A Fuzzy Model for Analogical Problem Solving

TL;DR

This paper introduces a fuzzy model for analogical reasoning, representing its steps with linguistic labels and measuring individuals' problem-solving abilities using the Shannon-Wiener diversity index, supported by a classroom experiment.

Contribution

It presents a novel fuzzy modeling approach for analogical reasoning steps and compares it with a stochastic model using Markov chains.

Findings

Fuzzy model effectively describes analogical reasoning process.

Shannon-Wiener index quantifies problem-solving abilities.

Classroom experiment demonstrates practical applicability.

Abstract

In this paper we develop a fuzzy model for the description of the process of Analogical Reasoning by representing its main steps as fuzzy subsets of a set of linguistic labels characterizing the individuals' performance in each step and we use the Shannon- Wiener diversity index as a measure of the individuals' abilities in analogical problem solving. This model is compared with a stochastic model presented in author's earlier papers by introducing a finite Markov chain on the steps of the process of Analogical Reasoning. A classroom experiment is also presented to illustrate the use of our results in practice.