INTRODUCTION
The publication of the second edition of the SAGE Handbook of E-learning Research attests to the continued need for study and understanding of learning practices in contemporary technology-supported and technology-enabled educational, work and social settings. In preparing the first edition (Andrews & Haythornthwaite, 2007a), we found that while there had been considerable development in teaching and learning online, and in learning design, there was no coherent view of what constituted research in the field. Writing for this 2016 edition, we find there has been much progress in research, but it has taken many new directions, each wrestling with how to analyze and represent learning in an era of continuing change in technologies, learning practices, and knowledge distribution. This volume, like the last, takes stock of progress in e-learning research, highlighting advances as well as new directions in studies and methods for approaching and keeping up with changes in learning in an e-society.
SITUATING E-LEARNING
The term e-learning has at times been equated with the implementation of institutional learning management systems (LMS), also known as virtual learning environments (VLE). Yet, e-learning encompasses far more than the technology alone and more than educational institutional environments. While we were cognizant of wider social impacts when the earlier edition of the Handbook was in production, major e-learning issues and attention at the time were directed to how to teach online, how to bring resources from the institution into the service of learning for distributed learners, and how to study and practice at the technologyālearning interface. While these remain major concerns, research and interest is now wider, grappling with how technology use can be blended with and complement traditional in-class education, and how to blend contemporary youth media practices with established educational perspectives as a wired ā and wireless ā generation enters university and then the workplace. The reach of the Internet has generated a desire and a vision for providing education to wider audiences, most recently expressed in the development of massively open online courses (MOOCs), yet also enacted daily on a global scale through social media, online news, open access journals, peer production, crowdsourcing, and collaborative information projects such as Wikipedia.
In the e-learning sphere, developments that have garnered attention include the greater adoption of video-based resources for teaching and learning (Burn, 2007; Sherer & Shea, 2011; Tan, 2013; Meyers, 2014a; Meyers, 2014b; Pesina, Beaumont & Parkes, 2014); games and gamification of learning (Halverson & Steinkeuhler, this volume; Burn, this volume; including use of virtual worlds: Savin-Baden & Tombs, this volume); and MOOCs (though see Laurillard, 2014). Other developments include implementation of more enhanced means of helping learners navigate their way through materials, such as lecture recordings that can be annotated (e.g. the collaborative lecture annotation system described in Risko, Foulsham, Dawson & Kingstone, 2013); adaptive learning systems that determine next steps according to learner progress and types of error; and dashboards that show progress or effort in comparison to other learners (e.g. Verbert, Duval, Klerkx, Govaerts & Santos, 2013).
The era of ābig dataā has arrived since our first edition, and it is quickly changing the landscape in the learning field. Particular attention has been given to the way every online use of information and communication technology leaves digital traces of engagement, interaction, communication, argumentation, and learning. These data provide views of different aspects of learnersā activities, such as: networks of conversation that can show the patterns of social learning; counts of reading downloads or time spent viewing readings that can indicate attention to resources; and highlighting, re-reading, or commentary on online resources that can indicate areas of learning difficulty.
Several major areas of research and institutional practice are emerging that collect or design for the use of such data to examine learning. These include research associated with more established areas of the learning sciences (Hoadley, this volume), computer-supported collaborative learning (e.g. Koschmann, 1996), and networked learning (Jones & de Laat, this volume; Carvalho & Goodyear, 2014); and newer areas such as educational data mining (Baker & Yacef, 2009; Romero, Ventura, Pechenizkiy & Baker, 2011), learning@scale (e.g. Fox, Hearst & Chi, 2014), and learning analytics (Rogers, Dawson & GaÅ”eviÄ, this volume; Haythornthwaite, de Laat & Schreurs, this volume; Wise & Paulus, this volume; Ferguson, 2012). The similar area of academic analytics provides overviews at the institutional level, such as mapping student trajectories across courses and programs, and looking at success and retention rates. Early alert systems for students in academic trouble have been an important development in this area (van Barneveld, Arnold & Campbell, 2012).
Other expansions include engagement of more types of institutions and professions in e-learning. Research for libraries (Bhimani, this volume) and museums (Looseley & Rae, this volume), for example, examines the effects of e-learning on their services and how to bring e-learning practices into their re...
