News

Topic

While recommender systems in general are used to suggest items of interest to users in a wide variety of domains, each domain presents its own specific challenge. Recently there has been growing interest in recommender systems in educational settings. In this context recommender systems have been used to e.g., recommend different resources, activities or content related to learning, recommend learning sequences or paths, learning partners or even courses, curricula as well as educational institutions to different stakeholders.

Increased research into the application of such systems in higher education, ethical considerations, and increased interest in complementary technologies such as large language models have the potential to improve the quality of available systems. In turn, these developments may improve the ability of recommender systems in higher education to support students in particular, allowing for more informed decisions about e.g. what resources to use or activities to engage in next, facilitating learner agency in the process.

EduRS 2024 – Recommender Systems in Education: Enhancing Higher Education for Personalized and Long-Life Learning delves into the critical role of technology in enhancing transparency and traceability in educational content and pathways. This workshop is designed to foster a deeper understanding of how recommender systems, that are powered by large language models and AI, can be strategically integrated into the open education ecosystem to provide personalized, adaptive learning experiences for every learner.

Workshop Themes and Topics: EduRS 2024 will feature a variety of sessions, including presentations, panel discussions, and hands-on workshops that cover but not limit to: