Inferring Creativity in Visual Programming Environments

Anastasia Kovalkov, Avi Segal, Kobi Gal

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

Abstract

This paper explores the use of data analytics for identifying creativity in visual programming. Visual programming environments are increasingly included in the schools curriculum. Their potential for promoting creative thinking in students is an important factor in their adoption. However, there does not exist a standard approach for detecting creativity in students' programming behavior, and analyzing programs manually requires human expertise and is time consuming. This work provides a computational tool for measuring creativity in visual programming that combines theory from the literature with data mining approaches. It adapts classical dimensions of creative processes to our setting, and considers new aspects such as visual elements of the visual programming projects. We apply our approach to the Scratch programming environment, measuring the creativity score of hundreds of projects. We show a preliminary comparison between our metrics and teacher ratings.

Original languageAmerican English
Title of host publicationL@S 2020 - Proceedings of the 7th ACM Conference on Learning @ Scale
Pages269-272
Number of pages4
ISBN (Electronic)9781450379519
DOIs
StatePublished - 12 Aug 2020
Event7th Annual ACM Conference on Learning at Scale, L@S 2020 - Virtual, Online, United States
Duration: 12 Aug 202014 Aug 2020

Publication series

NameL@S 2020 - Proceedings of the 7th ACM Conference on Learning @ Scale

Conference

Conference7th Annual ACM Conference on Learning at Scale, L@S 2020
Country/TerritoryUnited States
CityVirtual, Online
Period12/08/2014/08/20

Keywords

  • creativity
  • creativity tests
  • visual programming environments

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Networks and Communications

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