We are entering an age of 'big data' where the vast amounts of data we collect from a myriad of online systems and sensors are being analysed to discover (or uncover) patterns that would previously have gone unnoticed: "Big data refers to things one can do at a large scale that cannot be done at a small one, to extract new insights or create new forms of value, in ways that change markets, organisations, the relationship between citizens and governments, and more." (Mayer-Schonberger and Cukier, 2013:p6) Medical education is not immune to the impact of big data thinking and practice, reflected for instance in the tracking and modelling of learner behaviour and capability through learning management systems and social media. In this edition of eMT I review how big data concepts are already or are likely to impact medical education, with a particular focus on what this means for the future of scholarship and enquiry in medical education. Big data The concept of big data originated in disciplines that depend on very large data sets such as astronomy, genomics, and meteorology. In recent years big data has become a more ubiquitous concept as our many interactions with digital devices generate ever-increasing amounts of data that can be used for increasingly sophisticated purposes. For example tools such as Google Analytics (www.google.com/analytics) provide rich data on traffic to and through a website, allowing website owners to adjust their material to maximize its impact. Similarly, there are an ever growing range of tools to analyse trends in social media such as Twitter (such as wwrw.twitonomy.com). A recent review of Google's analytics applied to medical education videos in YouTube concluded that "simplified data on very large numbers were much more useful than greater detail on [just a few]", particularly in identifying patterns of behaviour such as which segments of a video were played or replayed more often than others (Topps et al, 2012).
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