AI-supported data practices
Explore our STEM research task: an open ended task, involving the use of authentic data to estimate species adaptation to climate change in the Illawarra region.
Real-world problems are often complex and rely on the use of (large) data. They are made up of interacting parts, influencing each other. Climate change affects ecosystems, species and human systems.
Task Scenario
In this task, you are responsible for planning the protection of a species until ~2050.
You will choose one of four endangered species in the Illawarra region and use data to make a judgement about its future distribution under climate change pressures.
Step 1: Choose your species (see species list below)
Step 2: Select data from the Atlas of Living Australia and the NARCliM climate projection for the region, using worst case scenario. Search for any other relevant data.
Step 3: Analyse your data.
Step 4: Based on the evidence, make a prediction about how your chosen species needs to be managed into the future and its viability.
Use of GenAI: This task is intentionally complex and difficult. We would like you to collaborate with a GenAI chatbot for assistance: to help you explore different publicly available data, generate ideas and refine your arguments. We are interested in how you collaborate in a group and with AI (human-AI collaboration). While you do so, ensure that you critically evaluate GenAI outputs.
Choose Your Species (Illawarra Endangered Species)
Work in your group to choose ONE of these endangered species as the focus for your species management task.
Mammal • Key concern: forest canopy loss and changing food availability.
Reptile • Key concern: sandstone rock temperature changes and habitat fragmentation.
Amphibian • Key concern: wetland drying and altered rainfall patterns.
Advancing Science Education Through Empirical Research
Our research is dedicated to addressing the gap in data practices in the science classroom. We recognise the importance of preparing young citizens for a STEM-empowered workforce and to become critical consumers and users of data. We also acknowledge that we live in a world with complex problems, which require a future-oriented and forward thinking approach.
With our research, we will develop frameworks that empower both students and educators.
Connect with Our Researchers
We are dedicated to advancing the use of data and human-AI collaboration in science education through rigorous research and interactive learning tasks. OUr research team are: Dr Sarah Digan (University of Wollongong), Associate Professor Helen Georgiou (University of Wollongong), Dr Andrew Zamecnik (University of Adelaide) and Dr Katharina Peters (University of Wollongong).
Contact us for partnership opportunities, academic inquiries, or collaboration.