Optimising students’ academic trajectories: The role of growth (‘personal best’) goals. Too many students fail to reach their academic potential and, as a result, they risk being systematically denied a sense of academic ‘success’ and progress. Through a focus on academic growth (and ‘personal bests’), this research project traverses complex terrain to identify the role of growth goals and growth goal setting in students’ academic trajectories. It also tackles methodological challenges that have ....Optimising students’ academic trajectories: The role of growth (‘personal best’) goals. Too many students fail to reach their academic potential and, as a result, they risk being systematically denied a sense of academic ‘success’ and progress. Through a focus on academic growth (and ‘personal bests’), this research project traverses complex terrain to identify the role of growth goals and growth goal setting in students’ academic trajectories. It also tackles methodological challenges that have impeded research progress in this compelling area. Through strategic international and institutional links, the research program will identify innovative approaches to academic growth and growth goals that will significantly assist pedagogy and psychology aimed at optimising students’ academic potential.Read moreRead less
Solving the inert knowledge problem. A central goal of education is for students to transfer what they learn to new contexts or problems. Indeed, expert reasoning is often characterised by seeing the deep structural commonalities across seemingly disparate situations. However, the knowledge students acquire is notoriously inert, tied to the specifics of the learning examples. This project aims to move towards solving 'the inert knowledge problem' by investigating how humans learn concepts define ....Solving the inert knowledge problem. A central goal of education is for students to transfer what they learn to new contexts or problems. Indeed, expert reasoning is often characterised by seeing the deep structural commonalities across seemingly disparate situations. However, the knowledge students acquire is notoriously inert, tied to the specifics of the learning examples. This project aims to move towards solving 'the inert knowledge problem' by investigating how humans learn concepts defined by abstract relational structure, and by designing educational applications that enhance the use of relational learning mechanisms in students with a wide range of cognitive abilities.Read moreRead less
Scalable urban traffic control framework driven by distributed information. This project aims to develop a mathematical framework for investigating the role of information interactions between traffic signal settings and choices made by road users. Traffic control is one of the oldest and most cost-effective solutions for the worsening congestion problem in many metropolitan areas. However, through addressing fundamental mathematical challenges, further gains can be achieved to improve traffic ....Scalable urban traffic control framework driven by distributed information. This project aims to develop a mathematical framework for investigating the role of information interactions between traffic signal settings and choices made by road users. Traffic control is one of the oldest and most cost-effective solutions for the worsening congestion problem in many metropolitan areas. However, through addressing fundamental mathematical challenges, further gains can be achieved to improve traffic control and combat congestion. The expected outcome will be insights into the use of information and algorithms that can provide efficient, robust and safe traffic network management.Read moreRead less
Investigating travel choice behaviour: a new approach. Since large monetary investments are involved in infrastructure decisions, it is of utmost importance that impacts of transport policies can be accurately predicted. The recent failures to forecast usage and revenues of toll tunnels in Australia illustrate this well. This project aims to contribute by producing improved practical behavioural models to predict responses to such transport policies to assist in better decision making. Further, ....Investigating travel choice behaviour: a new approach. Since large monetary investments are involved in infrastructure decisions, it is of utmost importance that impacts of transport policies can be accurately predicted. The recent failures to forecast usage and revenues of toll tunnels in Australia illustrate this well. This project aims to contribute by producing improved practical behavioural models to predict responses to such transport policies to assist in better decision making. Further, the project is expected to make several methodological contributions by for the first time merging methods from stated choice surveys, experimental economics, and naturalistic driving simulators in order to better investigate travel choice behaviour in realistic environments.Read moreRead less
Transforming primary teachers' representational practices: effects on students' scientific reasoning and discourse within contemporary sciences. Training teachers to appropriately represent and communicate scientific information is critically important for promoting scientific thinking and learning in students. This research is critical to securing Australia's future interests in developing new and emerging frontier science and technologies through the engagement and retention of students.
Discrimination learning in humans: Associative and attentional mechanisms. This project offers three major benefits: (1) Australian researchers excel in cognitive neuroscience, learning and psychopharmacology, areas based largely on animal models of human cognition. This project contributes to these areas by specifying the relationship between animal learning and human cognition; (2) the project enhances Australia's international reputation in these areas via its collaboration with a scientist ....Discrimination learning in humans: Associative and attentional mechanisms. This project offers three major benefits: (1) Australian researchers excel in cognitive neuroscience, learning and psychopharmacology, areas based largely on animal models of human cognition. This project contributes to these areas by specifying the relationship between animal learning and human cognition; (2) the project enhances Australia's international reputation in these areas via its collaboration with a scientist of Geoff Hall's stature; it also offers students outstanding research training and international exposure; (3) given Chris Mitchell's industry experience and the relevance of this work to advertising/marketing, this project will generate knowledge relevant to, and possible future collaborations with, Australian industries.Read moreRead less
Evaluating models of category learning that use general feature-based representations. Three competing models of human category learning will be evaluated by comparing their behaviour to human performance on an experimental task where each model makes qualitatively different predictions. A series of theoretical and algorithmic advances will be undertaken to ensure each of the category learning models uses the same feature-based representation. Because the three models propose very different lear ....Evaluating models of category learning that use general feature-based representations. Three competing models of human category learning will be evaluated by comparing their behaviour to human performance on an experimental task where each model makes qualitatively different predictions. A series of theoretical and algorithmic advances will be undertaken to ensure each of the category learning models uses the same feature-based representation. Because the three models propose very different learning processes, their comparison will give insight into the basic cognitive process of categorisation. The algorithms for generating feature representations and modelling human category learning will also have potential for application in data visualisation and information handling systems.Read moreRead less
Hierarchical Bayesian Models for Human Conceptual Learning. This project seeks to understand the nature of human conceptual learning. With the shift to an information-based economy, it becomes important to understand what assumptions a real-world learning system should make. Even given the impressive growth of machine learning and artificial intelligence, the human mind remains the most successful example of such a system. In this light, the scientific study of human conceptual structure present ....Hierarchical Bayesian Models for Human Conceptual Learning. This project seeks to understand the nature of human conceptual learning. With the shift to an information-based economy, it becomes important to understand what assumptions a real-world learning system should make. Even given the impressive growth of machine learning and artificial intelligence, the human mind remains the most successful example of such a system. In this light, the scientific study of human conceptual structure presents the opportunity to discover how an intelligent thinking system should operate. In addition, many important problems facing an information economy involve being able to understand how people behave. An understanding of the concepts people use is central to this endeavour.Read moreRead less
Adaptive Stochastic Dynamic Traffic Assignment. This project aims to address some of the limitations of dynamic transport network modelling in the planning process particularly related to traffic uncertainty, driver adaptivity and information-provision. Previous advances facilitate the proposed methods to introduce; new network routing algorithms that account for numerous increasingly important problem characteristics such as driver route-choice response to real-time information and uncertainty; ....Adaptive Stochastic Dynamic Traffic Assignment. This project aims to address some of the limitations of dynamic transport network modelling in the planning process particularly related to traffic uncertainty, driver adaptivity and information-provision. Previous advances facilitate the proposed methods to introduce; new network routing algorithms that account for numerous increasingly important problem characteristics such as driver route-choice response to real-time information and uncertainty; new formulations for the stochastic dynamic traffic assignment problem which employ the novel routing algorithms as sub-problems; and new methods for relevant bi-level optimisation transport applications such as network design and incident management.Read moreRead less
Advancing future primary teachers' engagement in science inquiry learning. Australia's challenges in regard to scientific literacy and growth of student enrolments in science need to be addressed at multiple levels, starting with the preparation of future primary teachers. Promoting children's early interest in inquiry-based science is essential, yet a challenge for many teachers. This project examines the complex and dynamic interplay of cognitive, metacognitive and emotional processes in futur ....Advancing future primary teachers' engagement in science inquiry learning. Australia's challenges in regard to scientific literacy and growth of student enrolments in science need to be addressed at multiple levels, starting with the preparation of future primary teachers. Promoting children's early interest in inquiry-based science is essential, yet a challenge for many teachers. This project examines the complex and dynamic interplay of cognitive, metacognitive and emotional processes in future primary teachers' engagement in collaborative inquiry-based science activities. A comprehensive intervention based on these insights aims to determine how scaffolding productive engagement can improve the quality of primary teachers' preparation for inquiry-based science.Read moreRead less