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Metaphorical Description and Model Description of Complex Systems.

Huaxin Huang1, Yuhang Li1

  • 1Center for the Study of Language and Cognition, Zhejiang University, Hangzhou 310028, Zhejiang, China.

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Summary

Complexity science matures by shifting from metaphorical to model descriptions. This study compares formal and relevance theory models, proposing fuzzy evaluation for educational complexity.

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Area of Science:

  • Complexity Science
  • Educational Evaluation

Background:

  • Complexity science advances from metaphorical to model-based descriptions.
  • Two key model description methods for complex systems are formal system models and relevance theory models.

Purpose of the Study:

  • To compare the advantages and disadvantages of formal system models and relevance theory models.
  • To propose a fuzzy evaluation method for educational complexity and scientificity.

Main Methods:

  • Comparative analysis of formal system models and relevance theory models.
  • Application of fuzzy evaluation, a mathematical approach based on fuzzy theory.

Main Results:

  • Both formal and relevance theory models offer unique, significant perspectives on complex systems.
  • Fuzzy evaluation provides a quantitative framework for complex educational assessment.

Conclusions:

  • The future of complexity science lies in the alternation, not integration, of different models.
  • Fuzzy evaluation offers a robust method for scientifically assessing educational complexity.