This project seeks to promote computational thinking and a sense of belonging in computer science through a culturally relevant robotics program (CRR Program) developed through a research-practice-partnership with university teacher educators and researchers, administrators, teachers, coaches, and Black and Latinx children and their families.

About the Project

What is a research-practice-partnership?

A research-practice partnership (RPP) situates research and development in real educational contexts, focuses on design and testing of interventions, involves multiple iterations, fosters collaborative partnerships among researchers and practitioners, and impacts practice.

What are the project goals?

(1) co-develop and refine a classroom- and home-based culturally relevant robotics program (CRR program) for Black and Latinx preschoolers. 

(2) assess the impact of the CRR program on children’s computational thinking and sense of belonging in computer science.

The Big So What?

Opportunities for jobs in computer science and information technology are projected to grow much faster than other occupations. These jobs will be across many industries (technology, health care, agriculture, defense, government, energy, etc.) and will be highly paid in addition to having a high impact on society. Therefore, there is a need to increase workforce diversity in order ensure that a wide range of voices are present and to help in reducing racial and gender income inequality.

However, there currently is a significant lack of diversity in the computer science field. Only about 15% of computer science majors are women (lower than many other engineering fields). Urban schools are much less likely to offer computer science in high school as compared to suburban schools.  Only 9 states in the U.S. had more than 10 Black women pass the computer science AP exam. Sense of belonging in the field starts at an early age, thus it is important to begin introducing computational thinking and computer science in early childhood.

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This work is being supported with funding from the National Science Foundation CSforAll (Award #2031394). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of NSF.