Abstract:

In the era of Internet, mobile technologies and open education, the need for changes to improve the efficiency and quality of higher education has become crucial. Big data and analytics can contribute to these changes and reshape the future of higher education. Basing decisions on data and evidence seems stunningly obvious. However, higher education, a field that gathers an astonishing array of data about its “customers,” has traditionally been inefficient in its data use, often operating with substantial delays in analyzing readily evident data and feedback. In this paper, the value of Analytics for Higher Education is discussed, and a model of learning analytics development is presented. The main pedagogical and ethical issues about the use of learning analytics are also pointed out, since learning is messy, and using analytics to describe learning is not easy. Nevertheless, Learning Analytics can penetrate the fog of uncertainty around the future of higher education, and shed light on how to allocate resources, develop competitive advantages, and most important, improve the quality and value of the learning experience.

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