Educational Data Mining in European Union – Achievements and Challenges: A Systematic Literature Review

Abstract

The quality of education is one of the pillars of sustainable development, as set out in "The 2030 Agenda for Sustainable Development", adopted by all United Nations Member States in 2015. Recent social and technological developments, as well as events such as the COVID-19 pandemic or conflicts in many parts of the world, have led to essential changes in the way education processes are carried out. In addition, they have made it possible to generate, collect and store large amounts of data related to these processes, data that can hide useful information for decisions that, in the medium or long term, can lead to a significant increase in the quality of education. Uncovering this information is the subject of Educational Data Mining. To understand the state-of-the-art reflected by recent developments, trends, theories, methodologies, and applications in this field, in the European Union, we considered it appropriate to conduct a systematic and critical literature review. Our paper aims to identify, analyze, and synthesize relevant information from these articles, both to build a foundation for further studies and to identify gaps or unexplored issues that can be addressed in future research. The analysis is based on research identified in three international databases recognized for content quality: Scopus, Science direct, and IEEEXplore.