Automated course composition and recommendation based on a learner intention

Hua Tsai Kun, Cheng Hsieh Tung, Kai Chiu Ti, Che Lee Ming, I. Wang Tzone

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

7 Citations (Scopus)

Abstract

Traditionally, the presentation order of the learning objects in a course must be described previously and manually. In a personalized tutoring system that may give different courses to different learners, planning the presentation order of courses can be irritating and time-wasting. This paper proposes an approach that can automatically composite and recommend courses to learners with different presentation order and in accord with their intentions. First, a course MAP is constructed according to the contents of related domain ontology and web pages collected form the Internet. Then, a learner's intention is analyzed for compositing automatically suitable orders of the learning objects to form a personalized course. This proposed approach can also recommend learning objects according to a learner's preferences and others' feedbacks. By this approach, personalized courses can be achieved more easily.

Original languageEnglish
Title of host publicationProceedings - The 7th IEEE International Conference on Advanced Learning Technologies, ICALT 2007
Pages274-278
Number of pages5
DOIs
Publication statusPublished - 2007
Event7th IEEE International Conference on Advanced Learning Technologies, ICALT 2007 - Niigata, Japan
Duration: 2007 Jul 182007 Jul 20

Publication series

NameProceedings - The 7th IEEE International Conference on Advanced Learning Technologies, ICALT 2007

Other

Other7th IEEE International Conference on Advanced Learning Technologies, ICALT 2007
Country/TerritoryJapan
CityNiigata
Period07-07-1807-07-20

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Information Systems and Management

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