Understanding Growth in Emotion Regulatory Flexibility in Emerging Adults. Emerging adults (ages 18-25) are now facing unparalleled social and technological change and the on-going effects of the COVID-19 pandemic. Such demands can be overwhelming and undermine engagement with education and employment, with serious impacts for the individual and society. At the same time, our novel model proposes that the diverse daily adult-like stressors that characterise emerging adulthood can also drive grow ....Understanding Growth in Emotion Regulatory Flexibility in Emerging Adults. Emerging adults (ages 18-25) are now facing unparalleled social and technological change and the on-going effects of the COVID-19 pandemic. Such demands can be overwhelming and undermine engagement with education and employment, with serious impacts for the individual and society. At the same time, our novel model proposes that the diverse daily adult-like stressors that characterise emerging adulthood can also drive growth in flexible emotion regulation when combined with reflection on, and insight into, their own coping processes. Our research expands scientific knowledge by taking the first steps to uncover why some emerging adults increase their ability to flexibly regulate their emotions over this period, whereas others fail to do so.Read moreRead less
From me to you and beyond: understanding socially-induced nocebo effects. Nocebo effects – when negative expectancies trigger adverse outcomes – cause enormous personal and societal harm. We have made great progress understanding how instruction and conditioning contribute to nocebo effects. Yet, the role of social learning – what we learn by observing others – has received surprisingly little attention despite its relevance to many prominent societal-level nocebo effects. The current project us ....From me to you and beyond: understanding socially-induced nocebo effects. Nocebo effects – when negative expectancies trigger adverse outcomes – cause enormous personal and societal harm. We have made great progress understanding how instruction and conditioning contribute to nocebo effects. Yet, the role of social learning – what we learn by observing others – has received surprisingly little attention despite its relevance to many prominent societal-level nocebo effects. The current project uses novel experimental methods to understand how social learning contributes to nocebo effects and which strategies inhibit these effects. The results will significantly advance scientific understanding of socially-induced nocebo effects and pave the way for translational research to reduce the substantial harm they cause.Read moreRead less
Using AI to reveal the true extent & context of alcohol exposure in videos. This project aims to extend an artificial intelligence algorithm to automatically identify and quantify alcohol prevalence in videos. The project is expected to generate significant new knowledge about alcohol’s exposure in these videos’ social, emotional, and environmental contexts. The expected outcomes include a more efficient and automated method of revealing alcohol pervasiveness and its context in the 1000 most wat ....Using AI to reveal the true extent & context of alcohol exposure in videos. This project aims to extend an artificial intelligence algorithm to automatically identify and quantify alcohol prevalence in videos. The project is expected to generate significant new knowledge about alcohol’s exposure in these videos’ social, emotional, and environmental contexts. The expected outcomes include a more efficient and automated method of revealing alcohol pervasiveness and its context in the 1000 most watched videos in Australia, making costly manual coding redundant. Anticipated benefits include enabling governments to better monitor compliance to alcohol product placement guidelines and increased public awareness of the frequency and harmful effects of being exposed to alcohol in videos.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
Discovery Early Career Researcher Award - Grant ID: DE230100171
Funder
Australian Research Council
Funding Amount
$438,560.00
Summary
Integrated models of learning and decision making in complex tasks. How do people learn to make decisions in complex work systems when assisted by automation? This project will develop computational models of human learning and decision making that explain and predict complex decisions relevant to industries such as aviation and defence. It will examine how humans learn to use automated advice, how learning affects remembering to perform planned (deferred) actions, and factors that pose a risk t ....Integrated models of learning and decision making in complex tasks. How do people learn to make decisions in complex work systems when assisted by automation? This project will develop computational models of human learning and decision making that explain and predict complex decisions relevant to industries such as aviation and defence. It will examine how humans learn to use automated advice, how learning affects remembering to perform planned (deferred) actions, and factors that pose a risk to learning and adaptation. The expected outcome is a significant theoretical advance in human factors and cognitive psychology, and a tool for informing work design (e.g., computer interface, task allocation) and training, with the potential to reduce human error in safety-critical workplaces.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
A statistical decision theory of cognitive capacity. This project aims to investigate the limited capacity of the human cognitive system to form representations of the things in the world around us and to make decisions about them in real time. Its goal is to provide an integrated theory of cognitive capacity based on the statistical properties of cognitive representations and the decision processes that act on them. Its expected outcome will be a unified metric for cognitive capacity that will ....A statistical decision theory of cognitive capacity. This project aims to investigate the limited capacity of the human cognitive system to form representations of the things in the world around us and to make decisions about them in real time. Its goal is to provide an integrated theory of cognitive capacity based on the statistical properties of cognitive representations and the decision processes that act on them. Its expected outcome will be a unified metric for cognitive capacity that will allow us to quantify how cognitive load affects the speed and accuracy of decision making. It will benefit the design and evaluation of high workload real-time decision systems and will contribute to the selection and training of users of such systems.
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Human Scheduling of Perceptual Tasks. This project aims to develop a novel approach for synthesising how people prioritise information with theories of attention and decision making. Characterising inefficient scheduling in the tradeoff between the difficulty and the cost/benefit of different subtasks will allow the development of a formal computional model that generalises statistical models of rank order data to a theory of the timing of scheduling decisions and task completions. Outcomes incl ....Human Scheduling of Perceptual Tasks. This project aims to develop a novel approach for synthesising how people prioritise information with theories of attention and decision making. Characterising inefficient scheduling in the tradeoff between the difficulty and the cost/benefit of different subtasks will allow the development of a formal computional model that generalises statistical models of rank order data to a theory of the timing of scheduling decisions and task completions. Outcomes include benchmark data from a novel paradigm for studying perceptual decisions and behavior and a model which can explain and predict human scheduling. This project aims to benefit industry by allowing for the simulation of information prioritisation by human agents in complex environments.Read moreRead less
Can the Relational Account predict search in multiple-element displays? . This project provides evidence of a novel mechanism that guides visual attention. Our results confirm the existence of a mechanism that can rapidly and automatically assess the dominant feature(s) in a visual scene and radically change how attention is tuned to a target object. Moreover, this attention-guiding target template can change systematically as observers search through different items in visual search, possibly d ....Can the Relational Account predict search in multiple-element displays? . This project provides evidence of a novel mechanism that guides visual attention. Our results confirm the existence of a mechanism that can rapidly and automatically assess the dominant feature(s) in a visual scene and radically change how attention is tuned to a target object. Moreover, this attention-guiding target template can change systematically as observers search through different items in visual search, possibly due to a re-shaping and narrowing of the target template. These are both ground-breaking discoveries that have not been described before. Work on this project promises to lead to important theoretical breakthroughs, resolve current discrepancies in the literature and advance methods of Cognitive Psychology and Neuroscience.Read moreRead less
Enhancing sensory perception and balance control in HMD-based VR. This project seeks to test a revolutionary new theoretical framework for understanding how we perceive our self-motion and maintain postural control when immersed in head-mounted display (HMD) virtual reality (VR). Photorealistic graphical simulations and artificial vestibular stimulation will be used to investigate how visual and non-visual information concerning self-motion is integrated in the brain. The outcomes will reveal ho ....Enhancing sensory perception and balance control in HMD-based VR. This project seeks to test a revolutionary new theoretical framework for understanding how we perceive our self-motion and maintain postural control when immersed in head-mounted display (HMD) virtual reality (VR). Photorealistic graphical simulations and artificial vestibular stimulation will be used to investigate how visual and non-visual information concerning self-motion is integrated in the brain. The outcomes will reveal how multisensory interaction influences our sensory perception and postural control during HMD VR. The knowledge gained is expected to generate new economic benefits by inspiring next-generation technologies that will optimise users' immersive experiences (e.g., virtual exploration and immersive gaming).Read moreRead less