The Computational Thinker

An interesting thing about computational thinking (CT) is that is based on the assumption that learning is achieved through failures rather than immediate success. CT seeks to dissect a problem into smaller more manageable problems, using logic to sequentially give sub solutions to the posed problem. Potential errors need to be catered for (debugging) whilst simplifying wherever possible.
Failure might be a great teacher, but it is also a cryptic one. Figuring out its lessons is no easy task, especially when lacking expertise or persistence.

Throughout our lives we experience situations involving Critical Thinking, Problem Solving and Decision Making. This includes school experiences of learners where for example, they use critical thinking skills to plan and conduct research, manage projects, solve problems, and make informed decisions using appropriate digital tools and resources.

Various definitions are used throughout the globe to explain CT, which DePaul (2009) see as facilitating new ways of seeing existing problems, emphasizing creating knowledge rather than using information, presenting possibilities for creatively solving problems, and facilitating innovation. On the same wavelength, Wing (2016) stresses that CT ‘represents a universally applicable attitude and skill’. Similarly, as mentioned by BBC, CT allows for the understanding of a complex problem and the development of possible solutions. Such solutions being meaningful for ‘a computer, a human, or both’. The definition which has gained attention internationally and which locally fits well with the other dimensions of Digital Literacy as a Cross Curricular Theme is as follows;

‘Computational thinking is the thought processes involved in formulating problems and their solutions so that the solutions are represented in a form that can effectively be carried out by an information-processing agent.’

CT involves a number of core concepts based on computing  mainly abstraction and algorithms, decomposition, pattern matching, generalization, and inference.

  • decomposition – breaking down a complex problem or system into smaller, more manageable parts
  • pattern recognition – looking for similarities among and within problems
  • abstraction – focusing on the important information only, ignoring irrelevant detail
  • algorithms – developing a step-by-step solution to the problem, or the rules to follow to solve the problems.

Such core components give a better understanding of what CT really encompasses and thus better explain how and where it can relate to subjects thought in our schools. Barefoot coin CT as involving core concepts of which logic, abstraction, algorithm, automation, decomposition, debugging and generalisation. CT can be understood as directly linked to and as a component of digital learning and which in a learning situation may be enabled through approaches which Barefoot points towards tinkering, making, collaboration, communication and creative situations.

These core components need to be delineated throughout the obligatory educational system (K-10), identifying learning outcomes and giving examples of how such concepts may be learnt through practical hands-on learning activities.

Computational Thinking foresees competences whose importance is increasing in an ever changing society. Such thinking underlines that an individual develops and employs strategies for understanding and solving problems in ways that leverage the power of technological methods to plan, develop and evaluate efficient solutions.

A computational thinker might be defined as a logical problem solver where rather than seeking trial and error methods, the focus is on the development of a computational mind-set provides a structured methodology.

Being able to understand that a problem actually exists and thus being able to define a problem is an important competence. It is less about behaving like a computer and more about thinking laterally, thinking as illustrated in De Bono’s thinking hats.

Traditional teaching is somewhat linear, education is a linear system, segregating learning in boxes, aka subjects. We, teachers have been brought up in a sequential world.  Today’s learning is linear, based on discrete subjects; many times focused on work rather than life. Classic TV in the analogue days used to have pre defined timetabled programs. Nowadays kids are comfortable in accessing any TV program according to appetite, randomly accessing any channel or program. Imagine going back to use a structured viewing timetable with no chance of binging in a TV series over the weekend, not being able to manage to catch up with peers in the favourite TV show!

Today’s young learners are being subjected to such a structured linear education whereas day-to-day they are experiencing a fast paced world, where digital competence gives an edge over lack of it.

Adopting computational thinking as a backbone for our educational system is key, removing linearity for the student, removing the physical subject barriers and moving towards a project based approach that allows every student to reach his/her own potential. Allowing students to become computational thinkers, taking ownership of their own learning is key.

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