A Concept for Modeling Adaptive Learning Mechanisms for Learning Management Systems

Research output: Contribution to book/Conference proceedings/Anthology/ReportConference contributionContributedpeer-review

Contributors

Abstract

Adaptive Learning Mechanisms (ALM) can be used to personalize the learning process in Learning Management Systems (LMS) to increase learning gains. The issue is that existing approaches to integrating ALMs into LMSs often do not focus on supporting the user groups that are interested in specifying and providing ALMs (i.e., instructors and researchers) according to their needs. This is because these approaches do not focus on specifying the provided ALMs, require a high level of technical expertise to specify them, or are not intended to integrate the provided ALMs into different LMSs to work with existing content. With the goal of addressing these requirements, we propose a concept of an LMS-independent modeling interface. This interface allows users with a low level of technical expertise to model ALMs, referred to as assistance workflows, in a flowchart-like graph. These ALMs can work with different LMSs based on a service-oriented architecture. We evaluated the proposed concept by means of a technical evaluation and a user evaluation according to the user-centered design approach. The results indicate that the proposed architectural approach is suitable to be applied to different LMSs and that the modeling interface meets the requirements of the target user groups.

Details

Original languageEnglish
Title of host publicationProceedings of the 2025 IEEE International Conference on Advanced Learning Technologies (ICALT)
EditorsMaiga Chang, Scott Chen, Rita Kuo, Demetrios Sampson, Ahmed Tlili, Pei-Shu Tsai
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages32-34
Number of pages3
ISBN (electronic)979-8-3315-6530-5
ISBN (print)979-8-3315-6531-2
Publication statusPublished - Oct 2025
Peer-reviewedYes

Publication series

SeriesInternational Conference on Advanced Learning Technologies (ICALT)
ISSN2161-3761

External IDs

Scopus 105021953984

Keywords

Keywords

  • LMS, adaptation models, adaptive learning, adaptive learning mechanisms, learning management systems, personalized learning, service-oriented architecture, technology-enhanced learning, user centered design, LMS, adaptation models, adaptive learning, adaptive learning mechanisms, learning management systems, personalized learning, service-oriented architecture, technology-enhanced learning, user centered design