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1 INTRODUCTION A major responsibility of educational systems in the 21“ century is to prepare future generations for the challenges involved with the increasing computerization of our everyday lives and to meet the demands of one of the fastest-growing job markets: computing (Grover & Pea, 2013; US-BLS, 2020). In line with this, in 2011, the Future Work Skills report of the Institute for the Future included computational thinking (CT) among the 10 top skills that will be needed for success in 2020 (Davies, Fidler, & Gorbis, 2011). Shute, Sun, and Asbell-Clarke (2017) draw an interesting analogy between reading-writing and CT. In the mediaeval period, only select groups of people could read and write, but as the world evolved increasingly more people needed these skills. Similarly, in the digital world of the 21“ century, everyone should acquire CT, not only programmers. CT has become a very hot topic in educational research and practice after Jeanette Wing published an influential article in this topic in 2006. According to Wing, CT is merely thinking like a computer scientist when approaching a problem and in solving it. As CT grew in popularity, computing education also received more and more attention. In the UK and the US, these trends are evident from initiatives such as Computing at School and Computer Science for ALL. The most cited definition of CT emphasizes that CT is a thinking process where “solutions are represented in a form that can be effectively carried out by an information-processing agent” (Wing 2010). To better understand the nature of this concept, researchers have tried to identify its roots within the framework of modern educational culture. The term of CT stems back to the constructionist work of Seymour Papert (1980, 1996). According to Spangsberg and Brynskov (2018), Papert’s work is a good starting point for talking about computing education from the perspective of CT. Papert formulated three main principles: (1) the power principle emphasizes that the natural mode of acquiring knowledge is through use, which will progressively lead to the deepening of one’s understanding; (2) the thingness principle is concerned with making abstract ideas concrete through a meaningful representation; (3) the dynamics before statics principle is closely related to the medium used for teaching. With regard to the expression of “can be effectively carried out by an information-processing agent”, Benedict du Boulay is recognized to be the first who introduced the concept of the notional machine. He used this term in the context of teaching novices how to program: “The notional machine is an idealized, conceptual computer whose properties are implied by the constructs in the programming language employed” (du Boulay, O’Shea, & Monk, 1981). Wing’s definition of CT has recently been a target for critiques. For example, Denning (2017) distinguishes between Traditional CT (pre-2006) and New CT
