11–12Enterprise Computing 11–12 Syllabus
The new Enterprise Computing 11–12 Syllabus (2022) is to be implemented from 2024.
2024, Term 1
- Start teaching new syllabus for Year 11
- Start implementing new Year 11 school-based assessment requirements
- Continue to teach the Information Processes and Technology Stage 6 Syllabus (2009) for Year 12
2024, Term 4
- Start teaching new syllabus for Year 12
- Start implementing new Year 12 school-based assessment requirements
2025
- First HSC examination for new syllabus
Content
Year 12
Explain the purposes of data visualisation
Including:- simplifying understanding
- telling a story
- highlighting significant results
Describe how features of software contribute to a better understanding of datasets through data visualisation, including spreadsheets, creative design applications and combining applications to track trends and forecast
Identify patterns in data by interpreting and comparing datasets for an enterprise, social or ethical issue to highlight trends and for predictive data analytics
Investigate the impact of the evolution of hardware and software on the field of data analytics
Including:- processing power
- storage/memory
- communication media
Describe online analytical processing (OLAP)
Assess data integrity in the development of a data visualisation
Including:- ownership
- source
- validation
- risk
Explain the impact of enterprise data warehousing on data visualisation
Including:- analysis and use of historical data trends and patterns
- correlation with current data
- data refinement/optimisation
Explain how big data affects the design and development of data visualisation
Including:- scope of visible information
- types and depth of insight provided by the data
Evaluate bias in data collection, storage and analysis when developing visualisations
Including:- accuracy
- audience
- data source
- unconscious bias
Evaluate the effectiveness of software tools used to develop data visualisations
Including:- spreadsheets used to develop dashboards
- presentation software used to present data analysis
- business analytics services, including ‘as a service’ products
- custom software solutions
Interrogate data from a data visualisation
Including:- interpreting what you see
- aggregation
- filtering
- the effect of outliers
- reasoning
Use graphic design tools to assist in the graphic development of a data visualisation
Explain how user experience (UX) influences the development of effective data visualisations
Including:- relevance to the audience
- audience interpretation
- customisation
- live analysis
Develop and implement criteria for evaluating the effectiveness of user experiences
Investigate the impact of emerging hardware and software technologies on user interface (UI) and UX design and development
Research, source, organise and store data appropriate for a data visualisation
Design and develop a data visualisation for a specific scenario to represent trends, patterns and relationships, and illustrate predictive analysis incorporating big data
Investigate and implement methods to maintain data security
Including:- cybersecurity
- data backup