CFP last date
20 May 2024
Reseach Article

Evaluating Students� Performance using Fuzzy Logic

Published on February 2013 by Shilpa N. Ingoley, J.w. Bakal
International Conference on Recent Trends in Information Technology and Computer Science 2012
Foundation of Computer Science USA
ICRTITCS2012 - Number 9
February 2013
Authors: Shilpa N. Ingoley, J.w. Bakal
8d4d52e1-72ad-4c96-bf75-248370725853

Shilpa N. Ingoley, J.w. Bakal . Evaluating Students� Performance using Fuzzy Logic. International Conference on Recent Trends in Information Technology and Computer Science 2012. ICRTITCS2012, 9 (February 2013), 15-20.

@article{
author = { Shilpa N. Ingoley, J.w. Bakal },
title = { Evaluating Students� Performance using Fuzzy Logic },
journal = { International Conference on Recent Trends in Information Technology and Computer Science 2012 },
issue_date = { February 2013 },
volume = { ICRTITCS2012 },
number = { 9 },
month = { February },
year = { 2013 },
issn = 0975-8887,
pages = { 15-20 },
numpages = 6,
url = { /proceedings/icrtitcs2012/number9/10310-1444/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Recent Trends in Information Technology and Computer Science 2012
%A Shilpa N. Ingoley
%A J.w. Bakal
%T Evaluating Students� Performance using Fuzzy Logic
%J International Conference on Recent Trends in Information Technology and Computer Science 2012
%@ 0975-8887
%V ICRTITCS2012
%N 9
%P 15-20
%D 2013
%I International Journal of Computer Applications
Abstract

Fair results give motivation and encouragement to the students. So reforms in education are must not only in curriculum development but also in students' performance assessment. Proposed method is useful when questions in the examination are of subjective or objective type and total time duration is given to attempt all questions rather than individual question. This method considers importance and complexity of question into account. It makes use of fuzzy inference system (FIS) and fuzzy logic.

References
  1. Ting-Kueili , Shyi-Ming Chen "A New Method For Students' Learning Achievement Evaluation By automatically Generating The Weights of Attributes with Fuzzy Reasoning Capability" (IEEE 2009 Proceedings of the Eighth International Conference on Machine Learning and Cybernetics, Baoding, 12-15 July 2009)
  2. R. Biswas , "An application of fuzzy sets in students' evaluation," Fuzzy Sets Syst. , vol. 74, no. 2, pp. 187–194, 1995.
  3. S. M. Chen and C. H. Lee, "New methods for students' evaluating using fuzzy sets," Fuzzy Sets Syst. , vol. 104, no. 2, pp. 209–218, 1999.
  4. Ibrahim Saleh, Seong-in Kim "A fuzzy system for evaluating students' learning achievement" (Expert Systems with Applications 36 (2009) 6236–6243)
  5. Shih-Ming Bai, Shyi-Ming Chen "Automatically constructing grade membership functions of fuzzy rules for students' evaluation" ELSEVIERScienceDirect Expert Systems with Applications 35 (2008) 1408–1414
  6. Hui-YuWang, Shyi-Ming Chen "Evaluating students' answerscripts using vague values" Springer Science+Business Media, LLC 2007
  7. James R. Nolan "An expert fuzzy classification system for supporting the grading of student writing samples" Expert Systems With Applications 15 (1998) 59–68
  8. Saleh, I. , & Kim, S. (2009). A fuzzy system for evaluation students' learning achievement. Expert Systems with Applications, 36(3), 6234–6236.
  9. Hui-Yu Wang and Shyi-Ming Chen, "Evaluating Students' Answerscripts Using Fuzzy Numbers Associated With Degrees of Confidence" IEEE TRANSACTIONS ON FUZZY SYSTEMS, VOL. 16, NO. 2, APRIL 2008 "
  10. Lotfi A. Zadeh "FUZZY LOGIC SYSTEMS: ORIGIN, CONCEPTS, AND TRENDS"
  11. Timothy J. Ross "Fuzzy Logic with Engineering Applications" Second Edition (WILEY Edition)
  12. Wang, H. Y. , & Chen, S. M. . Evaluating students' answerscripts using fuzzy numbers associated with degrees of confidence. (IEEE 2008 Transactions on Fuzzy Systems, 16(2), 403–415. )
  13. S. M. Bai and S. M. Chen, "Automatically constructing grade membership functions for students' evaluation for fuzzy grading systems," in Proc. 2006 World Automat. Congr. , Budapest, Hungary, 2006.
  14. Bai, S. M. , & Chen, S. M. (2008a). Automatically constructing concept maps based on fuzzy rules for adaptive learning systems. Expert Systems with Applications, 35(1), 41–49.
  15. Bai, S. M. , & Chen, S. M. (2008b). Automatically constructing grade membership functions of fuzzy rules for students' evaluation. Expert Systems with Applications, 35(3), 1408–1414.
Index Terms

Computer Science
Information Sciences

Keywords

Student Evaluation Fuzzification Defuzzification Computational Intelligent (ci) Soft Computing