Using Activity Data and Analytics to Address Medical Education’s Social Contract

Abstract Contemporary medical education is increasingly dependent on the assessment judgments and in-training evaluations of preceptors, especially in competency-based programs. However, preceptors are subject to biases and inconsistencies in undertaking these assessment tasks, and they are often reluctant to provide a negative judgment on their learners. The sustainability and reliability of these models of assessment are therefore questionable and more reliable alternatives are needed. We now find ourselves in a digital world, immersed in ambient surveillance on a large portion of our lives. If the commercial world is tracking our activities to a fine degree, why are we not embracing these same techniques in tracking the activities of our learners? Some would cite the right to privacy, but others have noted that we have effectively suborned that right some time ago. Either way, parsing these data (much of which we already collect) using activity-driven metrics and big data analytic approaches can provide a much broader-based assessment of the competencies of our learners, based on what they do rather than what their teachers say they do. Based on our work with virtual scenarios and virtual learners, and on our work with the Medbiquitous Learning Experience Working Group, we present some suggested approaches to how medical education programs can embrace activity metrics.