Publication
By offering a large number of highly diverse resources, learning platforms have been attracting lots of participants, and the interactions with these systems have generated a vast amount of learning-related data. Their collection, processing and analysis have promoted a significant growth of machine learning and knowledge discovery approaches and have opened up new opportunities for supporting and assessing educational experiences in a data-driven fashion. Being able to understand students' behavior and devise models able to provide data-driven decisions pertaining to the learning domain is a primary property of learning platforms, aiming at maximizing learning outcomes. However, the use of knowledge discovery in education also raises a range of ethical challenges including transparency, reliability fairness, and inclusiveness. In this workshop event, we focus on providing a common ground for researchers and practitioners working in this vibrant area, with the ultimate ambitious goal of bridging the UMAP community with the domain-oriented educational sister communities.