# Science K–12

Computational thinking:

• is a process where a problem is analysed and solved so that a human, machine or computer can effectively implement the solution
• involves using strategies to organise data logically, break down problems into parts, interpret patterns and design and implement algorithms to solve problems.

The computational thinking video (5:13) below explains computational thinking using the NSW Science and Technology K-6 Syllabus. Examples from Early Stage 1, Stage 2 and Stage 3 show how computational thinking could be embedded in the classroom.

Computational thinking using the NSW Science and Technology K-6 Syllabus

### Transcript of Computational thinking

[Light-hearted, upbeat music]

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The new Science and Technology K-6 Syllabus was released by the NSW Education Standards Authority (NESA) in 2017. This resource is designed to support teachers' knowledge and understanding of the Science and Technology K-6 Syllabus, in particular, the inclusion of four thinking skills.

These thinking skills are computational thinking, design thinking, scientific thinking and systems thinking. These four thinking skills encompass the productive, purposeful and intentional thinking that underpins effective learning in science and technology. This video will explore the thinking skill computational thinking and how it is embedded in the new Science and Technology K-6 Syllabus.

As the table shows, computational thinking skills are embedded within various content strands of the new Science and Technology K-6 Syllabus. Opportunities to embed computational thinking skills are identified by the ComT abbreviation after individual syllabus dot points. So what is computational thinking?

Computational thinking is a process where a problem is analysed and solved so that a human, machine or computer can effectively implement the solution. It involves using strategies to organise data logically, break down problems into parts, interpret patterns and design and implement algorithms to solve problems. Computational thinking is typically subdivided into four key aspects which are decomposition, abstraction, pattern recognition and algorithms.

Decomposition. Decomposition involves breaking something down into smaller parts. We often do this when we have a large or difficult task and need to break it into smaller steps in order to make it more manageable.

[Decomposition STe-7DI-T: Students follow and describe a sequence of steps (algorithms]

In Early Stage 1, for example, this might involve having students break down the routine of arriving at school. How did they get ready for the day? What transport did they take? What did they do when they arrived at school?

[ ST2-3DP-T:Students describe and follow a sequence of steps and decisions (algorithms) to solve defined problems involving branching and user input]

In Stage 2, for example, this might involve examining the individual ingredients used to make a cake or writing a list of steps to plan a birthday party.

Abstraction. Abstraction is the ability to focus on the key details of a problem and ignore details that are unimportant. This is a vital skill in computational thinking as it can help us avoid getting bogged down by little details of a problem.

In Stage 1, this might involve students identifying the key skills you need to be a good soccer or football player. Whilst students might think that new soccer boots or fancy equipment make a good player, these details don’t focus on key skills such as passing and shooting. Abstraction removes unnecessary information in order to focus on what is important to solve the problem or answer the question.

Pattern Recognition. Pattern recognition is about looking for trends or similarities which might help us better organise our thinking. Pattern recognition is another key computational thinking skill that many students will already be familiar with, particularly in mathematics.

In Stage 2, this might involve students creating a T-chart to classify or organise a selection of living and non-living things. Pattern recognition requires students to look for similarities and differences between items in order to compare and group these things in meaningful ways. Exploring mathematical patterns such as the Fibonacci sequence can also be a great way to delve into pattern recognition.

Algorithms. Algorithms or algorithmic design involves creating a set of step-by-step instructions in order to complete a task or solve a problem. Providing a robot with a set of instructions to follow a map is an example of an algorithm.

[ST3-11DI-T: Students explore how the main components of digital systems connect together to form networks that transmit data]

In Stage 3, students might create a flowchart or written instructions in order to complete a task such as borrowing a book from the library or separating a mixture.

The problems and challenges that our students may face in the future are yet to be determined. Computational thinking will help students address this uncertainty, encouraging them to become more flexible problem solvers and innovative learners.

The science and technology page on the NSW Department of Education website contains additional syllabus implementation support materials for teachers, including professional development opportunities. If you would like further information about syllabus implementation, please contact the science and technology K-6 curriculum team on the details below.

[ scienceandtechnologyk6@det.nsw.edu.au

education.nsw.gov.au/science]

[End of transcript.]

Definition © 2017 NSW Education Standards Authority (NESA) for and on behalf of the Crown in right of the State of New South Wales.