Frog Pond: A code-first learning environment on evolution and natural selection

Michael S. Horn, Corey Brady, Arthur Hjorth, Aditi Wagh, Uri Wilensky

Research output: Chapter in Book/Report/Conference proceedingConference contribution

15 Scopus citations

Abstract

Understanding processes of evolution and natural selection is both important and challenging for learners. We describe a "code-first" learning environment called Frog Pond designed to introduce natural selection to elementary and middle school aged learners. Learners use NetTango, a blocks-based programming interface to NetLogo, to control frogs inhabiting a lily pond. Simple programs result in changes to the frog population over successive generations. Our approach foregrounds computational thinking as a bridge to understanding evolution as an emergent phenomenon.

Original languageEnglish (US)
Title of host publicationIDC 2014 - Proceedings of the 2014 Conference on Interaction Design and Children
PublisherAssociation for Computing Machinery
Pages357-360
Number of pages4
ISBN (Print)9781450322720
DOIs
StatePublished - Jan 1 2014
Event13th International Conference on Interaction Design and Children, IDC 2014 - Aarhus, Denmark
Duration: Jun 17 2014Jun 20 2014

Publication series

NameACM International Conference Proceeding Series

Other

Other13th International Conference on Interaction Design and Children, IDC 2014
CountryDenmark
CityAarhus
Period6/17/146/20/14

Keywords

  • Agent-based modeling
  • Children
  • Code-first environment
  • Design
  • Evolution
  • Learning
  • Natural selection

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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  • Cite this

    Horn, M. S., Brady, C., Hjorth, A., Wagh, A., & Wilensky, U. (2014). Frog Pond: A code-first learning environment on evolution and natural selection. In IDC 2014 - Proceedings of the 2014 Conference on Interaction Design and Children (pp. 357-360). (ACM International Conference Proceeding Series). Association for Computing Machinery. https://doi.org/10.1145/2593968.2610491