2023: Integration of Adaptive Learning in Interactive Online Learning Environments

Master's theses

Student
Maximilian Anzinger

Supervisor(s)Advisor(s)

Abstract

An ever-increasing student body with vastly different backgrounds, abilities, and experiences steadily raises new challenges for instructors, particularly the consideration of students’ individual needs in large heterogeneous groups. In this work, we present an intelligent recommendation system to generate adaptive learning paths with the means to enhance students’ learning experiences in the interactive online learning platform Artemis. We conduct a requirements analysis and propose a system design for the integration of learning paths. Furthermore, we discuss the details of the implementation and outline future work to improve and extend the proposed system.