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AI-Based Learning Recommendations: Use in Higher Education

Author

Listed:
  • Prabin Dahal

    (Media Faculty, Offenburg University of Applied Sciences, Badstraße 24, 77652 Offenburg, Germany
    These authors contributed equally to this work.)

  • Saptadi Nugroho

    (Media Faculty, Offenburg University of Applied Sciences, Badstraße 24, 77652 Offenburg, Germany
    These authors contributed equally to this work.)

  • Claudia Schmidt

    (Media Faculty, Offenburg University of Applied Sciences, Badstraße 24, 77652 Offenburg, Germany)

  • Volker Sänger

    (Media Faculty, Offenburg University of Applied Sciences, Badstraße 24, 77652 Offenburg, Germany)

Abstract

We propose the extension for Artificial Intelligence (AI)-supported learning recommendations within higher education, focusing on enhancing the widely-used Moodle Learning Management System (LMS) and extending it to the Learning eXperience Platform (LXP). The proposed LXP is an enhancement of Moodle, with an emphasis on learning support and learner motivation, incorporating various recommendation types such as content-based, collaborative, and session-based recommendations to provide the next learning resources given by lecturers and retrieved from the content curation of Open Educational Resources (OER) for the learners. In addition, we integrated a chatbot using Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) with AI-based recommendations to provide an effective learning experience.

Suggested Citation

  • Prabin Dahal & Saptadi Nugroho & Claudia Schmidt & Volker Sänger, 2025. "AI-Based Learning Recommendations: Use in Higher Education," Future Internet, MDPI, vol. 17(7), pages 1-22, June.
    • Handle: RePEc:gam:jftint:v:17:y:2025:i:7:p:285-:d:1687917
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