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
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
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