Modeling Creativity in Visual Programming: From Theory to Practice

Anastasia Kovalkov, Benjamin Paaßen, Avi Segal, Kobi Gal, Niels Pinkwart

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Promoting creativity is considered an important goal of education, but creativity is notoriously hard to define and measure. In this paper, we make the journey from defining a formal creativity and applying the measure in a practical domain. The measure relies on core theoretical concepts in creativity theory, namely fluency, flexibility, and originality, We adapt the creativity measure for Scratch projects. We designed a machine learning model for predicting the creativity of Scratch projects, trained and evaluated on ratings collected from expert human raters. Our results show that the automatic creativity ratings achieved by the model aligned with the rankings of the projects of the expert raters more than the experts agreed with each other. This is a first step in providing computational models for describing creativity that can be applied to educational technologies, and to scale up the benefit of creativity education in schools.

Original languageAmerican English
Title of host publicationProceedings of the 14th International Conference on Educational Data Mining, EDM 2021
EditorsI-Han Hsiao, Shaghayegh Sahebi, Francois Bouchet, Jill-Jenn Vie
PublisherInternational Educational Data Mining Society
Pages518-524
Number of pages7
ISBN (Electronic)9781733673624
StatePublished - 1 Jan 2021
Event14th International Conference on Educational Data Mining, EDM 2023 - Paris, France
Duration: 29 Jun 20212 Jul 2021

Publication series

NameProceedings of the 14th International Conference on Educational Data Mining, EDM 2021

Conference

Conference14th International Conference on Educational Data Mining, EDM 2023
Country/TerritoryFrance
CityParis
Period29/06/212/07/21

Keywords

  • Creativity
  • Creativity Tests
  • Visual Programming Environments

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Information Systems

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