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A new fuzzy peer assessment methodology for cooperative learning of students
journal contribution
posted on 2015-07-01, 00:00 authored by K C Chai, K M Tay, Chee Peng LimChee Peng LimIn 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 computingVolume
32Pagination
468 - 480Publisher
ElsevierLocation
Amsterdam, The NetherlandsPublisher DOI
ISSN
1568-4946Language
engPublication classification
C Journal article; C1 Refereed article in a scholarly journalCopyright notice
2015, ElsevierUsage metrics
Categories
Keywords
Science & TechnologyTechnologyComputer Science, Artificial IntelligenceComputer Science, Interdisciplinary ApplicationsComputer SciencePerceptual computingPeer assessmentFuzzy preference relationsLinguistic gradesIndividual weighting factorMODELMARKINGSYSTEMInformation SystemsArtificial Intelligence and Image Processing
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