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Kenes Beketayev1, Mark A Runco2

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Summary

A new automated method for assessing divergent thinking (DT) shows strong correlation with traditional flexibility scoring. This semantics-based algorithmic (SBA) approach offers efficient and valid creative potential assessment.

Keywords:
Divergent thinkingassessing creativityassociative networkscomputer creativitycreativity testflexibilityideasideational fluencyoriginalitysemantic networks

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Area of Science:

  • Psychology
  • Cognitive Science
  • Artificial Intelligence

Background:

  • Divergent thinking (DT) is crucial for assessing creative potential.
  • Traditional scoring of DT tests can be time-consuming and subjective.
  • Automated assessment methods are needed for large-scale evaluations.

Purpose of the Study:

  • To introduce and evaluate a novel semantics-based algorithmic (SBA) method for automated DT assessment.
  • To compare the SBA method's scoring with traditional DT scoring metrics (fluency, originality, flexibility).

Main Methods:

  • Developed a fully automated SBA algorithm for DT assessment.
  • Administered the
  • Many Uses Test
  • to 250 examinees via digital devices.
  • Compared SBA scores with traditional fluency, originality, and flexibility scores.

Main Results:

  • A significant correlation (r = .74) was found between SBA scores and traditional flexibility scores.
  • SBA scores showed insignificant correlations with GPA, supporting discriminant and construct validity.
  • The SBA method offers nearly-immediate computation, ideal for large-scale assessments.

Conclusions:

  • The SBA method provides a valid and efficient alternative for assessing divergent thinking.
  • Algorithmic scoring of DT is supported by the strong correlation with established flexibility measures.
  • The SBA method is particularly suitable for large-scale divergent thinking assessments.