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Interdisciplinary resources about learning analytics, big data, and higher education presented as a living annotated bibliography for the DCCC community.
"the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimising learning and the environments in which it occurs" (Long & Siemens), or
"an educational application of web analytics aimed at learner profiling, a process of gathering and analyzing details of individual student interactions in online learning activities" (EDUCAUSE).
The resources on this page provide an introduction to the subject of learning analytics software applications in higher education.
"What You Need To Know About Learning Analytics" is a Focus collection featuring articles from The Chronicle of Higher Education. Published in October 2016, the articles elucidate ways in which learning analytics are actually being used, analyzes the promise of learning analytics as the next disruptive technology of education, raises ethical concerns about the collection and use of student-generated data, and examines the business and capitalization strategies for developers in the ed. tech. industry. The collection concludes with articles on how learning analytics is (and is not) influencing teaching and learning.
The presentation, "Learning Analytics: Big Data in Education," proposes interdisciplinary entry points to the scholarly examination of learning analytics from a range of disciplines, including computer science, statistics, education, psychology, history and political science, business and economics, law, and ethics. (Originally presented during DCCC Faculty In-Service, 16 Feb. 2017).
EDUCAUSE Review's "The State of Learning Analytics" explains a decline in learning analytics adoption and implementation due to issues with data quality, system interoperability, lack of administrative support, and "a possible faculty culture of resistance." This post links to a more comprehensive EDUCAUSE Center for Analysis and Research report, "Learning Analytics in Higher Education," which details adoption drivers and specific applications.