Journal of information and communication convergence engineering

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
권호 표지

Self-Directed Learning Evaluation Using Fuzzy Grade Sheets

  • Kim, Kwang-Baek (Department of Computer Engineering, University of Silla) ;
  • Kim, Byung-Joo (School of Network and Information Engineering, Youngsan University) ;
  • Cho, Jae-Hyun (Department of Computer Information, and Catholic University of Pusan)
  • Published : 2004.06.01
Download PDF
⟨ Previous Next ⟩

Abstract

This paper is about the use of existing evaluation methods, which evaluate learning determined by the score of an exam, which is either a multiple-choice type or single choice type question. These scores don't show the objective evaluations that cause some negative opinions about the scores. In this paper, we propose that the evaluation of the methods of self-directed learning use the triangle-type function of the fuzzy theory so that the learner can objectively evaluate their own learning ability. The proposed method classifies the result of learning into three fuzzy grades to calculate membership, and evaluate the result of an exam according to the final fuzzy grade degree as applied to the fuzzy grade sheets.

Keywords

References

  1. H. J. Kim and S. H. Cho, 'Design and Development of Web-Based Learning System Using Self-Directed Collaborative Learning Model,' Journal of Korean Association of Computer Education, Vol. 5, No. 1, pp.67-73, 2002
  2. K. H. Choo, S. Y. Park, C. S. Kim, 'Implementation the Estimation System Based on the Web for Tutoring Accomplishment Analysis,' Proceedings of Korea Multimedia, Vol. 2, No.1, pp.222-227, 1999
  3. L. H. Jang and T. K. Kim, 'Fuzzy perfonnance assessment methods and mathematical educations,' Journal ofKorea Fuzzy Logic and Intelligent Systems, Vol. 11, No.8, pp.742-754, 2001
  4. D. G. Sin, S. H. Won and H. M. Chung, 'A Study on Education Evaluation Method using Fuzzy Theory,' Journal ofKorea Fuzzy Logic and Intelligent Systems, Vol. 6, No. 1, pp.74-82, 1996
  5. T. A. Runkler and J.C. Bezde k, 'Function approximation with polynomial membership functions and alternation cluster estimation,' Journal ofFuzzy Sets and Systems, VoI.101, pp.207-218, 1999 https://doi.org/10.1016/S0165-0114(98)00164-X
  6. L. A. Zadeh, 'A Fuzzy-Algorithmic Approach to the Definition of Complex or Imprecise Concepts,' Int. Journal ofMan-Machine Studies, VoI.8, pp.249-291, 1976 https://doi.org/10.1016/S0020-7373(76)80001-6
  7. Dubois, D. and Prade, H., Fuzzy Sets and System: Theory and application, Academic Press, pp.393, 1980
  8. Dubois, D. and Prade, H., 'A Review of Fuzzy Set Aggregation Connective,' Journal of Information Science, Vol. 36, No.1, pp.85-121, 1985 https://doi.org/10.1016/0020-0255(85)90027-1