Dirk Ifenthaler

• Recently, interest in collecting and mining large sets of educational data on student background and performance to conduct research on learning and instruction has developed as an area generally referred to as learning analytics. Higher education leaders are recognising the value of learning analytics for improving not only learning and teaching but also the entire educational arena. However, theoretical concepts and empirical evidence need to be generated within the fast evolving field of learning analytics. In this paper, we introduce a holistic learning analytics framework. Based on this framework, student, learning, and curriculum profiles have been developed which include relevant static and dynamic parameters for facilitating the learning analytics framework. Based on the theoretical model, an empirical study was conducted to empirically validate the parameters included in the student profile. The paper concludes with practical implications and issues for future research.