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Klir, G. J. & Folger, T. A. (1988), Fuzzy Sets, Uncertainty and Information, Prentice-Hall, London.

has been cited by the following article:

Article

An Application of the Generalized Rectangular Fuzzy Model to Critical Thinking Assessment

1National University, Department of Mathematics and Natural Sciences, Los Angeles, California, USA

2Graduate Technological Educational Institute (T. E. I.) of Western Greece, Department of Applied Mathematics, Patras, Greece


American Journal of Educational Research. 2016, Vol. 4 No. 5, 397-403
DOI: 10.12691/education-4-5-6
Copyright © 2016 Science and Education Publishing

Cite this paper:
Igor Ya. Subbotin, Michael Gr. Voskoglou. An Application of the Generalized Rectangular Fuzzy Model to Critical Thinking Assessment. American Journal of Educational Research. 2016; 4(5):397-403. doi: 10.12691/education-4-5-6.

Correspondence to: Igor  Ya. Subbotin, National University, Department of Mathematics and Natural Sciences, Los Angeles, California, USA. Email: isubboti@nu.edu

Abstract

The authors apply the Generalized Rectangular Model (GRM) for assessing students’ critical thinking skills. GRM is a variation of the center of gravity (COG) defuzzification technique. The COG technique was properly adapted and used several times in the past by the present authors as an assessment method, called here the Rectangular Model (RM). The central idea of the GRM is the “movement” to the left of the rectangles appearing in the membership function’s graph of the RM, thus making the adjacent rectangles to share common parts. This treatment reflects better than RM the ambiguous assessment cases of student scores being at the boundaries between two successive assessment grades (e.g. something like 84-85% being at the boundaries between A and B) and therefore belonging to the common parts of the above rectangles. In fact, in GRM, assuming that these scores belong to both of the successive assessment grades, we consider twice the common parts of the rectangles for calculating the COG of the level’s section lying between the resulting graph and the OX axis. Our results are illustrated on the data of a classroom application performed in one of the Los Angeles Unified District High Schools and connecting the students CT skills with their language competencies.

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