Annotated knowledge graphs for teaching in higher education: Supporting mentors and mentees by digital systems

Abstract

Digital systems that enable so-called intelligent, adaptive or personalized learning are thought to bear great potential for the future of education. Research and development towards such innovative learning systems has therefore evolved into an expanding field. Two of the key challenges are (1) to automate the extraction of expert knowledge and (2) the development of an advanced domain model, on which the system can draw. To tackle these challenges, our interdisciplinary contribution is to suggest adopting a novel approach to creating educational knowledge graphs of texts (1), which can then be further annotated and supplemented by instructors and students (2). In particular, we will outline practical use cases for blended learning scenarios in Higher Education.