Tuning Perceptions and Inferences to See a Graph in a New Way

Hillary Lucille Swanson, Bruce Sherin, Uri Wilensky

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

Abstract

This work examines the representational and social features of a computational modeling activity to understand the role they play in helping a student make sense of a simulation graph. Specifically, it examines shifts in the student's thinking as she reflects on the output of a computational model of thermal equilibration, which she has built. By analyzing the student's trajectory through the lens of Coordination Class theory, the paper illuminates how she comes to see the simulation graph in a more sophisticated way through her interactions with the technology and the interviewer. The paper shows how these features of the computational modeling activity support her transition from seeing oscillations of temperature about the mean as a visual effect caused by the computer screen, to understanding that oscillation amplitudes are related to microscopic fluctuations in temperature, which decrease as the number of particles in the system increases.

Original languageEnglish (US)
Title of host publicationInternational Collaboration toward Educational Innovation for All
Subtitle of host publicationOverarching Research, Development, and Practices - 16th International Conference of the Learning Sciences, ICLS 2022
EditorsClark Chinn, Edna Tan, Carol Chan, Yael Kali
PublisherInternational Society of the Learning Sciences (ISLS)
Pages1589-1592
Number of pages4
ISBN (Electronic)9781737330653
StatePublished - 2022
Event16th International Conference of the Learning Sciences, ICLS 2022 - Virtual, Online, Japan
Duration: Jun 6 2022Jun 10 2022

Publication series

NameProceedings of International Conference of the Learning Sciences, ICLS
ISSN (Print)1814-9316

Conference

Conference16th International Conference of the Learning Sciences, ICLS 2022
Country/TerritoryJapan
CityVirtual, Online
Period6/6/226/10/22

Funding

This work was supported by the National Science Foundation (1842375).

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Education

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