Unpack the Curriculum

Understand the Australian Curriculum: Digital Technologies

Australian Digital Technologies Curriculum:

Data interpretation

The process of extracting meaning from data. Methods include modelling, statistical analysis, and visualisation.
Data interpretation
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F-2

Collect, explore and sort data, and use digital systems to present the data creatively (ACTDIP003)

3-4

Collect, access and present different types of data using simple software to create information and solve problems (ACTDIP009)

5-6

Acquire, store and validate different types of data, and use a range of software to interpret and visualise data to create information (ACTDIP016)

7-8

Analyse and visualise data using a range of software to create information, and use structured data to model objects or events (ACTDIP026)

9-10

Analyse and visualise data to create information and address complex problems, and model processes, entities and their relationships using structured data (ACTDIP037)
Organise data

Organise data explores the ways we order, sort and arrange data to assist us with interpretation in different contexts.

F-2

Organise data

Organise data by classifying, grouping and sorting.

Students explore data by classifying, grouping, and sorting (e.g. ordering students by height; grouping photos of pets by their type).

3-4

Interpret data

Organise data to answer questions.

Students answer simple questions by classifying, grouping, and sorting data (e.g. what is the most common car colour? how many female convicts were in the First Fleet?)

5-6

Interpret data

Organise data to answer questions.

Students can work with data that requires some simple processing using software. This could be in the form of things such as simple spreadsheet calculations or using data in code. They draw conclusions about the data as a result of this processing.

7-8

Analyse data

Examine data methodically and in detail to explain or interpret it.

Students can perform a variety of methodical calculations and manipulations of data (such as filtering, or working with subsets) to gain greater insight into its meaning and/or information.

Data modelling

To reorganise or restructure data to highlight different properties, or to enable new or alternative means of processing or analysing it.

Students can explain why not all data is atomic (i.e. stand-alone), and how sets of data often infer some kind of relatedness (e.g. weather data for a location over a period of time). They think about how the way that data is structured (e.g. in tables) helps to communicate its meaning and allow for better analysis.

9-10

Analyse data

Examine data methodically and in detail to explain or interpret it.

Students can investigate problems that may not have conclusive answers, and analysis of the data may lead to a strengthening of one view or another. Analysis may involve further data collection and analysis to make a conclusion about a hypothesis.

Data modelling

To reorganise or restructure data to highlight different properties, or to enable new or alternative means of processing or analysing it.

Students can understand the defined relationships between sets of data (e.g. the relationship between income and job), and consider ways of formatting or structuring their data to allow for ease of manipulation and analysis both manually and using software. This includes how data may define a process, such as its transformation over time, and how that would be represented.
Visualise data

Visualise data describes the many ways we present data in its raw and summarised form for communication and further analysis.

F-2

Present data

Present data in various ways to summarise data.

Students use digital systems to present data in different ways to answer simple questions (e.g. use a table or pictogram to present the most common pet at home).

3-4

Present data

Present data in various ways to summarise data.

Students present acquired data in different ways to answer questions (e.g. graph plant height to determine if sunlight increases growth).

5-6

Visualise data

Display data in various ways that either assists with understanding its meaning or allows for new meaning to be inferred.

Students can develop visualisations through software tools, such as heat maps, infographics or other forms of communication, as well as producing graphs or tables to present data.

7-8

Visualise data

Display data in various ways that either assists with understanding its meaning or allows for new meaning to be inferred.

students can generate visualisations programmatically or dynamically (i.e. that respond to change) using either pre-existing software tools or their own software.

9-10

Visualise data

Display data in various ways that either assists with understanding its meaning or allows for new meaning to be inferred.

Students can contrast the different or conflicting positions data can communicate when visualised in different ways. They consider the preferred method of visualisation to communicate as effectively as possible.