The augmented hybrid graph framework for multi-level e-learning applications

Di Zou, Haoran Xie, Tak Lam Wong, Fu Lee Wang, Qingyuan Wu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Citations (Scopus)

Abstract

The advances in MOOCs, Web learning communities, social media platforms and mobile learning apps have been witnessed in recent few years. With the development of these applications and systems, the significant growth of learning resources with multimodalities (e.g., web pages, e-books, lecture videos) has greatly changed the way people learn new knowledge and skills. However, this results in the problem of information overload as learners are overwhelmed by the rich learning resources that accompany the ever developing technologies. In other words, it is increasingly difficult for learners to find required learning materials efficiently and effectively when they confront such a large volume of data. To tackle this problem, it is essential to build a powerful framework to organize e-learning resources and capture learning preferences. In this paper, we therefore propose a graph-based framework to achieve these intended outcomes by integrating various hidden relationships among learners, users and resources. Throughout the case studies, we have verified that the proposed framework is very flexible and powerful to support various kinds of e-learning applications in different scales.

Original languageEnglish
Title of host publicationBlended Learning
Subtitle of host publicationAligning Theory with Practices - 9th International Conference, ICBL 2016, Proceedings
EditorsJunjie Shang, Aihua Wang, Reggie Kwan, Lam-for Kwok, Simon K.S. Cheung
Pages360-370
Number of pages11
DOIs
Publication statusPublished - 2016
Externally publishedYes
Event9th International Conference on Blended Learning, ICBL 2016 - Beijing, China
Duration: 19 Jul 201621 Jul 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9757
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference9th International Conference on Blended Learning, ICBL 2016
Country/TerritoryChina
CityBeijing
Period19/07/1621/07/16

Keywords

  • Conceptual framework
  • E-learning systems
  • Graph-based model
  • Hidden relationship
  • Learning preferences

Fingerprint

Dive into the research topics of 'The augmented hybrid graph framework for multi-level e-learning applications'. Together they form a unique fingerprint.

Cite this