In just a few years, e-learning has become part of the mainstream in medical education. While e-learning means many things to many people, at its heart it is concerned with the educational uses of technology. For the purposes of this guide, we consider the many ways that the information revolution has affected and remediated the practice of healthcare teaching and learning. Deploying new technologies usually introduces tensions, and e-learning is no exception. Some wish to use it merely to perform pre-existing activities more efficiently or faster. Others pursue new ways of thinking and working that the use of such technology affords them. Simultaneously, while education, not technology, is the prime goal (and for healthcare, better patient outcomes), we are also aware that we cannot always predict outcomes. Sometimes, we have to take risks, and 'see what happens.' Serendipity often adds to the excitement of teaching. It certainly adds to the excitement of learning. The use of technology in support of education is not, therefore, a causal or engineered set of practices; rather, it requires creativity and adaptability in response to the specific and changing contexts in which it is used. Medical Education, as with most fields, is grappling with these tensions; the AMEE Guide to e-Learning in Medical Education hopes to help the reader, whether novice or expert, navigate them. This Guide is presented both as an introduction to the novice, and as a resource to more experienced practitioners. It covers a wide range of topics, some in broad outline, and others in more detail. Each section is concluded with a brief 'Take Home Message' which serves as a short summary of the section. The Guide is divided into two parts. The first part introduces the basic concepts of e-learning, e-teaching, and e-assessment, and then focuses on the day-to-day issues of e-learning, looking both at theoretical concepts and practical implementation issues. The second part examines technical, management, social, design and other broader issues in e-learning, and it ends with a review of emerging forms and directions in e-learning in medical education.

Context matters in medical education and it can, despite many challenges, be considered systematically and objectively. The findings from this study both represent a catalyst and challenge medical education researchers to look at context afresh.

Mobile technologies (including handheld and wearable devices) have the potential to enhance learning activities from basic medical undergraduate education through residency and beyond. In order to use these technologies successfully, medical educators need to be aware of the underpinning socio-theoretical concepts that influence their usage, the pre-clinical and clinical educational environment in which the educational activities occur, and the practical possibilities and limitations of their usage. This Guide builds upon the previous AMEE Guide to e-Learning in medical education by providing medical teachers with conceptual frameworks and practical examples of using mobile technologies in medical education. The goal is to help medical teachers to use these concepts and technologies at all levels of medical education to improve the education of medical and healthcare personnel, and ultimately contribute to improved patient healthcare. This Guide begins by reviewing some of the technological changes that have occurred in recent years, and then examines the theoretical basis (both social and educational) for understanding mobile technology usage. From there, the Guide progresses through a hierarchy of institutional, teacher and learner needs, identifying issues, problems and solutions for the effective use of mobile technology in medical education. This Guide ends with a brief look to the future.

No single evaluation is likely to collect all of this information, nor would any single audience likely find all information elements equally useful. However, consistent use of a common evaluation framework across different courses and institutions would avoid duplication of effort and allow cross-course comparisons.

As we capture more and more data about learners, their learning, and the organization of their learning, our ability to identify emerging patterns and to extract meaning grows exponentially. The insights gained from the analyses of these large amounts of data are only helpful to the extent that they can be the basis for positive action such as knowledge discovery, improved capacity for prediction, and anomaly detection. Big Data involves the aggregation and melding of large and heterogeneous datasets while education analytics involves looking for patterns in educational practice or performance in single or aggregate datasets. Although it seems likely that the use of education analytics and Big Data techniques will have a transformative impact on health professional education, there is much yet to be done before they can become part of mainstream health professional education practice. If health professional education is to be accountable for its programs run and are developed, then health professional educators will need to be ready to deal with the complex and compelling dynamics of analytics and Big Data. This article provides an overview of these emerging techniques in the context of health professional education.