Blog by Marcus Specht (4TU.CEE leader TU Delft), Xiaoling Zhang, researcher at TU Delft and Vivian van der Werf (LIACS, Leiden University)
Algorithms and programming are ubiquitous in our world today, from setting an alarm or customising your smartphone to solving complex problems in bioengineering or developing Artificial Intelligence. At the core of these algorithms is a human skill to describe solutions for problems in a systematic and machine-readable way. This comes also really close to the first definition of Computational Thinking (CT) when introduced in 2006 by Jeanette Wing (2006). She defined CT as a thought process consisting of problem and solution formulation with solutions represented in the form that can be implemented by any information-processing agent.
The importance of CT skills
Some people hold the view that CT is a 21st century skill which is becoming ever-more important while others believe it is nothing new but the way of thinking adapted to today's technology. Nevertheless there is consensus that CT skills are of importance in our digitalising world and thus should be incorporated in our education system. Subskills often named in different definitions are: abstraction, algorithmic thinking, automation, pattern recognition, problem decomposition, or generalization.
The teaching and training of CT skills is just ramping up in the education system from broad implementations of programming education in primary education, programming and maker spaces in secondary schools, to scientific programming, data analysis courses, software-based engineering and design, or programming of quantum computers. The impact of CT can nowadays already be seen in a wide variety of application fields ranging from digital humanities to computational biology. The skills become more and more essential in hybrid problem solving involving humans and computers and in building scalable and high-quality solutions.
CT as a problem-solving tool
Computational Thinking can be regarded as a set of skills for solving problems. What distinguishes CT from other problem-solving tools as described by Denning (2019), is that CT is a tool with which problems can be solved more efficiently while at the same time it is less error prone. This is especially the case with large scale problems that have a high complexity of reasoning and require high demand in calculation that it would be impossible for a single human being to accomplish in a lifetime.
Computational sciences which adapt computing techniques and paradigms are the cases where CT is most visible in today’s educational scenarios. In these cases, domain-specific knowledge as well as CT as a tool are integrated in the problem-solving process, human problem solvers combine computational tools and reasoning in the process.
The role of CT in education
Building a common ground and recognizing the potential impact of CT skills is a first step for embedding CT in our curriculum (Specht et al. 2019). Understanding what CT means and how it can be integrated in lectures, courses and our underlying idea of teaching and problem solving in a subject (Specht, 2020) can already be seen with examples from arts, engineering, humanities, or social sciences.
So let's explore together what the future of digital design, digital humanities, digital engineering or digital art will be by embracing computers as the powerful tools they can be in the digital transition.
References
Selby, C., & Woollard, J. (2013). Computational thinking: the developing definition.
Specht, M., Coenders, M., & Stoyanov, S. (2019). Implementing Computational Thinking in the Dutch Curriculum an Exploratory Group Concept Mapping Study. CoolThink@ JC, 210.
Specht, M. (2020). Computational Thinking, why is it important and when to learn what? Keynote given at the International Conference on Computational Thinking Education. Hong Kong.
Wing, J. Research Notebook: Computational Thinking—What and Why? Link Mag. 2011, 8, 20–23.
What is computational thinking? - Introduction to computational thinking - KS3 Computer Science Revision. (n.d.). BBC Bitesize. Retrieved December 5, 2021, from https://www.bbc.co.uk/bitesize/guides/zp92mp3/revision/1
Denning, P. J., & Tedre, M. (2019). Computational Thinking (The MIT Press Essential Knowledge series) (Illustrated ed.). The MIT Press.