Preschool and Data Science: Supporting STEM Learning and Teaching with Hands-On Materials, Narratives, and a Digital Tool

Abstract

This paper describes a small, quasi-experimental, mixed method study investigating teacher and child outcomes for a preschool data science intervention condition compared to a business-as-usual comparison condition. The intervention included both hands-on activities and a free digital tool called the Preschool Data Toolbox to engage young children in foundational data science activities. The intervention activities aligned with a learning blueprint that articulated a set of early childhood data science learning goals based on K-12 computer science and early mathematics standards. The intervention supports teachers to implement foundational data science investigations using an intuitive tablet app that scaffolds the DS process through structured and open-ended instructional experiences. Findings from classroom observations, teacher surveys, and interviews indicate high feasibility and engagement, with teachers reporting ease of use, developmental appropriateness, and positive impacts on children’s data acumen and math skills (n = 217). After controlling pre-test scores, children who participated in the intervention demonstrated statistically higher post-test scores (p = 0.001) compared to those in the comparison group, highlighting the effectiveness of the program in fostering early STEM skills. The study underscores the potential of developmentally appropriate DS experiences to foster early learning, support teacher confidence, and prepare children for future academic success, while highlighting the need for further research and professional development to scale such interventions effectively.