Educational Recommender Systems

Tutorial at the 24th International Conference on Artificial Intelligence in Education (AIED), 2023
Schedule: July 3, 2023


The emergence of data science and artificial intelligence technologies has made technology-enhanced learning (TEL) a promising area of research and practice in education. One of the significant contributions of TEL has been the development of personalized learning and educational recommender systems.

Recommender systems (RecSys) have found widespread use in a variety of internet applications, including e-commerce platforms like 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 (EdRecSys). Its applications in this field include personalized learning experiences, recommending appropriate books, informal learning materials, and after-school programs, 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. However, these progresses made in the field of RecSys was not adequately disseminated to the education community or the development of educational recommender systems (EdRecSys). This tutorial will deliver background, motivations, knowledge and skills of educational recommender systems to the audience, as well as a summary of emerging topics and open challenges in this area.


Part I. EdRecSys: An Overview

Time: July 3, 9:00 - 10:30 + QA
Location: Hitotsubashi Hall, Room 203

  • Intro: Recommender Systems (RecSys)
  • RecSys in Education v.s. in other domains
  • Classification of Educational Recommender System (EdRecSys)
  • Available Data Sets
  • Case Studies: EdRec Specialized to Education
    • EdRec built in Educational Information Systems
    • EdRec: course recommendations
    • EdRec: book recommendations
    • EdRec: pathway recommendations
    • EdRec: peer matching
  • QA

Part II. EdRecSys: Case Studies

Time: July 3, 11:00 - 12:30 + QA
Location: Hitotsubashi Hall, Room 203

  • Case Studies: EdRec Specialized to Education (continued)
    • EdRec using pedagogical features
  • Case Studies: General RecSys with Practice in Education
    • Context-Aware EdRec
    • ITM-Rec Data Set
    • Multi-Criteria EdRec
    • Group EdRec
    • Personality-Based EdRec
    • Multi-stakeholder EdRec
    • Multi-task EdRec
    • Multi-objective EdRec
    • EdRec: Fairness, Transparency, Explanations
  • Challenges and Future Work
  • QA



Yong Zheng

Assistant Professor

Illinois Institute of Technology, USA