Visual modelling and emergent aspects of computational thinking: Example from a cross-disciplinary course

Abstract

In 2006, Jeanette Wing announced—in a very short, three-page paper—a new discipline she labelled ‘Computational Thinking.’ This new field, CT, she said, is not the same as just programming, because it also includes the energies, constructs and ambitions behind programming—such as problem-solving, heuristic and algorithmic thinking, data manipulation, abstraction, reduction, transformation, generalization, data manipulation, and pattern finding. Wing asserts that CT is an important methodology for learning in general, and that CT’s benefits extend into ‘all parts of life.’ If this claim is true, then CT should be crucial not only for students of STEM subjects—who already use computational methods—but also for those studying disciplines traditionally associated with the humanities, qualitative social sciences and arts and letters. But where are the voices from these other fields? Where are the studies of observed learning when computational methods are applied within these other non-STEM subjects? And where do we find instances of new kinds of thinking emerging from this mix? I want to address these questions in a personal and idiographic way. I describe the history, activities and outcomes of a university-level course I invented, called Visual Modelling. The course required students to intermingle computational methods with drawing and design tools. Using words and images I explain some of the ideas and procedures that emerged over the fifteen years of co-teaching this cross-disciplinary course. Everyone participated in the ongoing back-and-forth translation between the different notational languages, everyone benefited, and this level