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COMPUTATIONAL
THINKING

Two girls on the computer

What is it?

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.

Australian Curriculum definition

Computational thinking

A problem-solving method that involves various techniques and strategies that can be implemented by digital systems. Techniques and strategies may include organising data logically, breaking down problems into parts, defining abstract concepts and designing and using algorithms, patterns and models.

Source:Australian Curriculum: Technologies glossary

RESOURCES

Learn more about it

CSER digital technologies MOOCs

CSER digital technologies MOOCs

The CSER digital technologies MOOCs are free online courses, designed to support Australian teachers to implement the Australian Curriculum: Digital Technologies.

Computational thinking for K–6 online module

Computational thinking for K–6 online module

This online self-paced module provides an introduction to computer coding and computational thinking.

LESSON IDEAS

How to teach it

Primary

Computational thinking

Computational thinking

This lesson gives students the opportunity to practise the four arts of computational thinking (decomposition, pattern matching, abstraction, and algorithms) in one cohesive activity.

Secondary

Spreadsheets come alive

Spreadsheets come alive

Using the ‘Odds and evens’ problem as a springboard, students construct interactive spreadsheets designed to address particular needs. This lesson also demonstrates an approach to programming known as rapid application development (RAD).

Introducing algorithms

Introducing algorithms

Students design a sequence of steps for others to follow. They convey their instructions to peers and evaluate the work of others to determine if the outcome was successful.
Fibonacci served three ways

Fibonacci served three ways

Students learn to code separate modules that perform discrete functions but collectively meet the needs of the solution. They select the most appropriate algorithm based on the type of problem.
Eco calculator

Eco calculator

Students make a paper prototype of an eco calculator to demonstrate human impact on the environment and suggest changes in behaviour. This is an unplugged learning sequence with opportunities to extend learning through the development of a Scratch quiz.
There can only be one

There can only be one

Students write a simple suite of programs that can be used to facilitate an SRC election though the collection and processing of data. It assumes that students have been introduced to Python programming language.
Making maths quizzes 1

Making maths quizzes 1: Plan and test our programs

In this sequence students plan, create and edit a program that will ask maths questions that are harder or easier depending on user performance.
Breaking up can be good

Breaking up can be good

This sequence provides a gentle introduction to the skill of decomposition by having students develop discrete modules that together serve a single need: a maths teacher asks for a program that can be used to demonstrate aspects of maths. This sequence can be used in conjunction with 'Comparing and selecting appropriate algorithms'.
CS Unplugged

CS Unplugged

CS Unplugged is a collection of activities that introduce students to computational thinking through concepts such as binary, algorithms and data compression.
Behaving with real class

Behaving with real class

One challenge in teaching object-oriented principles is finding a suitable programming language. Many of these languages are too complex and their environments too confusing. This lesson sequence offers a choice of one of two approaches in an attempt to address this problem.
Making maths quizzes 2

Making maths quizzes 2: Implementing a digital solution

In this sequence students implement a digital solution for a maths quiz. They test and assess how well it works.
Who wants to be a millionaire

Who wants to be a millionaire?

Drawing on the well-known wheat/rice and chessboard problem, students use spreadsheets to simulate iteration and to solve problems.
Planting fruit and vegetables

Planting fruit and vegetables

This sequence integrates science as students grow a plant from seed, capture each step and decision as an algorithmic process and record data for future learning.
Seven seasons

Seven seasons

Leveraging the Year 10 Geography curriculum, this sequence works with the CSIRO Indigenous seasons calendars. Students produce a searchable database that captures data using the two data sources.
Buzzing with Bee-Bots

Buzzing with Bee-Bots

Students follow and describe a series of steps to program a floor robot. Plan a route to program a robot to follow a path and write a sequence of steps (algorithm).
Getting warmer

Getting warmer

This lesson sequence intentionally uses a visual-based programming tool to introduce designing and validating algorithms. Those students who complete this task can move to code the result in any text-based language with which they are familiar.

APPLICATIONS & GAMES

For the classroom

Blockly Games

Blockly Games

This series of self-paced interactive games progressively introduces programming concepts and challenges students to apply these to solve problems.

Code Monster

Code Monster

Code Monster is an interactive JavaScript editor and tutorial for students to learn basic coding concepts.

CASE STUDIES

John Monash Science School

John Monash Science School

The journey towards an integrated approach to digital technologies

my future

myfuture

This website assists users to identify a range of careers related to computational thinking and coding.

Curriculum links

Level F - 2:

Follow, describe and represent a sequence of steps and decisions (algorithms) needed to solve simple problems (ACTDIP004)

Level 3 - 4:

Define simple problems, and describe and follow a sequence of steps and decisions (algorithms) needed to solve them (ACTDIP010)

Implement simple digital solutions as visual programs with algorithms involving branching (decisions) and user input (ACTDIP011)

Level 5 - 6:

Design a user interface for a digital system (ACTDIP018)

Design, modify and follow simple algorithms involving sequences of steps, branching, and iteration (repetition) (ACTDIP019)

Implement digital solutions as simple visual programs involving branching, iteration (repetition), and user input (ACTDIP020)

Level 7 - 8:

Define and decompose real-world problems taking into account functional requirements and economic, environmental, social, technical and usability constraints (ACTDIP027)

Design algorithms represented diagrammatically and in English, and trace algorithms to predict output for a given input and to identify errors (ACTDIP029) 

Implement and modify programs with user interfaces involving branching, iteration and functions in a general-purpose programming language (ACTDIP030)

Level 9 - 10:

Define and decompose real-world problems precisely, taking into account functional and non-functional requirements and including interviewing stakeholders to identify needs (ACTDIP038)

Design algorithms represented diagrammatically and in structured English and validate algorithms and programs through tracing and test cases (ACTDIP040)

Implement modular programs, applying selected algorithms and data structures including using an object-oriented programming language (ACTDIP041)