Examining the Current Definitions of Computational Thinking

Introduction

Information and communication technologies (ICT) have become an indispensable part of our daily lives, and they constantly change how we interact both in and out of the cyberspace. Adapting to such changes may not always happen automatically, especially at a national level. Nonetheless, in order to become and remain as active contributors to the global community, individuals and nations alike should improve their adaptive skills for the digital era. Otherwise, the social, economic, and developmental gaps are bound to widen. Hence, adapting to technological innovations is an important aspect of the contemporary society, and going beyond adaption by producing such technologies is a key to success in this environment (OECD, 2005). The changes in technology also reshape the workplace. Some professionals even claim that once today’s digital children grow up, there will be brand new professions we do not know yet. To better prepare for this fast approaching future, individuals need to develop diverse sets of skills that enable them to function in the society. Among many 21st century skills found in the literature, computational thinking -an advance structure of problem solving- has gained precedence in the recent years.

Despite the growing interest in computational thinking skills, there is not a simple definition of the concept. Rather, the researchers often try to explain computational thinking by elaborating on what it encompasses. For instance, International Society for Technology in Education (ISTE) and Computer Science Teachers Association (CSTA) provided a functional definition of computational thinking that covers (International Society for Technology in Education [ISTE] & The Computer Science Teachers Association [CSTA], 2011);

According to Wing (2006), computational thinking includes understanding human behavior, designing systems and solving problems. Hu (2011) also expresses computational thinking as a kind of problem solving while emphasizing computational tools, automation, data transformation, concretization or abstraction, and modelling. Riley and Hunt (2014) state that computational thinking resembles the way computer scientists think as they approach problems. Moreover, Selby and Woollard (2013) maintain that while there is a general consensus that problem solving is at the core of computational thinking, problem solving, by itself, is not sufficient to define the depth of the concept. Rather, computational thinking is an intense problem solving process that also covers abstraction, pattern recognition, algorithmic thinking, decomposition and reflective thinking. Michaelson (2015) maintains that before utilizing computers in any given problem solving scenario, one should define the problem in detail and think about solution paths in a broader sense. Computational thinking influences how an individual perceives problems. It is emphasized that problem solving is important for the relationship between ICT and computational thinking and that there is a need for the information essential for the problem-solving process. As a note of caution, programming itself would be an oversimplification of computational thinking. Although programming requires one to think computationally, computational thinking applies to many other areas beyond programming (Wing, 2006). Computational thinking does not even necessitate the use of computers of any sort. Individuals can make use of computational thinking when dealing with real life problems as well. Of course, computers can be utilized in the problems solving process to aid calculations, data visualization, modelling, automation, and other tasks; however, the human way of harmonizing all available resources to create a solution is the essence of computational thinking.