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NSW Education Standards Authority

11–12Enterprise Computing 11–12 Syllabus

Record of changes
Implementation from 2024
Expand for detailed implementation advice

Content

Year 12

Intelligent systems
Systems and their applications
  • Investigate applications of decision support systems

  • Describe categories of decision-making within decision support systems

    Including:
    • an infinite set of instructions where judgement may be required (unstructured)
    • use of a specified set of finite instructions (semi-structured)
    • automated decisions (structured)
  • Investigate common applications of expert systems

    Including:
    • diagnosis
    • monitoring
    • process control
    • scheduling and planning
  • Describe key features of an expert system

    Including:
    • knowledge base
    • inference engine, including forward chaining and backward chaining
    • user interface (UI)
  • Research factors that have allowed expert systems to advance from rule-based systems to integrate probability

    Including:
    • processing power
    • data availability and access
    • hardware costs
    • neural networks
    • webometrics
  • Describe how people’s changing needs have shaped the proliferation of expert systems

    Including:
    • the Internet of Things (IoT)
    • Internet of Me (IoMe)
    • Industry 4.0
  • Describe the operation of simplistic and complex intelligent agents used by search engines, including predictive search strings and the use of voice assistants to initiate interaction

  • Compare techniques used by different inference engines

    Including:
    • truth maintenance
    • hypothetical reasoning
    • heuristic knowledge and fuzzy logic
    • ontology classification
  • Investigate the hardware used in an intelligent system

    Including:
    • biometrics
    • haptics
    • touch and gesture
    • virtual and augmented reality (VR/AR)
    • voice and sound
    • microcontrollers
    • sensors, actuators and motors
  • Explore how computational thinking can be integrated into the design and development of an intelligent system

    Including:
    • decomposition
    • pattern recognition
    • abstraction
    • algorithms
  • Communicate the logical processes performed by an intelligent system by using flowcharts, data flow diagrams and infographics

  • Investigate the disruptive effects of intelligent systems

    Including:
    • multitasking versus digital distraction
    • working differently to complete the same task
    • automation of enterprise and manufacturing processes
    • impact of artificial intelligence (AI) on employment
  • Investigate social and ethical issues to be considered when developing, implementing and using intelligent systems

  • Investigate current and emerging technologies associated with intelligent systems, including AI

  • Explain how intelligent systems combine innovative techniques and technologies to meet the needs of enterprise

Data and intelligent systems
  • Investigate the infrastructure requirements for an intelligent network in an enterprise with devices linked through an Internet of Things (IoT)

    Including:
    • networks with servers, local and cloud storage, and end-point devices
    • communication links that enable the efficient control and flow of data
  • Explore collection, type, storage, processing, application and transmission of relevant and surplus data in an intelligent IoT network

  • Investigate the application of simulation, data modelling and the automation of systems in a range of enterprises

    Including:
    • education and training
    • business analytics
    • high-risk applications
  • Explain the role of intelligent systems in surveillance

    Including:
    • closed circuit television (CCTV)
    • biometric scanning
    • customer loyalty schemes
    • fraud prevention
    • sniffing
    • trolling
  • Explain how AI supports efficiency in an IoT network

Creating intelligent systems
  • Develop a set of rules and facts that could be used within an expert system to draw conclusions

  • Apply certainty factors to construct a decision tree for a proposed expert system

  • Verify the sources of data used in a decision support system

  • Use a flowchart to develop a knowledge base of IF-THEN rules to be used by an expert system

  • Design and model an automated smart system using a range of inputs and outputs

  • Implement automated processing using software

  • Assess the output produced by a decision support system, including graphing to detail the success of decisions, and comparing the proposed versus the actual outputs

  • Explain how expert systems contribute to the efficiency of intelligent systems

    Including:
    • supercomputers
    • digital assistants
    • autonomous vehicles
    • streaming services
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