Dynamic and personalized curriculum-generation method analysing causality and dependency between learning objects

Ryosuke Konishi, Yusuke Takahashi, Yasushi Kiyoki

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

2 Citations (Scopus)

Abstract

In this paper, we show a dynamic and personalized curriculum generation method that analyses the causality and dependency between learning objects. This method calculates the strength and extracts the rules of causality and dependency between individual learning objects, described beforehand, using the results of testing, trends of understanding within a particular community, and definitions of learning objects with a learning order. This method determines the important learning objects for an individual user, and an order for effective learning, by analysing the results of an individual and those of a particular community. It dynamically computes changing relationships between learning objects and the learning situation of individual users, and enables generation of a personalized curriculum that supports effective learning.

Original languageEnglish
Title of host publication2007 IEEE International Workshop on Databases for Next-Generation Researchers, SWOD 2007 - Held in Conjunction with ICDE 2007
Pages91-96
Number of pages6
DOIs
Publication statusPublished - 2007 Dec 1
Event3rd IEEE International Workshop on Databases for Next-Generation Researchers, SWOD 2007, in Conjunction with the ICDE 2007 Conference - Istanbul, Turkey
Duration: 2007 Apr 152007 Apr 15

Publication series

Name2007 IEEE International Workshop on Databases for Next-Generation Researchers, SWOD 2007 - Held in Conjunction with ICDE 2007

Other

Other3rd IEEE International Workshop on Databases for Next-Generation Researchers, SWOD 2007, in Conjunction with the ICDE 2007 Conference
Country/TerritoryTurkey
CityIstanbul
Period07/4/1507/4/15

ASJC Scopus subject areas

  • Software

Fingerprint

Dive into the research topics of 'Dynamic and personalized curriculum-generation method analysing causality and dependency between learning objects'. Together they form a unique fingerprint.

Cite this