Investigating the psychometric features of a locally designed computational thinking assessment for elementary students

Lijun Shen, Zitsi Mirakhur, Sarah LaCour

Research output: Contribution to journalArticlepeer-review

Abstract

Background and Context: Educators and researchers are interested in building the computational thinking (CT) skills of K-12 students. However, the availability of language-agnostic assessments for lower elementary graders remains limited. Objective: We present preliminary insights into the reliability and validity of the Computational Thinking Assessment for Elementary Students (CTAES), a new assessment to measure 3rd-5th grade students’ CT abilities. Method: The CTAES was administered to 222 3rd-5th grade students. We conducted Rasch analyses, focusing on dimensionality, separation characteristics, and differential item functioning. Findings: The CTAES appears to be unidimensional, primarily assessing students’ CT skills. Students with lower CT proficiency demonstrate lower likelihood of correctly responding to assessment items compared to peers with higher CT proficiency levels. Preliminary evidence suggests that the assessment does not exhibit bias based on gender or racial/ethnic background. Implications: Initial findings suggest that the CTAES holds promise as a reliable and valid assessment tool, although there remain opportunities for further refinement.

Original languageEnglish (US)
JournalComputer Science Education
DOIs
StateAccepted/In press - 2024

Keywords

  • assessment
  • Computational thinking
  • elementary education
  • Rasch

ASJC Scopus subject areas

  • General Computer Science
  • Education

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