Student retention beyond the compulsory schooling years in rural, regional and disadvantaged communities. This project will incorporate longitudinal mixed-methods study to investigate the factors that influence student retention in schooling beyond the compulsory years in rural, regional and disadvantaged communities. Research outcomes will identify best-practice educational strategies to enhance retention in such communities across Australia.
Improving Regional Low SES Students' Learning and Wellbeing. This study aims to address the learning and wellbeing needs of over 7000 predominantly low socio-economic status students in regional Australia by researching the conditions that enable refinement and extension of a successful curricular and wellbeing program. The current low educational performance of this student cohort has significant negative effects on individual employment prospects and broader national productivity. Their under- ....Improving Regional Low SES Students' Learning and Wellbeing. This study aims to address the learning and wellbeing needs of over 7000 predominantly low socio-economic status students in regional Australia by researching the conditions that enable refinement and extension of a successful curricular and wellbeing program. The current low educational performance of this student cohort has significant negative effects on individual employment prospects and broader national productivity. Their under-achievement and disengagement from schooling also contribute to many antisocial, harmful short-and long-term outcomes for individuals, with significant health and other costs to the broader community. Outcomes from the project have the potential to improve these current outcomes and to be applicable to similar settings.Read moreRead less
Using data mining methods to remove uncertainties in sensor data streams. This project will develop key techniques for removing uncertainties in sensor data streams and thus improve the monitoring quality of sensor networks. The expected outcomes will benefit Australia by enabling improved, lower-cost monitoring of natural resources and management of stock raising.
Discovery Early Career Researcher Award - Grant ID: DE220100265
Funder
Australian Research Council
Funding Amount
$417,000.00
Summary
A closed-loop human–agent learning framework to enhance decision making. This project aims to design a foundational human–agent learning framework to augment the decision making process, using reinforcement and closed-loop mechanisms to enable symbiosis between a human and an artificial-intelligence agent. It envisages significant new technologies to promote controllability and efficient and safe exploration of an environment for decision actions – drastically boosting learning effectiveness and ....A closed-loop human–agent learning framework to enhance decision making. This project aims to design a foundational human–agent learning framework to augment the decision making process, using reinforcement and closed-loop mechanisms to enable symbiosis between a human and an artificial-intelligence agent. It envisages significant new technologies to promote controllability and efficient and safe exploration of an environment for decision actions – drastically boosting learning effectiveness and interpretability in decision making. Expected outcomes will benefit national cybersecurity by improving our understanding of vulnerabilities and threats involving decision actions, and by ensuring that human feedback and evaluations can help prevent catastrophic events in explorations of dynamic and complex environments.Read moreRead less
Building futures for young Australians at risk: a coordinated measurement framework and data archive. This project will build a national data base of evidence about and for programs that address the needs of the 16 per cent of young Australians currently at risk of school non-completion. It will generate important knowledge for program improvement and sustainability and coordination of evidence across diverse and fragmented programs.
Architectural Work Cultures: professional identity, education and wellbeing. This project aims to examine the work and study cultures of architecture in Australia, in relation to professional identity, and in terms of impact on wellbeing, with a whole-of-career scope spanning education to retirement. It will generate the first comprehensive account of work-related wellbeing problems for both architectural practitioners and students, via qualitative and quantitative methods and a vigorous engagem ....Architectural Work Cultures: professional identity, education and wellbeing. This project aims to examine the work and study cultures of architecture in Australia, in relation to professional identity, and in terms of impact on wellbeing, with a whole-of-career scope spanning education to retirement. It will generate the first comprehensive account of work-related wellbeing problems for both architectural practitioners and students, via qualitative and quantitative methods and a vigorous engagement with the profession. Expected outcomes include two toolkits to assist the profession to support cultural change across educational, workplace and institutional settings. This should provide significant benefits for the wellbeing of architects at all career stages, and also support the long-term viability of the sector.Read moreRead less
Visual analytics for massive multivariate networks. Visual analytics for massive multivariate networks. This project aims to create methods to visually analyse massive multivariate networks. The amount of network data available has exploded in recent years: software systems, social networks and biological systems have millions of nodes and billions of edges with multivariate attributes. Their size and complexity makes these data sets hard to exploit. More efficient ways to understand the data ar ....Visual analytics for massive multivariate networks. Visual analytics for massive multivariate networks. This project aims to create methods to visually analyse massive multivariate networks. The amount of network data available has exploded in recent years: software systems, social networks and biological systems have millions of nodes and billions of edges with multivariate attributes. Their size and complexity makes these data sets hard to exploit. More efficient ways to understand the data are needed. This project will design, implement and evaluate visualisation methods for massive multivariate network data sets. This research is expected to be used by Australian software development, biotechnology and security companies to exploit their data.Read moreRead less
School retention through alternative schooling: towards a socially just approach to education. This project is concerned with how mainstream schools may become more socially just and inclusive of all young people through an analysis of alternative schools specifically designed for this purpose. Such a concern is critical for lifting school retention rates of marginalised young people and improving practices in all schools.