A hybrid method for the assessment of analogical reasoning skills

  • سال انتشار: 1401
  • محل انتشار: نشریه گسترش مجموعه فازی و کاربردهای آن، دوره: 3، شماره: 2
  • کد COI اختصاصی: JR_JFEA-3-2_004
  • زبان مقاله: انگلیسی
  • تعداد مشاهده: 168
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نویسندگان

Michael Voskoglou

Mathematical Sciences, Graduate TEI of Western Greece.

Said Broumi

Laboratory of Information Processing, Faculty of Science Ben M&#۰۳۹;Sik, University Hassan II, Casablanca, Morocco.

چکیده

Much of a person’s cognitive activity depends on the ability to reason analogically. Analogical reasoning (AR) compares the similarities between new and past knowledge and uses them to obtain an understanding of the new knowledge. The mechanisms, however, under which the human mind works are not fully investigated and as a result AR is characterized by a degree of fuzziness and uncertainty. Probability theory has been proved sufficient for dealing with the cases of uncertainty due to randomness. During the last ۵۰-۶۰ years, however, various mathematical theories have been introduced for tackling effectively the other forms of uncertainty, including fuzzy sets, intuitionistic fuzzy sets, neutrosophic sets, rough sets, etc. The combination of two or more of those theories gives frequently better results for the solution of the corresponding problems. A hybrid assessment method of AR skills under fuzzy conditions is developed in this work using Grey Numbers (GN) and soft sets as tools, which is illustrated by an application on evaluating student analogical problem solving skills.

کلیدواژه ها

Soft set, Grey Number, Analogical Reasoning, Assessment under Fuzzy Conditions

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