Teaching how to learn: promoting self-regulated learning in STEM classes. This project aims to investigate key factors that influence change in teacher practices and student achievement in Science, Technology, Engineering and Mathematics (STEM). It will involve the development and evaluation of interventions designed to help teachers create learning environments that promote student engagement and the development of the cognitive and metacognitive skills needed for success in STEM. The project w ....Teaching how to learn: promoting self-regulated learning in STEM classes. This project aims to investigate key factors that influence change in teacher practices and student achievement in Science, Technology, Engineering and Mathematics (STEM). It will involve the development and evaluation of interventions designed to help teachers create learning environments that promote student engagement and the development of the cognitive and metacognitive skills needed for success in STEM. The project will advance our understanding of how to increase the quality of teaching and learning in STEM subjects. Improving teacher capacity and student performance in STEM is a national priority with significant social and economic benefits to Australia.Read moreRead less
Using large scale modelling to understand reading development and dyslexia. This project aims to construct a computational model of reading that makes quantitative predictions about reading behaviour and dyslexia. It will test theories of reading development and dyslexia based on what they predict in terms of reading performance, predictions which many theories of dyslexia do not make. The model will be in English, French and Italian, which offer rich and constraining data to test the model. The ....Using large scale modelling to understand reading development and dyslexia. This project aims to construct a computational model of reading that makes quantitative predictions about reading behaviour and dyslexia. It will test theories of reading development and dyslexia based on what they predict in terms of reading performance, predictions which many theories of dyslexia do not make. The model will be in English, French and Italian, which offer rich and constraining data to test the model. The project is expected to explain the link between reading performance and underlying influences and why dyslexia manifests differently in different languages.Read moreRead less
Early years languages learning in Australia. This project aims to investigate early year’s language programs in Australian schools. The project will explore and analyse successful programs in the three states of NSW, Queensland and Victoria, policy, curricula and resources for languages teaching and learning, key stakeholder perspectives, and student progress in new primary language teaching degrees. The project expects to generate new knowledge of linked best practice program types, pedagogies, ....Early years languages learning in Australia. This project aims to investigate early year’s language programs in Australian schools. The project will explore and analyse successful programs in the three states of NSW, Queensland and Victoria, policy, curricula and resources for languages teaching and learning, key stakeholder perspectives, and student progress in new primary language teaching degrees. The project expects to generate new knowledge of linked best practice program types, pedagogies, and teacher requirements, to provide new data and ongoing research opportunities. Intended benefits include the education of more linguistically and culturally competent young Australians who are able to effectively engage in a plurilingual, globalised world.Read moreRead less
Data analytics-based tools and methods to enhance self-regulated learning. This project aims to develop student self-regulated learning skills by harnessing the potential of Big Data analytics. The project expects to generate new knowledge at the intersection of learning analytics, educational technology, learning sciences and teaching practice resulting from novel data collection and analysis tools and methods. The outputs are expected to include insights into metacognitive, motivational, and t ....Data analytics-based tools and methods to enhance self-regulated learning. This project aims to develop student self-regulated learning skills by harnessing the potential of Big Data analytics. The project expects to generate new knowledge at the intersection of learning analytics, educational technology, learning sciences and teaching practice resulting from novel data collection and analysis tools and methods. The outputs are expected to include insights into metacognitive, motivational, and technical issues facing analytics-based personalised feedback. The outcomes are intended to offer benefits for developing pedagogical and the design of educational technology. The outcomes can result in improved student learning outcomes in higher education to ensure graduates are prepared for the digital economy.Read moreRead less
Sound discrimination in embryos affects lifetime fitness. This project aims to investigate the role of prenatal sound discrimination on postnatal vocal learning and foraging breadth. The project expects to generate new knowledge in the area of neuroscience and psychology using an innovative approach to measure how embryos learn, and determine effects of prenatal vocal experience on the repertoire of postnatal behaviour. Expected outcomes include understanding biological mechanisms for effective ....Sound discrimination in embryos affects lifetime fitness. This project aims to investigate the role of prenatal sound discrimination on postnatal vocal learning and foraging breadth. The project expects to generate new knowledge in the area of neuroscience and psychology using an innovative approach to measure how embryos learn, and determine effects of prenatal vocal experience on the repertoire of postnatal behaviour. Expected outcomes include understanding biological mechanisms for effective learning across life stages that would be useful to develop novel approaches for non-invasive monitoring of embryonic cognition.Read moreRead less
Learning how people read: Models, brains, big data and maths. Aims: This project aims to understand how people read. We will use novel mathematical methods, experimentation, brain imaging and computational modelling to adjudicate between model predictions.
Significance: This project expects to develop methods to understand and test important aspects of reading.
Expected outcomes: Expected outcomes are the development of novel methods for understanding complex models and the collection of data t ....Learning how people read: Models, brains, big data and maths. Aims: This project aims to understand how people read. We will use novel mathematical methods, experimentation, brain imaging and computational modelling to adjudicate between model predictions.
Significance: This project expects to develop methods to understand and test important aspects of reading.
Expected outcomes: Expected outcomes are the development of novel methods for understanding complex models and the collection of data that can extend and falsify current models of reading.
Benefits: These developments will significantly increase our understanding of how people read and what causes dyslexia. This work will also provide new ways to evaluate complex computational psychological models.Read moreRead less
Evaluating models of category learning that use general feature-based representations. Three competing models of human category learning will be evaluated by comparing their behaviour to human performance on an experimental task where each model makes qualitatively different predictions. A series of theoretical and algorithmic advances will be undertaken to ensure each of the category learning models uses the same feature-based representation. Because the three models propose very different lear ....Evaluating models of category learning that use general feature-based representations. Three competing models of human category learning will be evaluated by comparing their behaviour to human performance on an experimental task where each model makes qualitatively different predictions. A series of theoretical and algorithmic advances will be undertaken to ensure each of the category learning models uses the same feature-based representation. Because the three models propose very different learning processes, their comparison will give insight into the basic cognitive process of categorisation. The algorithms for generating feature representations and modelling human category learning will also have potential for application in data visualisation and information handling systems.Read moreRead less
Hierarchical Bayesian Models for Human Conceptual Learning. This project seeks to understand the nature of human conceptual learning. With the shift to an information-based economy, it becomes important to understand what assumptions a real-world learning system should make. Even given the impressive growth of machine learning and artificial intelligence, the human mind remains the most successful example of such a system. In this light, the scientific study of human conceptual structure present ....Hierarchical Bayesian Models for Human Conceptual Learning. This project seeks to understand the nature of human conceptual learning. With the shift to an information-based economy, it becomes important to understand what assumptions a real-world learning system should make. Even given the impressive growth of machine learning and artificial intelligence, the human mind remains the most successful example of such a system. In this light, the scientific study of human conceptual structure presents the opportunity to discover how an intelligent thinking system should operate. In addition, many important problems facing an information economy involve being able to understand how people behave. An understanding of the concepts people use is central to this endeavour.Read moreRead less
Improving eyewitness identification accuracy using free-report lineups. There is major national and community interest in the successful conduct of criminal investigations. This research addresses the accuracy of eyewitness identification tests. Specifically, we investigate whether developing lineup procedures that separate out witnesses who are unsure of their response will prevent erroneous identifications. Progress on this issue makes an important contribution to decisions about the ideal lin ....Improving eyewitness identification accuracy using free-report lineups. There is major national and community interest in the successful conduct of criminal investigations. This research addresses the accuracy of eyewitness identification tests. Specifically, we investigate whether developing lineup procedures that separate out witnesses who are unsure of their response will prevent erroneous identifications. Progress on this issue makes an important contribution to decisions about the ideal lineup procedure, thereby preventing innocent people from being prosecuted and perpetrators being free to re-offend. Additionally the international collaboration on the project will increase the visibility of Australian social science research and provide crucial development opportunities for young Australian scientists.Read moreRead less
Identifying the bad guy with deadlined confidence judgments. There is major interest in the successful conduct of criminal investigations. Identity tests are commonly used in such investigations, but eyewitness decision accuracy is still unacceptably low. While eyewitness memory research has already contributed significantly to the development of procedures that improve the diagnosticity of identification decisions, our proposal offers radical new alternatives that can significantly improve diag ....Identifying the bad guy with deadlined confidence judgments. There is major interest in the successful conduct of criminal investigations. Identity tests are commonly used in such investigations, but eyewitness decision accuracy is still unacceptably low. While eyewitness memory research has already contributed significantly to the development of procedures that improve the diagnosticity of identification decisions, our proposal offers radical new alternatives that can significantly improve diagnosticity. In refining and evaluating these alternatives we will boost the profile of Australian science research and provide rich international training environments for young Australian and overseas scientists.Read moreRead less