Data Analytics Applications in Education

Jan Vanthienen, Kristof De Witte

September 27, 2017 by Auerbach Publications
Reference - 265 Pages - 25 B/W Illustrations
ISBN 9781498769273 - CAT# K29292
Series: Data Analytics Applications


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  • Shows how big data analytics can change the way schools teach and administer education
  • Includes concrete examples of the use of data analytics in primary, secondary and tertiary education
  • Minimizes number of school dropouts and predicts success at secondary and tertiary education through big data analytics
  • Use data analytics to design, evaluate and improve the organization
  • Presents multi-objective optimization for maximizing ROMI and customer lifetime value


The abundance of data and the rise of new quantitative and statistical techniques have created a promising area: data analytics. This combination of a culture of data-driven decision making and techniques to include domain knowledge allows organizations to exploit big data analytics in their evaluation and decision processes. Also, in education and learning, big data analytics is being used to enhance the learning process, to evaluate efficiency, to improve feedback, and to enrich the learning experience.

As every step a student takes in the online world can be traced, analyzed, and used, there are plenty of opportunities to improve the learning process of students. First, data analytics techniques can be used to enhance the student’ s learning process by providing real-time feedback, or by enriching the learning experience. Second, data analytics can be used to support the instructor or teacher. Using data analytics, the instructor can better trace, and take targeted actions to improve, the learning process of the student. Third, there are possibilities in using data analytics to measure the performance of instructors. Finally, for policy makers, it is often unclear how schools use their available resources to "produce" outcomes. By combining structured and unstructured data from various sources, data analytics might provide a solution for governments that aim to monitor the performance of schools more closely.

Data analytics in education should not be the domain of a single discipline. Economists should discuss the possibilities, issues, and normative questions with a multidisciplinary team of pedagogists, philosophers, computer scientists, and sociologists. By bringing together various disciplines, a more comprehensive answer can be formulated to the challenges ahead. This book starts this discussion by highlighting some economic perspectives on the use of data analytics in education. The book begins a rich, multidisciplinary discussion that may make data analytics in education seem as natural as a teacher in front of a classroom.