The emergence of big data in educational contexts has led to new data-driven approaches
to support informed decision making and efforts to improve educational effectiveness. Digital …

In recent years, education institutions have offered a wide range of course selections with
overlaps. This presents significant challenges to students in selecting successful courses …

This report describes the current state of the art in artificial intelligence (AI) and its potential
impact for learning, teaching, and education. It provides conceptual foundations for well …

Automated recommendations have become a pervasive feature of our online user
experience, and due to their practical importance, recommender systems also represent an …

In higher education, predictive analytics can provide actionable insights to diverse
stakeholders such as administrators, instructors, and students. Separate feature sets are …

With cross-disciplinary academic interests increasing and academic advising resources over
capacity, the importance of exploring data-assisted methods to support student decision …

Collaborative filtering based algorithms, including Recurrent Neural Networks (RNN), tend
towards predicting a perpetuation of past observed behavior. In a recommendation context …

Equity of educational outcome and fairness of AI with respect to race have been topics of
increasing importance in education. In this work, we address both with empirical evaluations …

Abstract 21st century career development is increasingly characterized by recurring
participation in work-related skill learning, much of which is mediated by technology …

Universities are engines for human capital development, producing the next generation of
scientists, artists, political leaders, and informed citizens. Yet the scientific study of higher …