Use of Soft sets and the Bloom's Taxonomy for Assessing Learning Skills
الموضوعات : Transactions on Fuzzy Sets and Systems
Michael Voskoglou
1
(Department of Mathematical Sciences, Graduate Technological Educational Institute of Western Greece, Meg. Alexandrou 1, 263 34 Patras, Greece.)
الکلمات المفتاحية: fuzzy sets, Learning, Soft sets, Blooms taxonomy, Assessment methods,
ملخص المقالة :
Learning, a universal process that all individuals experience, is a fundamental component of human cognition. It combines cognitive, emotional and environmental influences 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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