Volume 5 Number 12 (Dec. 2010)
Home > Archive > 2010 > Volume 5 Number 12 (Dec. 2010) >
JSW 2010 Vol.5(12): 1355-1362 ISSN: 1796-217X
doi: 10.4304/jsw.5.12.1355-1362

Adaptive Support for Student Learning in an e-Portfolio Platform by Knowledge Discovery and Case-based Reasoning

Chih-Kun Ke1, Mei-Yu Wu2

1Department of Information Management, National Taichung Institute of Technology, Taichung, Taiwan, ROC
2Department of Information Management, Chung Hua University, Hsinchu, Taiwan, ROC

Abstract—Constructing an e-portfolio platform for students is a modern educational trend. However, a student’s learning context is not analyzed in the current e-portfolio platform. In this research a model was designed for identifying the specific learning context and providing the corresponding knowledge support. A system framework which uses advanced information techniques is proposed. Information Retrieval (IR) technique extracts and analyzes key concepts from the student’s previous e-portfolio records. The data mining technique discovers hidden knowledge rules from key concepts. Various context-knowledge views were constructed based on discovered knowledge rules. Besides, Case-Based Reasoning (CBR) and profiling techniques were used to identify learning context and design adaptive knowledge recommendation mechanisms. Therefore, after identifying current learning contexts, the system would recommend previously documented knowledge to assist the student. A prototype system was developed to demonstrate the effectiveness of providing knowledge to help students solve learning problem(s).

Index Terms—e-portfolio, learning context, data mining, adaptive knowledge support.


Cite: Chih-Kun Ke, Mei-Yu Wu, "Adaptive Support for Student Learning in an e-Portfolio Platform by Knowledge Discovery and Case-based Reasoning," Journal of Software vol. 5, no. 12, pp. 1355-1362, 2010.

General Information

ISSN: 1796-217X (Online)
Frequency:  Quarterly
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, CNKIGoogle Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsweditorialoffice@gmail.com
  • Mar 01, 2024 News!

    Vol 19, No 1 has been published with online version    [Click]

  • Jan 04, 2024 News!

    JSW will adopt Article-by-Article Work Flow

  • Apr 01, 2024 News!

    Vol 14, No 4- Vol 14, No 12 has been indexed by IET-(Inspec)     [Click]

  • Apr 01, 2024 News!

    Papers published in JSW Vol 18, No 1- Vol 18, No 6 have been indexed by DBLP   [Click]

  • Nov 02, 2023 News!

    Vol 18, No 4 has been published with online version   [Click]