Mid-Career Industry Fellowships - Grant ID: IM230100702
Funder
Australian Research Council
Funding Amount
$859,472.00
Summary
Optimising sleep, alertness and safety in shift work industries. This project aims to address the impaired alertness, and high risk of workplace errors and accidents that are associated with sleep loss and circadian misalignment during shift work. The project will deliver an innovative industry-driven digital technology to provide automated, customised sleep management strategies to shift workers, and will develop a framework for effective wide-scale deployment of the technology within Australia ....Optimising sleep, alertness and safety in shift work industries. This project aims to address the impaired alertness, and high risk of workplace errors and accidents that are associated with sleep loss and circadian misalignment during shift work. The project will deliver an innovative industry-driven digital technology to provide automated, customised sleep management strategies to shift workers, and will develop a framework for effective wide-scale deployment of the technology within Australian shift working organisations. The project will close the gap in resources currently available to support sleep in shift workers and will reduce the significant burdens of shift work for alertness, productivity and safety.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