Next Steps in the Implementation of Learning Analytics in Medical Education: Consensus From an International Cohort of Medical Educators

Abstract

BACKGROUND: With the implementation of competency-based assessment systems, education programs are collecting increasing amounts of data about medical learners. However, learning analytics are rarely employed to use this data to improve medical education. OBJECTIVE: We identified outstanding issues that are limiting the effective adoption of learning analytics in medical education. METHODS: Participants at an international summit on learning analytics in medical education generated key questions that need to be addressed to move the field forward. Small groups formulated questions related to data stewardship, learner perspectives, and program perspectives. Three investigators conducted an inductive qualitative content analysis on the participant questions, coding the data by consensus and organizing it into themes. One investigator used the themes to formulate representative questions that were refined by the other investigators. RESULTS: Sixty-seven participants from 6 countries submitted 195 questions. From them, we identified 3 major themes: implementation challenges (related to changing current practices to collect data and utilize learning analytics); data (related to data collection, security, governance, access, and analysis); and outcomes (related to the use of learning analytics for assessing learners and faculty as well as evaluating programs and systems). We present the representative questions and their implications. CONCLUSIONS: Our analysis highlights themes regarding implementation, data management, and outcomes related to the use of learning analytics in medical education. These results can be used as a framework to guide stakeholder education, research, and policy development that delineates the benefits and challenges of using learning analytics in medical education.

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