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NSW Curriculum
NSW Education Standards Authority

7–10Science 7–10 Syllabus

Record of changes
Implementation from 2026
Expand for detailed implementation advice

Content

Stage 5

Data science 2

Working scientifically

In this focus area, students develop skills in analysing data and information, problem-solving and communicating scientific arguments with evidence. Additional Working scientifically outcomes and skills may be integrated with this content.

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Data science context

The Data science focus area can be taught alongside other focus areas, or aligned to students’ interests, local context or school environment.

Investigating questions and claims
  • Discuss the features of investigable and non-investigable questions, including considerations of available resources

  • Investigate how scientific knowledge is verified and refined by scientists through hypothesis testing and peer review

  • Develop criteria and use them to evaluate whether online content is valid and reliable

  • Identify a claim that can be scientifically tested with an investigation, or series of investigations, to test the claim

  • Explain the evidence and reasoning used to support conclusions about claims, using data from investigations

  • Conduct a written scientific argument showing how a range of evidence supports a claim

Pseudoscience
  • Explain the distinction between science and pseudoscience using examples

  • Identify examples of pseudoscientific claims

  • Investigate incidences of pseudoscience in popular media

  • Investigate how data, or its analysis and interpretation, can be distorted to manipulate findings that support specific viewpoints

  • Determine if an assertion of a claim or theory is pseudoscientific

Large datasets and scientific argumentation
  • Outline the features, collection, uses and applications of large datasets

  • Use available large datasets to develop and test a question

  • Conduct a descriptive analysis of a large dataset

  • Identify and outline the benefits of using descriptive statistical analysis techniques to assist in recognising or communicating patterns

  • Conduct a univariate analysis and a bivariate analysis using large datasets

  • Recognise the difference between causal and correlational relationships

  • Explore the role of large datasets and statistical analysis in validating scientific findings

Data science 2 in context
  • Use data to make evidence-based decisions about a familiar issue and assess the implications of these decisions

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