The Development of Creative Thinking Ability in TAFE Design Students. The aim is to develop an instructional framework as a conceptual basis for instruction aimed at TAFE design student use of imagery in creative thinking. The research addresses the challenges of recent post-compulsory education initiatives, which include a more specific focus on the development of creative problem-solving skills, but provide little guidance on instructional strategies. The research will synthesise the framewo ....The Development of Creative Thinking Ability in TAFE Design Students. The aim is to develop an instructional framework as a conceptual basis for instruction aimed at TAFE design student use of imagery in creative thinking. The research addresses the challenges of recent post-compulsory education initiatives, which include a more specific focus on the development of creative problem-solving skills, but provide little guidance on instructional strategies. The research will synthesise the framework from theories about cognitive processes, creative problem-solving and the use of mental imagery; and the results of an imagery training program and creative problem-solving interventions. The outcome will be an instructional framework for guiding the development of student creative thinking in design-based courses in TAFE.Read moreRead less
Faster, cheaper, safer: how to accelerate rail driver training and avert the looming skills shortage. The Australian rail industry is growing rapidly and needs to double the number of drivers trained in order to meet demand. This project will bring together Australia's leading hi-tech simulator company and Australia's leading rail human factors research team to 'reinvent' driver training technologies and techniques for the 21st century.
Discovery Early Career Researcher Award - Grant ID: DE140100772
Funder
Australian Research Council
Funding Amount
$393,414.00
Summary
Response Time Constraints on Category Learning. Theories of associative learning and decision-making are among the most mathematically well developed in psychology. However, theories of learning do not account for the time course of decision-making, and theories of decision-making do not account for how decision-relevant information is learned. This project will develop an integrated theoretical framework linking core principles of associative learning theories with sequential sampling models of ....Response Time Constraints on Category Learning. Theories of associative learning and decision-making are among the most mathematically well developed in psychology. However, theories of learning do not account for the time course of decision-making, and theories of decision-making do not account for how decision-relevant information is learned. This project will develop an integrated theoretical framework linking core principles of associative learning theories with sequential sampling models of the time course of decision-making. The new theory will provide a quantitative account of how incremental associative learning processes drive changes in cognitive representations that, in turn, account for known changes in the time course of decision-making.Read moreRead less
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
Can the relational account of attention explain search in natural environments and inattentional blindness? This project aims to further extend the relational theory of attention to account for visual search and inattentional blindness in natural environments. In addition, the neuronal correlates for inattentional blindness will be investigated with the use of Functional Magnetic Resonance Imaging (fMRI). The research has fundamental implications for theories of visual attention and awareness, a ....Can the relational account of attention explain search in natural environments and inattentional blindness? This project aims to further extend the relational theory of attention to account for visual search and inattentional blindness in natural environments. In addition, the neuronal correlates for inattentional blindness will be investigated with the use of Functional Magnetic Resonance Imaging (fMRI). The research has fundamental implications for theories of visual attention and awareness, and will advance understandings of how and why we frequently fail to notice potentially important objects and events in the environment.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
Mechanisms of learning at the interface between perception and action. Using the latest in brain imaging and simulator technology, this project will advance understanding of how experience shapes the visual centres of our brain. It will also support partnerships with construction, mining and health services by developing real and virtual machine interfaces and tools to enhance the outcome of simulator-based training.