Teaching Computational Thinking to Children in Head Start Classrooms

Results from a Randomized Controlled Trial

Christopher Joseph Doss, John F. Pane, Victoria L. Jones

ResearchPosted on rand.org Jun 8, 2026Published in: Early Childhood Research Quarterly, Volume 76, pages 445-467 (3rd Quarter 2026). DOI: 10.1016/j.ecresq.2026.04.010

Despite efforts to broaden participation in computer science and its related fields, there exist stark disparities in participation in computer related fields by gender, race/ethnicity, and socio-economic status. One approach to combat these disparities is to expose children to computing concepts early, to provide them with the foundational skills needed to be successful in later courses. This article reports on the results of a randomized controlled trial evaluation of a novel curriculum that teaches computational thinking (CT) skills to children ages three through five in Head Start classrooms. We find that the curriculum improved child performance on a validated CT assessment by a significant 0.66 standard deviations (SDs), equivalent to moving the median control group student to the 75th percentile had they been exposed to the curriculum. Effects of similar magnitude were seen for most domains of the CT assessment and subgroups of children. In a subset of children for whom we were able to obtain Head Start formative assessments, we saw the curriculum improved teacher ratings of math development by a significant 0.36 SDs but it had no effect on literacy or social-emotional development. Though we were underpowered to detect effects on teacher outcomes, survey results indicate that the curriculum may improve teacher confidence and knowledge in teacher CT skills, especially for novice and assistant teachers. These results indicate that prekindergarten can be an opportune time to start addressing disparities by teaching foundational computing skills and that a supplemental, short-term curriculum can produce measurable gains in children’s CT knowledge.

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Document Details

  • Publisher: Elsevier Inc
  • Availability: Non-RAND
  • Year: 2026
  • Pages: 23
  • DOI: https://doi.org/10.7249/pubs
  • Document Number: EP-71335

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