The Significance of Enhancing Data Fairness in Educational Recommender Systems

Students, teachers, and educational institutions can all benefit from improving data fairness in educational RS through a variety of helpful approaches. Because data is so vital, the goal of this work is to propose characteristics and strategies to increase fairness in pre-processing procedures. By highlighting the importance of specific variables that are influenced by data fairness approaches, our work aims to improve data fairness in educational Recommender Systems (RS). We highlight the impact that enhancing data fairness has on students’ performance in educational RS. Students’ motivation rises and their performance benefits when they obtain fair and balanced recommendations. Additionally, we aim to present novel strategies that support increasing and strengthening fairness in educational RS.