Computational thinking can be a part of any classroom right from primary classes.
By Sheetal Javeri
“A complex problem is one that, at first glance, appears difficult to solve, but when broken down, it forms a series of small, manageable questions.”
I firmly believe fostering computational thinking during remote learning is the need of the hour. In the middle of any difficulty, lies a greater opportunity, for instance in the current pandemic where the face-to-face conversation is limited, various tools and techniques have been developed to make communication easier. Computational thinking allows students to understand complex problems. A complex problem is one that, at first glance, appears difficult to solve, but when broken down, it forms a series of small, manageable questions.
It is a thought process, which is why computational thinking should be a part of any classroom.
Learners must acquire mathematical understanding by constructing their own meaning through ever-increasing levels of abstraction, starting with exploring their own personal experiences, understanding, and knowledge. (Mathematics Scope Sequence, 2009)
What is computational thinking?
It is a form of reasoning and problem-solving technique in which the learner attempts a problem in such a way that its solution can be represented as algorithms. It is how computers or humans take the information in steps to understand the problem and then present the solution. Students can effectively perform these tasks only when they understand the four techniques behind the application.
(1)Decomposition, (2)Pattern recognition, (3)Abstraction, and (4)Algorithms.
It may initially seem challenging to imagine primary students designing algorithms, but from an early age, we can find opportunities to engage them, to varying degrees, in building their understanding of the steps in the computational thinking process. Young children enjoy playing with numbers. We can utilize their natural inclination to explore and solve problems.
As part of the Transdisciplinary Theme, ‘Where We Are In Place & Time’ students were inquiring into explorations and how it leads to new opportunities and understandings. Students hence worked with a “If you decide to go on a road trip to your favourite destination, what possible questions will you consider?”
- What are the possible routes available? To take the fastest or shorter path, you may need to consider whether to take the city or highway route or forest road.
- Consider how safe this route is? Narrow lanes or straight road, dark
- Does this route cater to travel needs (gas station, refreshments, etc.)
Finally, an algorithm is created; a series of information is put together in a sequence to determine the most suitable route to reach your destination.
One student said, ‘I would prefer the expressway as it is fast and my favourite ice-cream shop falls at the end of the expressway’
Another short-listed the highway as she wanted to reach faster with few essentials available on the road: Gas station, McDonald Café, etc.
A third student said, ‘I would prefer the city route as I want to save the toll money. I also want to go through the city because emergency services like the hospital and clinics are available. Also, the city route has an amusement park on the way which I can enjoy with my family.’
Students are engaged in playful thinking through computation thinking and can look at one situation with many possibilities, enabling purpose and engagement. They also applied their understanding of the concept of angle while choosing their route. In the way navigators used bearings to find angles and directions students used curvy roads and straight roads to understand angles in their route. Straight roads and 90 degree roads will be faster to reach while steep curvy roads will have angles less than 90 degrees, which will break their speed. One student chose the right angle 90 degrees road to maintain her speed and avoid too many steep curves as she understood that curvy roads would cause a delay in reaching her destination.
“Each technique is as essential as the others. They are like the legs of a table – if even one leg is missing, the table will collapse. “
In another learning experience, we applied computational thinking to the concept of numbers (ascending/descending).
It is easier for students to arrange when the numbers are simple, e.g., 6000, 4000, 5000, 3000; however, the problem becomes complex with similar numbers or mirror image numbers like 69966, 69699, 96669, 96969, 69696.
Students used the four concepts of computational thinking to arrange the numbers.
(1) Decomposition – breaking a complex problem into smaller parts.
Breaking the numbers: The first two digits are separated from the last three digits of each number, i.e., 69, 69, 96, 96, 69.
(2)Pattern recognition – looking for similarities among and within problems.
After separating the first two digits from the last three digits from each number, these digits were compared, and identical digits are underlined with the same colour. (identical digits that are smaller – 69, 69, 69 were underlined with a green pencil) and (higher identical digits- 96, 96 were coloured with orange pencil).
Subsequent three digits inside the circle were furthermore broken down into smaller parts to compare them in the same way as shown in the figure above.
(3)Abstraction – focusing on the important information only, ignoring irrelevant details.
Through abstraction students focus specifically on lower digits underlined in green and were now able to arrange in increasing order easily.
(4)Algorithms – developing a step-by-step solution to the problem by following the rules to solve the problem.
Finally, the remaining numbers (96,669, 96,969) were arranged in the same manner after the numbers (69,696 69,699 69,966) in ascending order.
Using the structure of computational thinking, students could construct and transfer meaning and apply it with a better understanding. Each technique is as essential as the others. They are like the legs of a table – if even one leg is missing, the table will collapse.
Students were further encouraged to use computational thinking in their daily lives.
Children shared examples of applying computational thinking to plan a playdate, and whom to call? Friends who like playing similar board games, keeping games ready as per their choice and sitting arrangements. Similarly, a child used computational thinking skills in baking a cake where she thought of the proportion of ingredients to be considered before mixing them and then baking.
Teaching is learning twice, the process was a great learning experience, as I learnt to overcome challenges while teaching and guiding students in dealing with a problem. I fundamentally believe the most complex problems can have the simplest solutions. When children reflect on their own experiences it gives structure to their skills and these can be transferred to more complex tasks.
Sheetal Javeri PYP Math teacher at Fazlani L’Académie Globale International School in Mumbai. Currently pursuing a 2nd-year master’s degree program. Having done the accredited ‘Mathematical Thinking’ course from Stanford University would like to work on building a variety of mathematical skills that facilitate the complexities of a problem with applications.