Expecting the unexpected: how people prioritise predictability. This project aims to investigate how people represent and use information about unpredictability in their environment. Seeing too much predictability is problematic, but seeing too little can also be a problem, for example inappropriate "learned helplessness" can occur, whereby people feel disempowered because the world is seen as random. Recent findings demonstrated a bias in fundamental learning that may maintain these inappropria ....Expecting the unexpected: how people prioritise predictability. This project aims to investigate how people represent and use information about unpredictability in their environment. Seeing too much predictability is problematic, but seeing too little can also be a problem, for example inappropriate "learned helplessness" can occur, whereby people feel disempowered because the world is seen as random. Recent findings demonstrated a bias in fundamental learning that may maintain these inappropriate beliefs about unpredictability. This bias is not anticipated by formal theories of learning. The project will investigate how this bias is brought about by first formalising a novel theory of fundamental learning and then systematically testing its assumptions.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE210100292
Funder
Australian Research Council
Funding Amount
$380,868.00
Summary
From known to unknown: Individual differences in associative generalisation. This project aims to investigate how and why individuals differ in the way that they generalise from past experiences to novel situations. The goal of the project is to develop an innovative and formal model capable of predicting how a given individual will generalise based on their beliefs and personal traits, and to better understand how people behave when there are multiple conflicting ways to generalise. The expecte ....From known to unknown: Individual differences in associative generalisation. This project aims to investigate how and why individuals differ in the way that they generalise from past experiences to novel situations. The goal of the project is to develop an innovative and formal model capable of predicting how a given individual will generalise based on their beliefs and personal traits, and to better understand how people behave when there are multiple conflicting ways to generalise. The expected outcomes of the project are a better understanding and measurement of generalisation, a fundamental psychological process. The outcomes of this project can be used to benefit the development of clinical treatment for anxiety disorders, of which overgeneralisation of fear responses is a defining feature. Read moreRead less
The role of inductive reasoning in generalization of associative learning. This project seeks to develop a better understanding of how learning is generalised to novel stimuli. Learning about associations around us helps us to obtain resources and minimise threat. A critical task for the learner is how far to extrapolate this knowledge: too little generalisation reduces the benefits of learning and too much risks distraction and maladaptive responding. Recent evidence has shown an important role ....The role of inductive reasoning in generalization of associative learning. This project seeks to develop a better understanding of how learning is generalised to novel stimuli. Learning about associations around us helps us to obtain resources and minimise threat. A critical task for the learner is how far to extrapolate this knowledge: too little generalisation reduces the benefits of learning and too much risks distraction and maladaptive responding. Recent evidence has shown an important role for reasoning processes in human associative learning. This project aims to apply insights from the inductive reasoning literature to study the role of hypothesis and category induction in generalisation of associative learning. The results are expected to have important implications for our understanding of associative learning and generalisation which may inform techniques to promote adaptive generalisation in fields such as education, training and clinical practice.Read moreRead less
Creating a climate for change: from cognition to consensus. Climate change is a significant contemporary issue, and communicating the complexities of the terminology and the data is a major modern challenge. This project will apply principles of cognitive and social psychology to determine the most effective methods for promoting an understanding of the scientific dimensions of the issue. The research is significant because it provides a coherent theoretical framework for identifying the psychol ....Creating a climate for change: from cognition to consensus. Climate change is a significant contemporary issue, and communicating the complexities of the terminology and the data is a major modern challenge. This project will apply principles of cognitive and social psychology to determine the most effective methods for promoting an understanding of the scientific dimensions of the issue. The research is significant because it provides a coherent theoretical framework for identifying the psychological mechanisms underlying cognition and commitment at both an individual and collective level. The outcome will be a body of evidence that will inform strategies and policies for communication of complex scientific questions.Read moreRead less
Unifying decisions from experience and description. The project aims to answer an enduring question: are separate theories required for decisions from experience and description? For some decisions, potential outcomes and probabilities are known – a gamble offering a 10 per cent chance to win $100 or a 90 per cent chance of nothing, for example. For many others, there is no ‘look-up table’ of probabilities and outcomes and so we must learn them via experience. Intriguingly, risky choices made on ....Unifying decisions from experience and description. The project aims to answer an enduring question: are separate theories required for decisions from experience and description? For some decisions, potential outcomes and probabilities are known – a gamble offering a 10 per cent chance to win $100 or a 90 per cent chance of nothing, for example. For many others, there is no ‘look-up table’ of probabilities and outcomes and so we must learn them via experience. Intriguingly, risky choices made on the basis of described or experienced information differ markedly. This project examines why this divergence occurs. The project plans to test an innovative approach that unifies both types of decisions into a single theoretical framework and provides a suite of empirical and modelling results.Read moreRead less
Toward a unified account of adaptive decision making: learning to search, stop and decide. The quality of decision making, our own and those with influence over us is a fundamental concern. The centrality of this issue means that it is crucial to understand the cognitive processes underlying human decision making. This project will deliver new insights into these processes and make key recommendations for improving decision making.
How do people make uncertain predictions? Exemplar-based and category-based approaches to inductive inference. This project is an innovative experimental and field study of how people reason under uncertainty. The project will broaden our understanding of human reasoning and enhance the reputation of Australian cognitive science.
When reading takes off: Children's word learning during independent reading. This project aims to address the major unsolved problem of how children build their knowledge about printed words through their reading. This is important since, once children have been taught the basics of reading, the primary means by which they learn new words is through reading experience. The project will use innovative technology to monitor children’s eye movements as they encounter new words during reading, exami ....When reading takes off: Children's word learning during independent reading. This project aims to address the major unsolved problem of how children build their knowledge about printed words through their reading. This is important since, once children have been taught the basics of reading, the primary means by which they learn new words is through reading experience. The project will use innovative technology to monitor children’s eye movements as they encounter new words during reading, examining factors influencing real-time cognitive processing and ongoing learning. Expected outcomes will be new insights into how to optimise children’s word learning when reading, and the refinement of a new computational model. These will inform policy and practice in reading instruction, to the benefit of Australia's children.Read moreRead less
Adapting cognition to a changing climate. Research indicates that public knowledge of the causes and consequences of global warming are poor, and a correct understanding is a key predictor of behaviour that reduces carbon footprints. This project applies basic principles of cognitive science to improve public knowledge and thereby increase the likelihood of reducing carbon footprints.
Beyond reading jumbled words: Bridging perception and language in the Noisy Channel model. Classic computational models of visual word recognition do not consider the noise present in early perceptual processes, and they cannot cope with “jubmled wrods”- words with distorted letter order, unlike skilled readers. Previous work has developed the Noisy Channel model which can recognise such words, modelled as an optimal Bayesian inference process operating on a noisy visual input where there is unc ....Beyond reading jumbled words: Bridging perception and language in the Noisy Channel model. Classic computational models of visual word recognition do not consider the noise present in early perceptual processes, and they cannot cope with “jubmled wrods”- words with distorted letter order, unlike skilled readers. Previous work has developed the Noisy Channel model which can recognise such words, modelled as an optimal Bayesian inference process operating on a noisy visual input where there is uncertainty in the identity and order of letters. In this project, using computational modeling and behavioural experiments, the scope of the Noisy Channel model will be extended to address the role of phonology in the early stages of reading. The outcome will be a better understanding of the link between visual perception and language.Read moreRead less