Evaluating recurrence as a measure of change in interpersonal dynamics. This project aims to develop an automated conversation analysis system to quantify how communication changes over extended periods of time. It is innovative in proposing to extend the theory and methods of recurrence analysis (a dynamical systems technique) to interacting modalities combining text, audio and video, and to longitudinal analyses. The project is significant in being the first to aim to measure communication dyn ....Evaluating recurrence as a measure of change in interpersonal dynamics. This project aims to develop an automated conversation analysis system to quantify how communication changes over extended periods of time. It is innovative in proposing to extend the theory and methods of recurrence analysis (a dynamical systems technique) to interacting modalities combining text, audio and video, and to longitudinal analyses. The project is significant in being the first to aim to measure communication dynamics over time in the fields of education, health, public discourse and science. It is expected to result in new theories and methods for recurrence analysis validated using real-world data; and to enable new technologies for evaluating professional communication training and communication changes resulting from education or disease progression.Read moreRead less
Protein structure prediction by deep long-range learning. This project aims to address the challenging problem of protein structure prediction by developing deep long-range learning methods. The project expects to advance protein structure prediction by capturing the long-range interactions through whole sequence learning, rather than short window-based learning. Expected outcomes include next-generation machine-learning techniques for predicting one, two and three-dimensional protein structures ....Protein structure prediction by deep long-range learning. This project aims to address the challenging problem of protein structure prediction by developing deep long-range learning methods. The project expects to advance protein structure prediction by capturing the long-range interactions through whole sequence learning, rather than short window-based learning. Expected outcomes include next-generation machine-learning techniques for predicting one, two and three-dimensional protein structures from their sequences. The expected outcomes should provide significant benefits by computationally determining protein structures beyond homologous sequences, and enabling structure-based drug discovery to disease-causing protein targets previously inaccessible to biotech and pharmaceutical companies.Read moreRead less
Combining modal logics for dynamic and multi-agent systems. Modern computer software systems are required to operate in complex dynamic environments and to handle functioning of highly sensitive (security and safety-critical) organizations in government and commerce. Typical applications include air-traffic control systems, telecommunication networks, and banking systems. To ensure robustness, computationally predictable behaviour and trustworthiness of these systems, their designs and implement ....Combining modal logics for dynamic and multi-agent systems. Modern computer software systems are required to operate in complex dynamic environments and to handle functioning of highly sensitive (security and safety-critical) organizations in government and commerce. Typical applications include air-traffic control systems, telecommunication networks, and banking systems. To ensure robustness, computationally predictable behaviour and trustworthiness of these systems, their designs and implementations must be formally well grounded. This is an important but difficult challenge. This project will systematically develop a framework by combining modal-logics to adequately capture and reason about temporal, epistemic and social aspects of dynamic and multi-agent systems. The combined logics would be evaluated on practical applications.
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Real-time high-level cognitive robotics controllers. Technological advances have seen the recent release of commercially affordable mobile robots. In the wake of Sony's immensely successful AIBO entertainment robot, it is anticipated that the market will be flooded with similar devices in short time. However, while traditional robotics focuses on problems like navigation and sensory perception, scant attention has been paid to the development of high-level cognitive robotics languages for coordi ....Real-time high-level cognitive robotics controllers. Technological advances have seen the recent release of commercially affordable mobile robots. In the wake of Sony's immensely successful AIBO entertainment robot, it is anticipated that the market will be flooded with similar devices in short time. However, while traditional robotics focuses on problems like navigation and sensory perception, scant attention has been paid to the development of high-level cognitive robotics languages for coordinating these lower-level "skills". Such languages allow development of sophisticated robot controllers. We aim to develop a cognitive robotics language capable of controlling robots in real-time and in a multi-agent setting requiring coordination among agents.Read moreRead less
Testing a relational account for visual working memory. This project aims to test whether Becker's relational theory of attention can explain visual working memory performance, the ability to remember visual items over brief time periods. According to the relational account, elementary features such as colours are encoded relative to other features in the context (e.g. as redder, larger, darker). Our ability to detect a change in a feature would depend on the features in the context, and on whet ....Testing a relational account for visual working memory. This project aims to test whether Becker's relational theory of attention can explain visual working memory performance, the ability to remember visual items over brief time periods. According to the relational account, elementary features such as colours are encoded relative to other features in the context (e.g. as redder, larger, darker). Our ability to detect a change in a feature would depend on the features in the context, and on whether the context remains constant. This project expects to provide insights into how features are represented in memory, and to predict which items will be remembered. This could help to develop interactions and therapies for the ageing population and in clinical disorders.Read moreRead less
Transforming primary teachers' representational practices: effects on students' scientific reasoning and discourse within contemporary sciences. Training teachers to appropriately represent and communicate scientific information is critically important for promoting scientific thinking and learning in students. This research is critical to securing Australia's future interests in developing new and emerging frontier science and technologies through the engagement and retention of students.
The role of relational information in the guidance of visual attention. The project aims to develop a new theory of attention that describes more accurately which items in the visual field can pop out and grab attention. The potential practical gains of the project are high, as it can lead to significant advancements in robotic vision, transport safety, and provide insights into clinical disorders such as ADHD.
Modelling with data: Advancing STEM in the primary curriculum. Improving the nation's skills in Science, Technology, Engineering, and Mathematics (STEM) remains a continuing concern, especially given the decline in international test results. The project aims to introduce a new approach to promoting this learning across grades 3-6 through modelling with data. With a focus on inquiry processes involving data variation and uncertainty within STEM-based contexts, the project aims to develop the imp ....Modelling with data: Advancing STEM in the primary curriculum. Improving the nation's skills in Science, Technology, Engineering, and Mathematics (STEM) remains a continuing concern, especially given the decline in international test results. The project aims to introduce a new approach to promoting this learning across grades 3-6 through modelling with data. With a focus on inquiry processes involving data variation and uncertainty within STEM-based contexts, the project aims to develop the important mathematical and statistical literacies needed for lifting student achievements. In advancing both theory and practice, the project aims to contribute to knowledge of primary students' capabilities for STEM problem solving and ways of enhancing implementation of the Australian Curriculum.Read moreRead less
The Control of Memory Access. The topic of control processes in memory access is central to most of the big questions about human memory such as; why we forget, what produces spectacular and tragic memory failures (e.g.,lighting a match to check the level of petrol in a tank) and the role of context in familiarity and recollection. Because of the centrality of the problems addressed there will be many applications for the results. The long term results will include better models for human ope ....The Control of Memory Access. The topic of control processes in memory access is central to most of the big questions about human memory such as; why we forget, what produces spectacular and tragic memory failures (e.g.,lighting a match to check the level of petrol in a tank) and the role of context in familiarity and recollection. Because of the centrality of the problems addressed there will be many applications for the results. The long term results will include better models for human operators which can be used in both civilian (e.g., air traffic control) and military applications. Other areas of application will include how we measure memory impairment, why we make errors in industrial settings, and the nature of memory deficits as we age. Read moreRead less
Love Maths, Why Not? Developing Students’ Positive Learning Identities and Engagement in Mathematics. Mathematics is the foremost enabling science that underpins research, development and innovation in every aspect of society. Recent trends in mathematics education show that attitude, confidence and a sense of personal relevance play an influential role in student engagement and achievement. Yet Australian students’ achievement in mathematics has plateaued, and participation in mathematics is st ....Love Maths, Why Not? Developing Students’ Positive Learning Identities and Engagement in Mathematics. Mathematics is the foremost enabling science that underpins research, development and innovation in every aspect of society. Recent trends in mathematics education show that attitude, confidence and a sense of personal relevance play an influential role in student engagement and achievement. Yet Australian students’ achievement in mathematics has plateaued, and participation in mathematics is steadily declining. This study combines innovative pedagogical research in mathematics with research of positive learning identity and engagement to develop knowledge about educational practices that sustain the attention and positive engagement of our nations’ future mathematicians, scientists and mathematically fluent citizenry. Read moreRead less