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Creative thinking encompasses innovative and unconventional methods for addressing challenges, often leading to groundbreaking solutions. Instead of focusing solely on enhancing existing systems, such as increasing smartphone battery capacity, creative thinking might inspire advancements like energy-efficient batteries or processors that minimize power consumption. This multidimensional approach underscores the importance of exploring novel pathways to innovation.
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CAP: The creativity assessment platform for online testing and automated scoring.

John D Patterson1, Jimmy Pronchick2, Ruchi Panchanadikar3

  • 1Department of Psychology, The Pennsylvania State University, 140 Moore Building, University Park, PA, 16802, USA. jpttrsn@psu.edu.

Behavior Research Methods
|August 18, 2025
PubMed
Summary

The Creativity Assessment Platform (CAP) is a new, free web tool that makes creativity assessments accessible to educators and researchers. It simplifies assessment creation, data collection, and scoring using machine learning, promoting wider use of creativity measurement.

Keywords:
Automated creativity scoringComputational psychometricsDivergent thinkingOnline data collectionScientific creativityVisual creativity

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Area of Science:

  • Psychology
  • Educational Technology
  • Human-Computer Interaction

Background:

  • Creativity is a vital 21st-century skill, necessitating effective assessment tools for education, research, and industry.
  • Current software for creativity assessment often requires technical expertise, limiting accessibility for many.
  • There is a need for user-friendly, accessible platforms to measure and foster creativity.

Purpose of the Study:

  • Introduce the Creativity Assessment Platform (CAP), a free web application designed to simplify the creation, administration, and scoring of creativity assessments.
  • To provide a multilingual and automated solution for creativity measurement, enhancing accessibility and reproducibility.
  • To democratize the process of creativity assessment for a broader audience.

Main Methods:

  • Developed CAP, a web-based application with a point-and-click interface for creating custom assessments in ten languages.
  • Integrated machine learning models for automatic scoring of creativity tasks, including the Cross-Lingual Alternate Uses Scoring (CLAUS) large language model.
  • Implemented a centralized dashboard for data monitoring, automated scoring, and one-click generation of Methods section text.

Main Results:

  • CAP enables users to create and administer diverse creativity tasks (e.g., Short Story, Drawing, Scientific Creative Thinking Test) easily.
  • The platform offers automated scoring with machine learning models that predict human creativity ratings across ten languages.
  • CAP facilitates data management and promotes transparency and reproducibility through automated reporting features.

Conclusions:

  • CAP significantly lowers the barrier to entry for conducting creativity assessments, making sophisticated measurement tools widely available.
  • The platform's multilingual capabilities and automated scoring enhance the efficiency and global applicability of creativity research and education.
  • CAP empowers educators, researchers, and practitioners to better understand and cultivate creativity through accessible and reproducible measurement.