Tutorial: Educational Recommender Systems.

Recommender systems (RecSys) have found widespread use in a variety of applications, including e-commerce platforms like Amazon.com and eBay, online streaming services such as YouTube, Netflix, and Spotify, and social media sites like Facebook and Twitter. The success of these applications in improving user experience and decision making by providing personalized recommendations highlights the effectiveness of RecSys. Over the past few decades, RecSys has also made its way into the field of education, which results in the development of educational recommender systems (EdRec). Its applications in this field include personalized learning experiences, recommending appropriate formal or informal learning materials, suggesting learning peers, and adapting learning to context-aware or mobile environments, and so forth. Recently, the development of RecSys has been advanced by a series of interesting and promising topics, such as multi-task learning, multi-objective optimization, multi-stakeholder considerations, concerns of fairness, accountability, and transparency, etc. However, this progress made in the field of recommender systems was not adequately disseminated to the education community or the development of EdRec. In this tutorial, we will introduce the background, motivations, knowledge & skills associated with the current development of EdRec, and discuss a set of emerging topics and open challenges, along with case studies in EdRec.