In this chapter, we introduce the readers to the field of big educational data and how big educational data can be analysed to provide insights into different stakeholders and thereby foster data driven actions concerning quality improvement in education. For the analysis and exploitation of big educational data, we present different techniques and popular applied scientific methods for data analysis and manipulation such as analytics and different analytical approaches such as learning, academic and visual analytics, providing examples of how these techniques and methods could be used. The concept of quality improvement in education is presented in relation to two factors: (a) to improvement science and its impact on different processes in education such as the learning, educational and academic processes and (b) as a result of the practical application and realization of the presented analytical concepts. The context of health professions education is used to exemplify the different concepts.
Part of the book: Big Data on Real-World Applications