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Developing a kindergarten computational thinking assessment using evidence-centered design: the case of algorithmic thinking

  • Jody Clarke-Midura
  • , Deborah Silvis
  • , Jessica F. Shumway
  • , Victor R. Lee
  • , Joseph S. Kozlowski
  • Utah State University
  • Stanford University

Research output: Contribution to journalArticlepeer-review

58 Scopus citations

Abstract

Background and Context: There is a need for early childhood assessments of computational thinking (CT). However, there is not consensus on a guiding framework, definition, or set of proxies in which to measure CT. We are addressing this problem by using Evidence Centered Design (ECD) to develop an assessment of kindergarten-aged children’s CT. Objective: To present a design case on the development of the assessment, specifically the algorithmic thinking (AT) tasks and to share validity evidence that emerged. Method: We focus on the AT sub-component of CT and present the principled assessment design process using ECD. Findings: Our operationalization of CT includes spatial reasoning as a sub-component. Pilot results showed an acceptable internal consistency reliability for the AT items and critical design decisions that contributed to validity evidence. Implications: An important contribution of this work is the inclusion of spatial reasoning in our definition of early childhood CT.

Original languageEnglish
Pages (from-to)117-140
Number of pages24
JournalComputer Science Education
Volume31
Issue number2
DOIs
StatePublished - 2021

Keywords

  • Computational thinking
  • algorithmic thinking
  • assessment
  • early childhood
  • evidence-centered design

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