A two-phase fuzzy mining and learning algorithm for adaptive learning environment

Chang Jiun Tsai, S. S. Tseng, Chih Yang Lin

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

48 Scopus citations


As computer-assisted instruction environment becomes more popular over the world, the analysis of historical learning records of students becomes more important. In this work, we propose a Two-Phase Fuzzy Mining and Learning Algorithm, integrating data mining algorithm, fuzzy set theory, and look ahead mechanism, to find the embedded information, which can be provided to teachers for further analyzing, refining or reorganizing the teaching materials and tests, from historical learning records.

Original languageEnglish
Title of host publicationComputational Science – ICCS 2001 - International Conference, Proceedings
EditorsVassil N. Alexandrov, Jack J. Dongarra, Benjoe A. Juliano, Rene S. Renner, C.J. Kenneth Tan
PublisherSpringer Verlag
Number of pages10
ISBN (Print)3540422331, 9783540422334
StatePublished - 2001
EventInternational Conference on Computational Science, ICCS 2001 - San Francisco, United States
Duration: 28 May 200130 May 2001

Publication series

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


ConferenceInternational Conference on Computational Science, ICCS 2001
Country/TerritoryUnited States
CitySan Francisco


  • CAI
  • Data Mining
  • Fuzzy set theory
  • Machine learning


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