A Data Warehousing Framework for Predictive Analytics in Higher Education: A Focus on Student at-Risk Identification - Ismaili Burim; Besimi Adrian (SEEU Review)
This paper will examine the development of a data warehouse aimed at improving decision-making in higher education, which focuses on the identification of students at-risk of academic failure through machine learning techniques. This research utilizes South East European University (SEEU) as a case study to show how data warehousing can integrate various student data—including demographics, academic performance, grades, attendance, and engagement—into an integrated framework that enables predictive analytics.