Instrumentation for Gauging Computational Thinking in Elementary Grades

Computational thinking is a recent and very popular addition to elementary school curricula. Computational thinking projects students undertake include five basic parts: identifying key features of a problem (decomposing), creating a model of relationships among factors (modeling) in a causal system or data, designing steps (algorithm) to solve the problem or analyze data, trying out and repairing missteps (debugging), and generalizing findings. Research on promoting young students’ (grades 1-6) computational thinking skills is sparse, as is work fusing computational thinking with self-regulated learning. Teachers and students need to know more about how to leverage this new focus in the school curriculum. This project will review research on these topics, develop tools teachers and students can use to observe how teaching and learning unfold in computational thinking projects, and investigate how those classroom practices relate to students growth in computational thinking.

Pin-Chuan Lin
Faculty Supervisor: 
Philip Winne
British Columbia
Partner University: