Computational thinking: An essential skill for young STEM learners
STEM learning has emerged into one of the most popular and avantgarde technique in the modern education system. It is an experiential method that involves application of integrated knowledge, information, skills and creativity for better problem solving. STEM learning has many significant aspects and one such essential aspect is computational thinking.
What is computational thinking?
Computational thinking is a versatile skill that helps in understanding and leveraging technology (computers) for all purposes. The key to computational thinking is not only to figure out how computers work but to predict what they are capable of doing for us in the near future.
By definition, computational thinking is taking help of algorithms (step-by-step instructions to implement a series of applications) to strategically think or plan a computer function and then make the computer execute the plan effectively. It involves communicating with technology and then thinking and acting like a computer expert. Effective computational thinking is done in parts and helps in identifying known and unknown patterns.
Few common yet popular examples of computational thinking are: creating and reading online maps, developing strategies for a video came and so on.
What can be done with computational thinking?
Computational thinking has subsets, which, if combined together, gives useful results and becomes a useful resource for coding, programming and other computer workings. Here is what one can do with computational thinking.
Pattern recognition: This includes analyzing the similarities and differences in computer languages, and providing a constructive and creative solution to them. Coders and programmers often use the pattern recognition feature to solve every day tech problems especially in the domains of data science, machine learning, artificial intelligence, so on and so forth. Profound and structured pattern recognition is often helpful for young coders and programmers whether they are upping their game while developing new apps or making strategies during online gaming.
Decomposition: As the term suggests, decomposition is learning how to take things apart in order to join them back into a structured form. Tech-savvy youngsters who are passionate about building machines and tech models often find decomposition offering them a hands-on experience. It helps young minds take time and understand the components to fuse them together into one single device. Later on, this might come in handy if your youngster is interested to work in the field of robotics. Decomposition is also beneficial outside STEM learning in day-to-day activities like DIY crafts, learning a new language, and keeping track of chronology in history or literature.
Abstraction: Abstraction in computational thinking means emphasizing only on what’s important and ignoring the rest for the time being. This comes in handy in case of young coders who are easily distracted. Abstraction lets them focus on one relevant information at a time, be it during coding or during editing an assignment. Abstraction is actually a key component of computational thinking as it leads the person to the best possible outcome and helps in effective communication. Learning this helps youngsters not only in the field of coding and programming but also in future real-life situations like convincing an investor to fund their start-ups.
Algorithm design: This aspect of computational thinking helps in locating the most convenient and quickest method to reach the desired outcome. It is through algorithm design that information and data are stored where they should be and tracked as and when necessary. This is what makes it possible for us to find what we are looking for in Google’s search engine. Algorithm design is especially beneficial during coding as it helps proceed in a straightforward manner without any deflection.