Discovery Early Career Researcher Award - Grant ID: DE240100883
Funder
Australian Research Council
Funding Amount
$452,777.00
Summary
The cognitive science of farsighted deliberation. Many fundamental decisions in life require us to deliberate about sooner versus later consequences. This cognitive psychology project aims to determine how the capacities that enable people to think about the future (prospection) and reflect on their own thinking (metacognition) influence how they manage such decisions. By using innovative methods, this project is expected to advance our understanding of future-oriented cognition across the lifes ....The cognitive science of farsighted deliberation. Many fundamental decisions in life require us to deliberate about sooner versus later consequences. This cognitive psychology project aims to determine how the capacities that enable people to think about the future (prospection) and reflect on their own thinking (metacognition) influence how they manage such decisions. By using innovative methods, this project is expected to advance our understanding of future-oriented cognition across the lifespan. Expected outcomes include new knowledge about how people deliberate through important everyday decisions. This should provide significant benefits by laying the foundation for improving effective choices about the future.Read moreRead less
Understanding the role of mental imagery in cognition and behaviour. This project aims to develop objective physiological methods to measure mental imagery, uncover its brain mechanisms using neuroimaging and show how it biases cognition. It has long been suspected that mental imagery biases cognition, visual working memory and perception. However, showing this has been difficult due to a lack of measurement techniques. Here this is overcome by developing novel assay technologies and applying th ....Understanding the role of mental imagery in cognition and behaviour. This project aims to develop objective physiological methods to measure mental imagery, uncover its brain mechanisms using neuroimaging and show how it biases cognition. It has long been suspected that mental imagery biases cognition, visual working memory and perception. However, showing this has been difficult due to a lack of measurement techniques. Here this is overcome by developing novel assay technologies and applying them to the extremes of imagery, Aphantasia (no imagery) and Hyperphantasia (strong and vivid imagery). Expected outcomes include new measurement tools for generations of scientists, understanding the brain mechanisms of imagery and showing how our cognition (memory, risk, investing) is biased by mental imagery. Read moreRead less
Towards a cognitive process model of how attention and choice interact. Before making any decision, we must gather information on what options are available. This process may influence the choices we make: if we do not notice an option, we will not choose it even if it would have been valuable. This project aims to examine how prior experience can produce attentional biases that influence decisions, and will develop a new computational model of this interaction of attention and choice as an outc ....Towards a cognitive process model of how attention and choice interact. Before making any decision, we must gather information on what options are available. This process may influence the choices we make: if we do not notice an option, we will not choose it even if it would have been valuable. This project aims to examine how prior experience can produce attentional biases that influence decisions, and will develop a new computational model of this interaction of attention and choice as an outcome. This new knowledge will enhance the world-class status of Australian cognitive psychology. Moreover, it should provide significant benefits through improving our ability to predict and shape behaviour, and shedding light on the role of biases in healthy cognition and in the context of compulsive behaviours.Read moreRead less
Using cognitive models to understand memorability of real world images. This proposal aims to understand and make predictions about which real world images -- specifically living things, objects, and human faces -- that people will remember remember via an integration of cognitive models of memory and machine learning techniques. Computer vision models and similarity scaling techniques will be used to produce psychological representations of the images. These representations will then be integra ....Using cognitive models to understand memorability of real world images. This proposal aims to understand and make predictions about which real world images -- specifically living things, objects, and human faces -- that people will remember remember via an integration of cognitive models of memory and machine learning techniques. Computer vision models and similarity scaling techniques will be used to produce psychological representations of the images. These representations will then be integrated with cognitive models of memory, which predict that images are more likely to be recognized if they are similar to each of the representations in memory. Large scale memory and similarity rating datasets will be used to develop and test the model.Read moreRead less
The Misinformation Future—Confronting Emerging Threats. Misinformation presents challenges to public health and democracy. Though psychological research has explored processing mechanisms and countermeasures, new threats are arising that need to be confronted. This project aims to help meet these threats by (a) investigating misinformation impacts on future-oriented cognition and behaviours, with a focus on global long-term issues and (b) addressing the unique challenges posed by visual and synt ....The Misinformation Future—Confronting Emerging Threats. Misinformation presents challenges to public health and democracy. Though psychological research has explored processing mechanisms and countermeasures, new threats are arising that need to be confronted. This project aims to help meet these threats by (a) investigating misinformation impacts on future-oriented cognition and behaviours, with a focus on global long-term issues and (b) addressing the unique challenges posed by visual and synthetic (AI-generated) misinformation. The expected outcome is new knowledge on the processing and impacts of emerging types of misinformation and translation into practical interventions. These promise to benefit consumers, educators and policymakers, contributing to a healthier information environment.Read moreRead less
Australian Laureate Fellowships - Grant ID: FL220100061
Funder
Australian Research Council
Funding Amount
$3,147,256.00
Summary
Literacy in adolescence: The next major challenge in the science of reading. This project aims to address the pressing problem of why Australian secondary school children have been declining in literacy. To do so is crucial, since adolescence is a period when strong literacy is critical for knowledge acquisition and preparation for adult life. The project will use a range of theoretically-informed methods to scrutinise cognitive processes in adolescent reading, as well as identify interactions b ....Literacy in adolescence: The next major challenge in the science of reading. This project aims to address the pressing problem of why Australian secondary school children have been declining in literacy. To do so is crucial, since adolescence is a period when strong literacy is critical for knowledge acquisition and preparation for adult life. The project will use a range of theoretically-informed methods to scrutinise cognitive processes in adolescent reading, as well as identify interactions between reading progress and socio-emotional functioning and motivation. Expected outcomes will be the first comprehensive account of secondary school reading acquisition and new insights into how to optimise progress. These will inform research, policy, and reading instruction practice, to the benefit of Australia's children.Read moreRead less
Bridging the meaning gap: A computational approach to semantic variation. This project aims to create and validate a new class of large language models that capture and partially explain semantic variation between people. We will (1) measure nuanced differences in word meaning and linguistic experience across individuals; (2) develop computational models that incorporate this variation; and (3) evaluate the extent to which the models capture behavioural and cognitive differences related to polit ....Bridging the meaning gap: A computational approach to semantic variation. This project aims to create and validate a new class of large language models that capture and partially explain semantic variation between people. We will (1) measure nuanced differences in word meaning and linguistic experience across individuals; (2) develop computational models that incorporate this variation; and (3) evaluate the extent to which the models capture behavioural and cognitive differences related to political affiliation, gender, and culture. This will advance our understanding of the nature and origin of individual differences as well as improve the calibration of AI systems for under-represented groups. These advances will support eventual applied outcomes in health, domestic security, and resilience to misinformation. Read moreRead less