Educators and administrators face difficult choices in response to calls for greater accountability and improved completion rates. Learning analytics can illuminate complex situations and help identify at-risk learners. Analytics, when coupled with open educational resources, the semantic web, and personal and adaptive learning content, suggest the prospect of systemic change. With the use of recommender systems, social networks analysis, discourse analysis, and activity trails, existing course models of learning may have a limited future. This discussion-oriented session will begin with a review of current learning analytics in higher education and explore future trends and directions. We will solicit input from participants, particularly in relation to concerns around learning analytics and barriers organizations face in their adoption.