating?

  • Understand key definitions and issues in data and analytics
  • Become aware of key tools and methods to use learning analytics and personalised recommendations in medical education
  • Appraise their practice in the light of the new landscape afforded by learning analytics
  • Gain insight into challenges and solutions from colleagues who are adopting learning analytics in medical education
  • Identify opportunities to adopt learning analytics in their practice
  • Engage in an open debate of the potential strengths and weaknesses of using learning analytics


Cost: Euros 90 (includes coffee)

PLEASE NOTE: Pre-conference Workshop participants must also register for AMEE 2019 and pay the conference fee.


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