Concept maps construction based on student-problem chart

Jiann Cherng Shieh, Yi Ting Yang

Research output: Contribution to conferencePaperpeer-review

4 Citations (Scopus)

Abstract

Concept maps can help students learn more meaningfully. According to test scores only, students were divided into three groups of high-score, middle-score and low-score, in the previous works, researchers then applied data mining association rule technique to analysis different student groups' assessment data to construct corresponding concept maps. However, for considering more accurate to evaluate students' performance states and various possible distributions of students' assessment data, in this research, we apply student-problem chart to obtain students response patterns for grouping purpose. We generate six response pattern groups for 30131 students. Using association rule data mining technique also, we will construct more precise concept maps for students of different groups individually.

Original languageEnglish
Pages324-327
Number of pages4
DOIs
Publication statusPublished - 2014 Sept 29
Event3rd IIAI International Conference on Advanced Applied Informatics, IIAI-AAI 2014 - Kitakyushu, Japan
Duration: 2014 Aug 312014 Sept 4

Other

Other3rd IIAI International Conference on Advanced Applied Informatics, IIAI-AAI 2014
Country/TerritoryJapan
CityKitakyushu
Period2014/08/312014/09/04

Keywords

  • Association rule
  • Concept map
  • Data mining
  • SP chart

ASJC Scopus subject areas

  • Information Systems

Fingerprint

Dive into the research topics of 'Concept maps construction based on student-problem chart'. Together they form a unique fingerprint.

Cite this