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How Interval and Fuzzy Techniques Can Improve Teaching
Author(s) -
Olga Kosheleva,
Karen Villaverde
Publication year - 2017
Publication title -
studies in computational intelligence
Language(s) - English
Resource type - Book series
SCImago Journal Rank - 0.185
H-Index - 68
eISSN - 1860-9503
pISSN - 1860-949X
DOI - 10.1007/978-3-662-55993-2
Subject(s) - computer science , interval (graph theory) , fuzzy logic , process (computing) , artificial intelligence , mathematics education , machine learning , mathematics , combinatorics , operating system
There are many papers that experimentally compare effectiveness of different teaching techniques. Most of these papers use traditional statistical approach to process the experimental results. The traditional statistical approach is well suited to numerical data but often, what we are processing is either intervals (e.g., A means anything from 90 to 100) or fuzzy-type perceptions, words from the natural language like “understood well” or ”understood reasonably well”. We show that the use of intervals and fuzzy techniques leads to more adequate processing of educational data.

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