Algorithmic Decision Making in Education: Challenges and Opportunities

Algorithmic technology has experienced significant development in recent years. With advancements in Artificial Intelligence (AI) and the proliferation of Machine Learning (ML) algorithms, Algorithmic Decision-making Systems (ADSs) are embraced by several public sectors, such as health, justice, education, in order to improve their efficiency and create additional sources of information. The need for modernization has led to extended Digital Transformation projects that pose a significant impact on everyday processes but also organizations' long-term goals and even purpose. However, although the benefits, ADSs raise serious concerns in terms of transparency, fairness, and accountability, trust, etc. This paper aims to point out the major challenges related to algorithmic decision-making technology, especially in the field of education, focusing on the effectiveness and suitability of current systems based on their technological limitations. In particular, it identifies and breaks down the key challenges emerging due to the adoption of ADSs and the concerns that they create, while it also discusses the solutions proposed by experts in recent research papers. The paper also provides some thoughts for the future of ADSs in the education sector reflecting upon potential counteracting measures and conflicts with existing technologies or issues regarding the implementation of those solutions, identifying areas that need further research.