F-10 Curriculum (V8)
F-10 Curriculum (V9)
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This resource provides examples of ways Aboriginal and Torres Strait Islander Histories and Cultures can be integrated into Digital Technologies. Examples include 'classification and sorting data' and 'designing solutions'.
This video demonstrates ways in which data can be authenticated in spreadsheets. It is the second in a series of four.
This PDF demonstrates how using concepts derived from age-appropriate content, combined with multiple points of entry to and exit from a shopping-related task might remove barriers to learning. Students engage in purposeful and authentic open-ended explorations that require critical and creative thinking and incorporate ...
This resource provides strategies for assessing aspects of the Digital Technologies subject in the Australian Curriculum that relate to data using contexts from other learning areas and General Capabilities, including Science, Mathematics, Numeracy and Literacy. The resource includes an assessment planner and rubric, as ...
This PDF is a booklet that accompanies the years 3-4 assessment task, Classifying living and non-living things.
This document provides a scaffold to teach and assess students’ understanding of how digital systems can be used to monitor and collect information used for mapping and making judgements about the environment. Students record information using digital systems to investigate a school need, then design solutions to improve ...
This video demonstrates ways in which data can be analysed and visualised. It is the final in a series of four.
This PDF provides activities for collecting, analysing and representing data about litter in the local community. It prompts students to consider the implications of rubbish in the local environment, and suggests actions students can take in order to reduce litter.
Resource description This resource provides strategies for assessing students' understanding of the ways in which data can be sourced, organised and represented to maximise options for analysis, evaluation, decomposition and visualisation in order to create digital solutions. The context of the resource is the liveability ...
This video demonstrates ways in which data can be manipulated in spreadsheets. It is the first in a series of four.
This video demonstrates ways in which data can be structured in spreadsheets. It is the third in a series of four.
The Years 7-8 assessment task focuses on digital systems (integrating Digital Technologies and Science). The digital systems assessment task provides a scaffold to teach about and assess students’ understanding of how digital systems can be used to monitor the classroom learning environment. learn how to create environmental ...
Use the tasks in this lesson to introduce concepts that underpin artificial intelligence (AI). The majority of the tasks are unplugged (do not require a digital device). Use the downloadable AI cards with your students to explore what they know about AI.
This lesson is an introduction to the way in which a computer sees. It focuses on image recognition that involves feature extraction, object detection and classification. This lesson was developed in collaboration with Dr Karsten Schulz, Digital Technologies Institute.
This is the second in a series of lessons to transition from visual coding to text-based coding with a general-purpose programming language. This lesson may take two to three 45-minute periods. It introduces how to make decisions (branching) and identify data types.
Natural language processing is growing in importance. We often converse with automatic chatbots for customer service without even knowing. We also use online translation services or mobile apps. But how do these services work? Is there artificial intelligence (AI) in them? Three projects are offered to cater for student ...
This curriculum provides a teacher guidebook for implementing lessons, with learning and teaching activities, content, printable worksheets and some assessment lessons.
Artificial intelligence can sometimes be biased to certain shapes or colours. When such AI systems are applied to situations that involve people, then this bias can manifest itself as bias against skin colour or gender. This lesson explores bias in AI, where it comes from and what can be done to prevent it.