Science
Digital Technologies + Science
F-2
Planting fruit and vegetables (Digital Technologies Hub lesson)
In this sequence of lessons students grow a plant from seed, capturing each step and decision as an algorithmic process and recording data for future learning.
3-4
Rubbish recording and reduction: Part 1 (Digital Technologies Hub lesson)
In this lesson sequence students survey and collect data concerning what is brought to school each day and subsequently becomes rubbish. They then use Excel to represent that data in a variety of different ways.
Rubbish recording and reduction: Part 2 (Digital Technologies Hub lesson)
In this lesson sequence students use Excel to represent data in a variety of ways.
5-6
Makey Makey boards (Digital Technologies Hub lesson)
In this sequence of lessons students explore how electrical energy can be transferred and transformed in electrical circuits, using Makey Makey boards as the basis for experimentation and recoding of data.
Animal adaptations (Digital Technologies Hub lesson)
In this lesson sequence students explore aspects of animal adaptation prior to applying their knowledge to constructing their own digital creature using littleBits electronic sets.
Eco-calculator (Digital Technologies Hub lesson)
In this sequence of lessons students make a paper prototype of an eco-calculator to demonstrate human impact on the environment and suggest changes in behaviour. This is an unplugged activity with an opportunity to extend learning to create a digital solution using Scratch.
Is it going to rain today? (Digital Technologies Hub lesson)
In this lesson sequence students understand the importance of data in effective decision-making, and are able to find, sort and interpret Bureau of Meteorology (BOM) rainfall data, and to collect their own data and analyse the resulting datasets.
Learning environments (Digital Technologies Hub lesson)
This sequence of lessons explores how conditions in the environment can impact on learning. Through investigating the environmental influences on our classroom, and learning environments such as light, noise and temperature, students collect data and identify the optimal learning environment.