Positioning Youth for Success in Science: Studying the Malleability and Impact of Computational Thinking for Science

Researchers and curriculum designers at the Lawrence have been engaged in a three-year project (NSF STEM+C #1838992) that investigates computational thinking as both an input into and an outcome of science learning. After synthesizing a variety of frameworks and definitions of computational thinking (CT) to define the aspects of CT that best position youth specifically for learning science, we are testing whether this new construct, called computational thinking for science (CT-S), prepares youth from diverse backgrounds for achieving success with their science learning in technology-rich classrooms. We are specifically investigating whether CT-S is valuable above and beyond two of the previously identified dimensions of Science Learning Activation: fascination and scientific sensemaking, each of which has been shown to enable success in science learning during the middle school years. We are also investigating the relationship between CT-S and the development of STEM career preferences. The study is situated within classrooms that use the Amplify Science Middle School curriculum, also developed by the Learning Design Group. The project includes measurement development, validity testing, and a one-semester-long study to explore variation in CT-S and the extent to which CT-S is predictive of science learning and engagement. To read more about our development process and the items on the measure, please download our technical report.

Technical Report: Measuring Computational Thinking For Science (CT-S) PDF

Computational Thinking for Science Framework PDF