A Typology of Models for Integrating Computational Thinking in Science (CT+S)

In order to expand opportunities to learn computer science (CS), there is a growing push for inclusion of CS concepts and practices, such as computational thinking (CT), in required subjects like science. Integrated, transdisciplinary (CS/CT+X) approaches have shown promise for broadening access to CS and CT learning opportunities, addressing potential self-selection bias associated with elective CS coursework and afterschool programs, and promoting a more expansive and authentic contextualization of CS work. Emerging research also points to pedagogical strategies that can transcend simply broadening access, by also working to confront barriers to equitable and inclusive engagement in CS. Yet, approaches to integration vary widely, and there is little consensus on whether and how different models for CS and CT integration contribute to desired outcomes. There has also been little theory development that can ground systematic examination of the affordances and tradeoffs of different models. Toward that end, we propose a typology through which to examine CT integration in science (CT +S). The purpose of delineating a typology of CT+S integration is to encourage instantiation, implementation, and inspection of different models for integration, and to promote shared understanding among learning designers, researchers, and practitioners working at the intersection of CT and science. For each model in the typology, we characterize how CT+S integration is accomplished, the ways in which CT learning supports science learning, and the affordances and tensions for equity and inclusion that may arise upon implementation in science classrooms.