Computational Thinking—More Than a Variant of Scientific Inquiry!

Abstract

The essence of Computational Thinking (CT) lies in the creation of "logical artifacts" that externalize and reify human ideas in a form that can be interpreted and "run" on computers. Various approaches to scientific inquiry (learning) also make use of models that are construed as logical artifacts, but here the main focus is on the correspondence of such models with natural phenomena that exist prior to these models. To pinpoint the different perspectives on CT, we have analyzed the terminology of articles from different backgrounds and periods. This survey is followed by a discussion of aspects that are specifically relevant to a computer science perspective. Abstraction in terms of data and process structures is a core feature in this context. As compared to a "free choice" of computational abstractions based on expressive and powerful formal languages, models used in scientific inquiry learning typically have limited "representational flexibility" within the boundaries of a predetermined computational approach. For the progress of CT and CT education, it is important to underline the nature of logical artifacts as the primary concern. As an example from our own work, we elaborate on "reactive rule-based programming" as an entry point that enables learners to start with situational specifications of action that can be further expanded into more standard block-based iterative programs and thus allows for a transition between different computational approaches. As an outlook beyond current practice, we finally envisage the potential of meta-level programming and program analysis techniques as a computational counterpart of metacognitive strategies.

Abstraction in Computer Science Education: An Overview

“…A key aspect differentiates CT from other disciplines using abstraction: the "essence of Computational Thinking lies in the creation of 'logical artifacts' that externalize and reify human ideas in a form that can be interpreted and 'run' on computers" (Hoppe and Werneburg, 2019). Said otherwise, the abstractions devised to model real-world problems materialise and become real in programs, in that they will live on whenever the program is running -typically with concrete effects on the real lives of their users -without the mediation of minds, which instead is usually required for abstract ideas to exist.…”