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A new fuzzy peer assessment methodology for cooperative learning of students

Version 2 2024-06-06, 08:06
Version 1 2016-01-25, 11:01
journal contribution
posted on 2024-06-06, 08:06 authored by KC Chai, KM Tay, Chee Peng Lim
In this paper, a new fuzzy peer assessment methodology that considers vagueness and imprecision of words used throughout the evaluation process in a cooperative learning environment is proposed. Instead of numerals, words are used in the evaluation process, in order to provide greater flexibility. The proposed methodology is a synthesis of perceptual computing (Per-C) and a fuzzy ranking algorithm. Per-C is adopted because it allows uncertainties of words to be considered in the evaluation process. Meanwhile, the fuzzy ranking algorithm is deployed to obtain appropriate performance indices that reflect a student's contribution in a group, and subsequently rank the student accordingly. A case study to demonstrate the effectiveness of the proposed methodology is described. Implications of the results are analyzed and discussed. The outcomes clearly demonstrate that the proposed fuzzy peer assessment methodology can be deployed as an effective evaluation tool for cooperative learning of students.

History

Journal

Applied soft computing

Volume

32

Pagination

468-480

Location

Amsterdam, The Netherlands

ISSN

1568-4946

Language

eng

Publication classification

C Journal article, C1 Refereed article in a scholarly journal

Copyright notice

2015, Elsevier

Publisher

Elsevier