MARATTO

book chapter · Advances in educational technologies and instructional design book series

Machine Learning in Adaptive Online Learning for Enhanced Learner Engagement

Abstract

In this chapter, the authors delve into the intricate world of online learning, emphasizing the paramount importance of adaptability in adaptive online learning systems. Beginning with an overview of the dynamic nature of today's digital learners, the chapter underscores the need for learning platforms to be flexible and responsive to individual learner needs. A significant portion of the chapter is dedicated to the potential of machine learning as a method to enhance adaptability. The authors elucidate how machine learning, with its ability to represent knowledge in a structured and interconnected manner, can be harnessed to create more personalized and contextually relevant learning experiences.

Research topics

  • Online Learning and Analytics
  • Intelligent Tutoring Systems and Adaptive Learning
  • Innovative Teaching and Learning Methods

Sustainable Development Goals

Read the original research

This page summarises published work. The authoritative version sits with the publisher.

DOI: 10.4018/979-8-3693-3132-3.ch003

Is something wrong with this record? Report it or request removal.

Discussion

Discuss this research

Have you built on this work, tried to replicate it, or seen it applied in practice? Share what you know. Verified researchers and MARATTO™ domain experts can open a discussion, and any member can reply. Contributions are reviewed before they appear.

No discussion yet. Open the first thread.