QUT offers a diverse range of student topics for Honours, Masters and PhD study. Search to find a topic that interests you or propose your own research topic to a prospective QUT supervisor. You may also ask a prospective supervisor to help you identify or refine a research topic.
Found 650 matching student topics
Displaying 193–204 of 650 results
Reconciling competing perspectives of mathematics in teacher education
This project explores how pre-service teachers experience and reconcile competing conceptions of mathematics, such as mathematics as a formal discipline versus a pedagogical practice. These tensions can shape teaching approaches and classroom environments.The project will investigate how teacher education programs influence these perspectives and how pre-service teachers develop coherent professional identities.
- Study level
- PhD
- Faculty
- Faculty of Creative Industries, Education and Social Justice
- School
- School of Education
AI, data, and mathematical thinking in education
This project explores how emerging technologies, including artificial intelligence, influence mathematical thinking, teaching, and learning. It focuses on how students and teachers engage with data-rich and AI-supported environments.The project aligns with ongoing work in quantitative reasoning, modelling, and educational innovation, including research on adaptive learning technologies.
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Creative Industries, Education and Social Justice
- School
- School of Education
Mathematics Teacher Education Across the Primary–Secondary Continuum
This project examines how mathematics teacher education develops across primary and secondary contexts, focusing on curriculum, pedagogy, reasoning, and assessment.The project builds on current research examining how teacher education is designed differently across contexts and schooling levels.
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Creative Industries, Education and Social Justice
- School
- School of Education
Developing teacher capability in statistical reasoning and modelling
This project investigates how teachers develop confidence and capability in teaching statistics, probability, and modelling. It focuses on strengthening pedagogical and content knowledge in complex mathematical domains.This project builds on extensive experience in pre-service teacher education and research on strengthening statistical reasoning and conceptual understanding.
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Creative Industries, Education and Social Justice
- School
- School of Education
Bridging Real-World Modelling and Secondary Mathematics Education
This project explores how authentic modelling approaches (for example Bayesian reasoning and systems thinking) can be integrated into secondary mathematics classrooms to enhance engagement and conceptual understanding.
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Creative Industries, Education and Social Justice
- School
- School of Education
Modelling educational equity and access pathways
This project examines how pathways of disadvantage and success develop across schooling. It focuses on identifying how socio-economic, wellbeing, and contextual factors interact over time to shape outcomes.This project extends ongoing research into student engagement trajectories and aligns with faculty priorities in inclusive and socially just education.
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Creative Industries, Education and Social Justice
- School
- School of Education
Data-informed decision-making in education systems
This project explores how advanced statistical modelling can support decision-making in complex education systems. It focuses on modelling uncertainty, interdependencies, and policy-relevant insights to guide planning and practice.The project aligns with research applying Bayesian networks to real world decision-making under uncertainty across infrastructure, health, and education contexts
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Creative Industries, Education and Social Justice
- School
- School of Education
Modelling student engagement and success using Bayesian networks
This PhD project investigates how academic, wellbeing, family, and school-context factors interact to shape student engagement, retention, and academic success in secondary schooling. Using large-scale longitudinal datasets, the project will develop advanced probabilistic models to identify key predictors and pathways that explain diverse learner trajectories.The research will contribute to evidence-based strategies for improving student engagement and reducing attrition, with strong relevance to policy and practice in Australian and international contexts.This project builds on ongoing work applying advanced statistical modelling to …
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Creative Industries, Education and Social Justice
- School
- School of Education
Machine learning for power quality analysis in low-voltage distribution Networks
Two full PhD scholarships are available at Queensland University of Technology (QUT), Brisbane, Australia, focusing on machine learning for power quality analysis in low-voltage distribution networks.These PhD projects are part of an Industrial Transformation Training Centre (ITTC), providing students with access to a strong interdisciplinary research environment and collaboration opportunities with leading academic researchers and industry partners.The projects will investigate how solar inverters and electric vehicle (EV) chargers affect harmonic distortion, impedance, and resonance behaviour in the 2–9 kHz range. …
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Electrical Engineering and Robotics
Smart triggered sampling: low-cost devices and intelligent retrofits for capturing the moments that matter
Many water quality issues are event-driven. The most informative signals often appear during short windows associated with storms, illicit discharges, first flush, or operational upsets. Capturing these windows is genuinely hard. Manual sampling is often too slow, especially overnight or during fast-changing events. Conventional autosamplers help, but they are large, power-hungry, and typically deployed only at major assets, leaving smaller drains, tributaries, pump stations, and pollution hotspots without coverage. Even when an event is captured, fixed-interval sampling fills bottles after …
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Civil and Environmental Engineering
See it without touching it: low-cost non-contact sensing for our waterways
Many of our most important waterbodies, including reservoirs, lakes, lagoons, wetlands, sedimentation basins, and constructed wetlands, are still monitored using sparse in-water sensors and periodic grab sampling. These methods are costly to maintain, hard to scale across many sites, and often miss spatially variable changes in water quality.Non-contact sensing offers a different approach. Cameras, spectral sensors, radar, thermal imaging, and other sensing modalities can observe water from outside it, reducing fouling, simplifying servicing, improving worker safety, and enabling broader spatial …
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Civil and Environmental Engineering
Rapid pathogen detection in water: from lab prototype to field-ready public health tool
Faecal contamination is one of the most consequential water hazards because it directly affects public health. Beach closures, do-not-drink advisories, and waterway warnings all depend on detecting microbial contamination quickly and reliably. Today, monitoring still depends largely on infrequent sampling and laboratory turnaround times that arrive long after the contamination has come and gone.Direct microbial sensing has advanced through biosensors and microfluidics, but most concepts remain at low technology readiness and are rarely demonstrated as field-usable systems. Reliability in the …
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Civil and Environmental Engineering
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