Use of Soft sets and the Bloom's Taxonomy for Assessing Learning Skills
Publish place: Transactions on Fuzzy Sets and Systems، Vol: 1، Issue: 1
Publish Year: 1401
Type: Journal paper
Language: English
View: 201
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Document National Code:
JR_TFSS-1-1_007
Index date: 17 January 2023
Use of Soft sets and the Bloom's Taxonomy for Assessing Learning Skills abstract
Learning, a universal process that all individuals experience, is a fundamental component of human cognition. It combines cognitive, emotional and environmental in uences for acquiring or enhancing ones knowledge and skills. Volumes of research have been written about learning and many theories have been developed for the description of its mechanisms. The goal was to understand objectively how people learn and then develop teaching approaches accordingly. In this paper soft sets, a generalization of fuzzy sets introduced in 1999 by D. Molodstov as a new mathematical tool for dealing with the uncertainty in a parametric manner, are used for assessing student learning skills with the help of the Blooms taxonomy. Blooms taxonomy has been applied and is still applied by generations of teachers as a teaching tool to help balance assessment by ensuring that all orders of thinking are exercised in student learning. The innovative assessment method introduced in this paper is very useful when the assessment has qualitative rather than quantitative characteristics. A classroom application is also presented illustrating its applicability under real conditions.
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Use of Soft sets and the Bloom's Taxonomy for Assessing Learning Skills authors
Michael Voskoglou
Department of Mathematical Sciences, Graduate Technological Educational Institute of Western Greece, Meg. Alexandrou ۱, ۲۶۳ ۳۴ Patras, Greece.
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