Coding Introduction

Problem solving in technology-rich environments involves using digital technology, communication tools and networks to acquire and evaluate information, communicate with others and perform practical tasks. It requires the ability to solve problems for personal, social and economic purposes through the setting of appropriate goals and plans and by the accessing and making use of information through computers and computer networks. piaacexpertgroupinproblemsolvingintechnologyrichenvironments_2009_piaac

Digital problems are therefore those problems that are solvable using information and communication technologies. These digital solutions can use a wide variety of developed and developing contexts such as web applications, mobile applications, interactive media and intelligent systems. digitaltechnologieshub_2017_topics

What distinguishes a digital problem is that the solution consists of digital hardware and software working together to form a digital system.

In a digital system:

• data goes in (input)

• data is manipulated (process)

• data is sent out (output)

People control the a digital system through the use of algorithms.

For example, the input process and output (IPO) for logging on would be:

Computational thinking¶

Computational thinking describes the processes and approaches we draw on when thinking about how a computer can help us to solve complex problems and create systems. We often draw on logical reasoning, algorithms, decomposition, abstraction, and patterns and generalisation when thinking computationally. digitaltechnologieshub_2017_topics

Decomposition¶

Decomposition is when you break a big problem into smaller, simpler parts. This makes the problem easier to understand and helps you solve it step by step without getting overwhelmed.

Most complex problems are just lots of smaller problems joined together. When you break them down, it’s easier to figure out what to do and plan your solution.

When using decomposition, ask yourself:

• What are the different parts of the problem?

• What tasks do I need to do to solve it?

• Can I do each task easily, or should I break it down more?

• If I finish all the smaller tasks, will that solve the whole problem?

Decomposition Example

Problem: Create a program that calculates a student’s average grade.

Decomposition steps:

1. Get input from the user

   • Ask the user how many subjects they have

   • Ask for the grade for each subject

2. Store the grades

   • Save the grades in a list or array

3. Calculate the average

   • Add all the grades together

   • Divide by the number of subjects

4. Show the result

   • Display the average grade to the user

   Decomposition Activities

   Activity 1

   Create a program that helps students manage their homework tasks. Students need to build a digital tool that allows users to enter, view, and organise their homework across subjects.

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   Activity 2

   Design a digital scoreboard for a school sports event. The system should display team names, update scores during matches, and show the final result at the end.

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   Activity 3 Develop a quiz app for science revision. The app should present questions, let users choose answers, and give feedback on how they did.

   Pattern Recognition¶

   Pattern recognition means spotting things that are the same or similar. In Digital Solutions, you look for patterns when you break down a big problem into smaller parts.

   By comparing the different parts, you can notice what repeats or what looks similar. This helps you understand the problem better and come up with a smarter solution. It’s not just about patterns in numbers or letters—it can be patterns in how problems work or how information is structured.

   

   When using pattern recognition, ask:

• What patterns do I see?

• Have I solved something like this before?

• Do any parts of the problem work in a similar way?

• Is anything repeating?

Abstraction¶

Abstraction is about focusing on the most important parts of a digital problem and ignoring the details that don’t help solve it. After breaking a problem into parts (decomposition) and spotting patterns (pattern recognition), abstraction helps you decide what features, data, and actions are needed for your digital solution.

In programming, procedural abstraction is when you group steps into a named procedure or function. Instead of worrying about how the steps work each time, you just call the procedure. This makes your code simpler, clearer, and easier to reuse.

It’s like designing an app: you include only the features that matter, and you organise repeated actions into clean, reusable blocks of code.

When using abstraction, ask:

• What is the main goal of my digital solution?

• What information and features are essential?

• What can I ignore because it’s not needed?

• Can I group actions into procedures to keep my code clean and simple?

Algorithmic Thinking¶

Algorithmic thinking is about planning the steps needed to solve a problem. It helps you create a clear set of instructions (an algorithm) that a person or computer can follow to get the right result.

Instead of just finding an answer, you work out how to solve the problem step by step. These steps take input, do something with it, and give the correct output. If you follow the steps the same way every time, you should always get the same result.

In Digital Solutions, algorithmic thinking is used to design instructions for programs and apps so they work reliably and predictably.

Then creating algorithms, ask:

• What’s the first thing I need to do?

• What steps do I need to follow?

• What order should the steps go in?

Systems thinking¶

A system is a set of interrelated elements that make a unified whole. Systems are everywhere — for example, the interdisciplinary team involve in supporting someone, the Human Resources in your organization, the circulatory system in your body, the predator/prey relationships in nature, the ignition system in your car, and so on. Ecological systems and human social systems are living systems; human-made systems such as cars and washing machines are nonliving (sic) systems. persondirectclinicalservice_2017_system

Systems thinking is about looking at the big picture when solving problems. It helps you understand how different parts of a system work together and affect one another.

In Digital Solutions, this means seeing how your solution fits into a larger system — like how an application, a database, and a user all interact. If one part changes, it might impact other parts. This helps you design better, more reliable systems.

When using systems thinking, ask:

• What parts make up the system?

• How do the parts connect and depend on each other?

• What happens if one part changes?

• How does this solution affect people, other systems, or the environment?