Thinking outside the box

The term thinking outside the box originated from an experiment done in 1930 called the Nine Dot Problem. This experiment was performed by Norman Maier, an American psychologist. What the Nine Dot Problem entails, is that three rows of three dots underneath one another needs be connected, using only four lines. Solving the problem requires drawing and connecting the lines outside of the square box created by the dots. At first, it seems impossible to connect the dots using four lines. There is no rule stating that one should draw the lines within the borders of the box, yet most people try to do that.

Student’s ability to solve problems in the 21st-century is becoming more crucial as we start facing issues that can no longer be solved by basic trial and error. Problem-solving is one of the most valuable skills to have. A modern iteration of problem-solving skills can be seen with the concept of Computational Thinking skills (Wang, 2015). Computational Thinking is a process whereby we take a complex problem, explore the problem and develop workable solutions. We can then present these solutions in a way that a computer or a human, can effectively carry out (Langner, 2016).

Computational Thinking Process

In an article published by the BBC (2018), it states that a problem and the ways in which it could be resolved must be understood first, before considering possible outcomes. It might sound simple, yet most people facing a problem will just start solving the problem with trial and error. Although this helps us to explore the problem space (a long process of mental journey to discovery of the solution) the problem can be analysed and solved effectively with four Computational Thinking processes: Decomposition, pattern recognition, abstraction and algorithms. (Robertson, 2017).

Computational thinking involves taking a complex problem and breaking it down into a series of small, more manageable problems; we call this process Decomposition. The smaller problems can then be looked at individually, considering how similar problems have been solved previously, and is known as Pattern Recognition. By only focusing on the vital details and ignoring irrelevant information that does not contribute to the goal at hand, we can Abstract the key components. Lastly, simple steps or rules to solve each of the smaller problems can be designed; these are called Algorithms. If any of these steps are omitted, students will get frustrated and focus more on the problem than the possibilities of outcomes.

An essential skill for students

Numerous studies have even argued that it is now essential for students to develop skills in Computational Thinking even before being introduced to introductory programming courses, mathematics, computer sciences and robotics, Rich & Hodges (2017). Schools who started stimulating real-life problems (without making the problem threatening) found that when students get a problem or a real-life problem directly affecting them, they not only find a solution but also become more innovative to start solving similar problems and consider technology as an important source of problem solving, Rich & Hodges (2017).

Problem-solving is one of the basic activities of human life. It is critical to be proficient problem-solvers as challenges we face evolve and change with the 21st-century challenging us in ever more complex ways. By providing our students with opportunities that stimulate Computational Thinking, we prepare our students to adapt to an ever-changing world. We are preparing our students to solve the problems of tomorrow.

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