Broadening learning sciences theoretical lenses to understand young children’s sensemaking

Danielle Keifert, X. Christine Wang, Dania P. Sacks, Sharona T. Levy, Xintian Tu, Joshua Danish, Megan Humburg, Noel Enyedy

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

Abstract

If “the theories that we propose and the assumptions that we hold fundamentally shape the questions we ask, what we notice, and what we design for” (ICLS Call for Papers), we must understand the full diversity of human learning, including critically the learning of young children (ages 5-8). This session explores how several scholars have applied and pushed for revisions of existing theories as the Learning Sciences field seeks to better understand young children’s sensemaking. Each paper takes up two central questions: (1) How is existing LS theory drawn upon in each study? (2) How is new theory built or existing LS theory modified in each study? The goal of attending to these questions is that participants in this symposium might better understand the ways that existing theory does and does not work when studying young children.

Original languageAmerican English
Title of host publication14th International Conference of the Learning Sciences
Subtitle of host publicationThe Interdisciplinarity of the Learning Sciences, ICLS 2020 - Conference Proceedings
EditorsMelissa Gresalfi, Ilana Seidel Horn
PublisherInternational Society of the Learning Sciences (ISLS)
Pages390-397
Number of pages8
ISBN (Electronic)9781732467255
StatePublished - 2020
Event14th International Conference of the Learning Sciences: The Interdisciplinarity of the Learning Sciences, ICLS 2020 - Nashville, United States
Duration: 19 Jun 202023 Jun 2020

Publication series

NameComputer-Supported Collaborative Learning Conference, CSCL
Volume1

Conference

Conference14th International Conference of the Learning Sciences: The Interdisciplinarity of the Learning Sciences, ICLS 2020
Country/TerritoryUnited States
CityNashville
Period19/06/2023/06/20

All Science Journal Classification (ASJC) codes

  • Human-Computer Interaction
  • Education

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