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The importance of computational thinking (CT) as a goal of science education is increasingly acknowledged. The representational affordances of computational tools are changing the way knowledge can be constructed, expressed, and understood across disciplines. Our group has worked to explicitly characterize CT practices used by computational STEM researchers (CT-STEM practices) and to develop computational science curricula that teach both CT-STEM practices and science content. We have previously characterized four strands of CT-STEM practices: data practices, modeling and simulation practices, computational problemsolving practices, and systems thinking practices. In this chapter, we show that a group of 9th grade students developed competencies for modeling and simulation practices as a result of their engagement in our computational biology curriculum. As evidence, we present findings from a quantitative analysis of students' written responses to assessments given before and after their participation in three computational biology units. Results suggest that the computational biology curriculum helped students develop a number of important competencies for the strand on modeling and simulation practices. Our work contributes to the field's understanding of how science curricula can be designed to foster students' development of CT-STEM practices and how this development can be assessed.

This paper reports on the first iteration of the Computational Thinking Summer Institute, a monthlong programme in which high school teachers codesigned computationally enhanced mathematics

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