Dynamic assessment and customizable e-learning content generator

W. T. Tsai, Madhu Datla, Jingjing Xu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper proposes a framework to create customizable on - demand educational contents with automated assessment. This framework can sequence educational contents logically based on content dependency, both implicit dependency in domain ontology and/or explicit dependency in external specifications. Based on the dependency information, the framework can propose several alternative and ranked learning paths so that educators or learners can make intelligent decisions. A metric called "Learning Path Relevance" can be used to evaluate alternative learning paths. The framework also has a formal model to generate questions automatically from domain ontology for assessment. Using the proposed framework, it is possible to customize various learning modules for individuals with different backgrounds with automated assessment.

Original languageEnglish (US)
Title of host publicationProceedings of the 2008 International Conference on e-Learning, e-Business, Enterprise Information Systems, and e-Government, EEE 2008
Pages172-178
Number of pages7
StatePublished - 2008
Event2008 International Conference on e-Learning, e-Business, Enterprise Information Systems, and e-Government, EEE 2008 - Las Vegas, NV, United States
Duration: Jul 14 2008Jul 17 2008

Publication series

NameProceedings of the 2008 International Conference on e-Learning, e-Business, Enterprise Information Systems, and e-Government, EEE 2008

Other

Other2008 International Conference on e-Learning, e-Business, Enterprise Information Systems, and e-Government, EEE 2008
Country/TerritoryUnited States
CityLas Vegas, NV
Period7/14/087/17/08

Keywords

  • Content reusability
  • Customizable content
  • Dynamic assessment
  • Dynamic sequencing
  • On-demand learning content

ASJC Scopus subject areas

  • Management of Technology and Innovation
  • Artificial Intelligence
  • Computer Science Applications
  • Law

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