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Estimating Levels of Learning Outcomes Acquirement Based on Fuzzy Sets, Relations, and Their Compositions

Estimating Levels of Learning Outcomes Acquirement Based on Fuzzy Sets, Relations, and Their Compositions
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Author(s): Aleksandra Mreła (Kazimierz Wielki University in Bydgoszcz, Poland) and Oleksandr Sokolov (Nicolaus Copernicus University in Torun, Poland)
Copyright: 2021
Pages: 24
Source title: Handbook of Research on Modern Educational Technologies, Applications, and Management
Source Author(s)/Editor(s): Mehdi Khosrow-Pour D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-7998-3476-2.ch006

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Abstract

New curriculum designers should prepare the set of learning outcomes that will be studied by students, and their acquirement will be verified by teachers. It is not easy to estimate whether students achieved the required learning outcomes even in the range of knowledge and skills, but when the competencies are considered, it becomes harder. Because of the convenience of using the linguistic terms (excellent, poor, good, and so on), it is better to apply fuzzy relations (type 1 if the numbers are chosen or type 2 if the sets are used), which can handle with the linguistic terms better than classical relations. The estimation of the learning outcome's acquirement can be conducted on the bases of a test or tests. For calculating the levels of learning outcome's acquirement, two fuzzy input relations are designed. Experts build one based on their knowledge, and the second one is based on the test results. The output relation, showing levels of learning outcome/outcomes' acquirement, is built with the application of the S-T composition of the first and second relations.

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