Developing curricula and supporting teaching of computer science and computational thinking for multilingual learners in grades K-8

University Of California-Santa Cruz, Santa Cruz CA

Investigators

Abstract

This project will prepare both teachers-in-training and veteran teachers to develop curriculum and instructional methods that will help low income, multilingual learners in grades K-8 grow their skills in computer science and computational thinking, The researchers will collaborate extensively with practitioner-experts in the schools to create a teacher learning pathway that builds their confidence and experience with this curricula. The project also leverages the strengths of the students’ community by engaging families in project-based learning experiences. The overall aim is to develop teachers' ability to integrate Computer Science and Computational Thinking into their science classes and to increase student learning and identity formation, particularly for those who are underrepresented in the STEM fields. By addressing the specific needs of multi-lingual learners in economically disadvantaged schools, this project will expand students’ opportunities to develop skills and knowledge that will be crucial to their success in the future job market. The results will be shared with schools nationwide as a model of equitable and inclusive computer science education for multilingual learners. This project will examine how to develop and sustainably implement innovations that can support K-8 teachers’ ability to engage their students in computer science and computational thinking in a manner that is relevant to the learners’ lives and communities. The project will employ a design-based research approach collaboratively designing innovations with teachers, students and their families, testing these in classrooms and the community, and refining them over the span of the project with the aim of scaling up their impact and increasing the overall capacity of the district to support computer science education for all students. Data analysis will utilize a quasi-experimental design to measure multilingual learners’ achievement and teacher learning. The data will include observations of the curricular innovations and teacher professional development, participant surveys, and student achievement data. Results from this work will contribute to our understanding of (1) how coherently integrating computer science/computational thinking into K-8 science curriculum can increase student learning in core content areas and computer science/computational thinking, particularly for multilingual learners, (2) how a teacher professional development model that spans different stages of teacher learning – from preservice to in-service – can build computer science/computational thinking experience and confidence for teachers over time, and (3) how at-home, family-engaged project-based learning experiences can increase computer science/computational thinking identity formation for all students, particularly multilingual and low-income learners. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.