Learning analytics has a vast potential to address the many current concerns in higher education surrounding learning and the educational experience. These include lead indicators and predictive models for identifying students requiring additional learning support, reducing student attrition, measuring student graduate attributes, and developing scalable methods for enhancing teaching practice.

Learning analytics capitalizes on the data-intensive technological base that supports formal and informal learning to extend capacity and understanding of learning processes in contemporary environments. It is of little surprise that the field of learning analytics is a rapidly expanding area of research and practice, drawing the attention of governments, foundations, and academics.

This conference provides the opportunity to consider these opportunities and challenges and the role learning analytics can play in both applied and theoretical contexts. LAK12 will bring together a diversity of researchers focused on the many inter-disciplinary fields associated with learning analytics.

Keynote speakers include Katy Börner, Professor of Information Science at the School of Library and Information Science at Indiana University; George Siemens, researcher and strategist with the Technology Enhanced Knowledge Research Institute at Athabasca University in Alberta (CA); and Barry Wellman, Professor at the Department of Sociology at the University of Toronto (CA).