Computational Thinking - Algorithmic Thinking
An algorithm is a process or formula for calculating answers, sorting data, and automating tasks; and algorithmic thinking is the process for developing an algorithm.
With algorithmic thinking, students endeavour to construct a step-by-step process for solving a problem and like problems so that the work is replicable by humans or computers.
Algorithmic thinking is a derivative of computer science and the process to develop code and program applications. This approach automates the problem-solving process by creating a series of systematic, logical steps that intake a defined set of inputs and produce a defined set of outputs based on these.
In other words, algorithmic thinking is not solving for a specific answer; instead, it solves how to build a sequential, complete, and replicable process that has an end point – an algorithm. Designing an algorithm helps students to both communicate and interpret clear instructions for a predictable, reliable output. This is the crux of computational thinking.
Examples of Algorithms in Everyday Life
Like computational thinking and its other elements we’ve discussed, algorithms are something we experience regularly in our lives.
If you’re an amateur chef or a frozen meal aficionado, you follow recipes and directions for preparing food, and that’s an algorithm.
Outlining a process for checking out books in a school library or instructions for cleaning up at the end of the day is developing an algorithm and letting your inner computer scientist shine.
Here is an amazing video that tells you more about Algorithms and its applications.
Source: coursera
🎨 An activity applying Algorithms:
Think of a problem for which you could use computational thinking, describe it, and then describe how you would apply Algorithms.
(Add a text box here)
If you feel like you may still not entirely understand the concept, keep moving forward. You will learn more about Algorithms and Algorithmic thinking in the upcoming lessons.
Check-point Assessment
Q. Select the correct pair
Decomposition : break data and problem into small modules
Algorithms : observe patterns and trends in data
Abstraction : sequential and step wise approach to a problem
Pattern recognition : remove details and extract relevant data
Option A. 1
Option B. 2
Option C. 3
Option D. 4
Check the Solution!
Ans : A. Decomposition : break data and problem into small modules
Connect the dots through case study
Here is a video that will show 2 case studies discussed previously to connect all the pillars of Computational thinking.
Source: coursera
Useful resources for you
1.The Art of Coding Logic: Computational Thinking To Algorithmic thinking.
2.Using Computational thinking
3.Computational Thinking: What Is It? How Is It Used?
Alright then,
