Preventing Early Academic Problems By Improving Working Memory: Translational Randomised Trial
Funder
National Health and Medical Research Council
Funding Amount
$831,085.00
Summary
Learning difficulties are common and can cause school failure and poor self-esteem. They are associated with specific problems with temporarily remembering and using information (‘working memory’). Research suggests that improving working memory might improve academic achievement. We will study this intervention in a large group of primary school children who have poor working memory. If successful, the intervention will provide a way to improve the learning skills of these high-risk children.
Discovery Early Career Researcher Award - Grant ID: DE240101089
Funder
Australian Research Council
Funding Amount
$436,847.00
Summary
Trustworthy Hypothesis Transfer Learning. It is urgent to develop a new hypothesis transfer learning scheme that can overcome potential risks when finetuning unreliable large-scale pre-trained models. This project aims to develop an advanced and reliable scheme of hypothesis transfer learning, called Trustworthy Hypothesis Transfer Learning (TrustHTL). A new theoretically guaranteed heterogeneous hypothesis transfer learning framework will be developed to handle heterogeneous situations; a metho ....Trustworthy Hypothesis Transfer Learning. It is urgent to develop a new hypothesis transfer learning scheme that can overcome potential risks when finetuning unreliable large-scale pre-trained models. This project aims to develop an advanced and reliable scheme of hypothesis transfer learning, called Trustworthy Hypothesis Transfer Learning (TrustHTL). A new theoretically guaranteed heterogeneous hypothesis transfer learning framework will be developed to handle heterogeneous situations; a methodology to disinherit risks of pre-trained models and a new fuzzy relation based distributional discrepancy in heterogeneous transfer learning scenarios. The outcomes should significantly improve the reliability of machine learning with benefits for safety learning in data analytics.Read moreRead less
Self-supervised feature learning for rapid processing of marine imagery. Fast and reliable quantitative estimates of marine environmental health are needed for scientific studies, design and management of protected areas, and regulatory compliance of industrial activity in the ocean. Australia is collecting seafloor images at increasing rates but expert annotations are not keeping up, meaning that typical machine learning approaches struggle. This project will develop self-supervised techniques ....Self-supervised feature learning for rapid processing of marine imagery. Fast and reliable quantitative estimates of marine environmental health are needed for scientific studies, design and management of protected areas, and regulatory compliance of industrial activity in the ocean. Australia is collecting seafloor images at increasing rates but expert annotations are not keeping up, meaning that typical machine learning approaches struggle. This project will develop self-supervised techniques that use large amounts of unlabeled data to enhance performance. Our design takes advantage of additional information available for marine imagery such as geolocation and remote sensing context. We will explore how these representations can guide additional sampling and improve performance in classification tasks.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE140100751
Funder
Australian Research Council
Funding Amount
$379,506.00
Summary
How health shapes young children’s academic outcomes, and opportunities to intervene. Every year, about 280,000 Australian children make the crucial transition from preschool to formal education. Within this population, there is a wide range of learning capabilities and levels of preparedness. Children who have difficulties during the early years have greater risk of poorer academic and social outcomes. This project aims to determine how children's academic outcomes are shaped by common physical ....How health shapes young children’s academic outcomes, and opportunities to intervene. Every year, about 280,000 Australian children make the crucial transition from preschool to formal education. Within this population, there is a wide range of learning capabilities and levels of preparedness. Children who have difficulties during the early years have greater risk of poorer academic and social outcomes. This project aims to determine how children's academic outcomes are shaped by common physical health problems during the early years of school and how best to address these problems within the traditional school setting. This will inform future research as to the opportunities to help all children have the best opportunity to learn so they can reach their academic potential.Read moreRead less
Exploiting Geometries of Learning for Fast, Adaptive and Robust AI. This project aims to uniquely exploit geometric manifolds in deep learning to advance the frontier of Artificial Intelligence (AI) research and applications in cybersecurity and general cognitive tasks. It expects to develop new theories, algorithms, tools, and technologies for machine learning systems that are fast, adaptive, lifelong and robust, even with limited supervision. Expected outcomes will enhance Australia's capabili ....Exploiting Geometries of Learning for Fast, Adaptive and Robust AI. This project aims to uniquely exploit geometric manifolds in deep learning to advance the frontier of Artificial Intelligence (AI) research and applications in cybersecurity and general cognitive tasks. It expects to develop new theories, algorithms, tools, and technologies for machine learning systems that are fast, adaptive, lifelong and robust, even with limited supervision. Expected outcomes will enhance Australia's capability and competitiveness in AI, and deliver robust and trustworthy learning technology. The project should provide significant benefits not only in advancing scientific and translational knowledge but also in accelerating AI innovations, safeguarding cyberspace, and reducing the burden on defence expenses in Australia.Read moreRead less
The Benefits of Utilising Visual-Spatial Representations of Numbers . The aim of this project is to investigate how visual-spatial representations of numbers enhance practice to promote the use of retrieval-based over counting-based strategies for children learning early arithmetic. About one-third of Australian children stay reliant on counting strategies for basic arithmetic, despite these being associated with lower achievement in mathematics in later years. Expected outcomes of this project ....The Benefits of Utilising Visual-Spatial Representations of Numbers . The aim of this project is to investigate how visual-spatial representations of numbers enhance practice to promote the use of retrieval-based over counting-based strategies for children learning early arithmetic. About one-third of Australian children stay reliant on counting strategies for basic arithmetic, despite these being associated with lower achievement in mathematics in later years. Expected outcomes of this project are new understandings of how problem-answer associations can be strengthened in memory and the development of tools to promote retrieval-based strategies. Potential benefits include children who are better prepared to take on higher-level mathematics in secondary school and, subsequently, more numerate citizens. Read moreRead less
Indigenous persistence in formal learning. This project will improve knowledge of the learning experiences of Indigenous students transiting from TAFE to university studies. The results will have significant implications for the ways Indigenous students can be supported in their studies in order to achieve better quality learning experiences as well as learning outcomes.
Modelling complex learning spaces. The growing use of digital tools and resources means that students' learning activities are no longer tied to unique physical places. Their work is distributed across increasingly complex mixtures of physical and digital spaces, which both shape and are shaped by students' activity. This project aims to identify productive ways of modelling the characteristics and uses of complex learning spaces in higher education. Evidence and models generated by the project ....Modelling complex learning spaces. The growing use of digital tools and resources means that students' learning activities are no longer tied to unique physical places. Their work is distributed across increasingly complex mixtures of physical and digital spaces, which both shape and are shaped by students' activity. This project aims to identify productive ways of modelling the characteristics and uses of complex learning spaces in higher education. Evidence and models generated by the project aim to strengthen the logic connecting the use, management and design of learning spaces. A better understanding of the relations between pedagogy, activity and space will improve the work of architects and other designers, campus managers, university teachers and students themselves.Read moreRead less
Does a teacher-led mindfulness intervention improve student outcomes? This project aims to determine if improving teacher knowledge and practice of mindfulness in the classroom, can lead to better child attention and school functioning outcomes during the early primary school years. Mindfulness is an approach that aims to improve attention, self-regulation, mental health, and cognitive functioning. Expected outcomes include new knowledge as to whether mindfulness can be integrated into classroom ....Does a teacher-led mindfulness intervention improve student outcomes? This project aims to determine if improving teacher knowledge and practice of mindfulness in the classroom, can lead to better child attention and school functioning outcomes during the early primary school years. Mindfulness is an approach that aims to improve attention, self-regulation, mental health, and cognitive functioning. Expected outcomes include new knowledge as to whether mindfulness can be integrated into classroom practice, how to best implement it, student benefits and cost-effectiveness. Findings will inform schools as to whether this approach can support students in making a positive transition to primary school that can place them on positive academic and well-being pathways and lead to benefits in their adulthood.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE240100144
Funder
Australian Research Council
Funding Amount
$444,447.00
Summary
Universal Model Selection Criteria for Scientific Machine Learning. This project aims to develop provably reliable universal model selection criteria to facilitate trustworthy scientific machine learning. Combining stochastic methods with an innovative geometric approach to basic statistical principles, this project expects to characterise, combine, and refine the most successful heuristics for designing and training huge models, such as deep neural networks, into a cohesive theoretical framewor ....Universal Model Selection Criteria for Scientific Machine Learning. This project aims to develop provably reliable universal model selection criteria to facilitate trustworthy scientific machine learning. Combining stochastic methods with an innovative geometric approach to basic statistical principles, this project expects to characterise, combine, and refine the most successful heuristics for designing and training huge models, such as deep neural networks, into a cohesive theoretical framework. The expected outcomes include a general toolkit for assisting neural network design at the forefront of scientific applications. This should significantly improve the quality of scientific predictions by facilitating confident adoption of deep learning methods into the pantheon of trustworthy modeling techniques. Read moreRead less