The Centre for Applied Research in engineering and computing Education (CARE) at the University of Sydney is committed to driving rapid, research-informed improvements in engineering and computing education.
We focus on solving the Faculty鈥檚 most pressing educational challenges, ensuring strong student learning outcomes while maintaining a high-quality student experience. Our work is anchored in rigorous scholarship, prioritising initiatives that deliver meaningful and scalable impact.聽
_self
h2
Find out more
cmp-call-to-action--ochre
Centre for Applied Research in engineering and computing Education (CARE)聽envisions a future where the University of Sydney Faculty of Engineering is a world-leader in personalised learning at scale. We are internationally recognised for developing innovative approaches that are grounded in, and contribute to, educational scholarship, and which enable educators to focus on individual student needs while maintaining scalability and efficiency.
Our approaches will be known for leveraging advanced learning analytics, artificial intelligence (AI)-driven adaptive systems, and evidence-based pedagogical strategies, to empower our educators to deliver customised learning experiences that enhance student engagement, retention, and skill development.聽
The Centre for Applied Research in engineering and computing Education (CARE) at the University of Sydney is committed to driving rapid, research-informed improvements in engineering and computing education. We focus on solving the Faculty鈥檚 most pressing educational challenges, ensuring strong student learning outcomes while maintaining a high-quality student experience. Our work is anchored in rigorous scholarship, prioritising initiatives that deliver meaningful and scalable impact.聽聽聽
CARE serves as a central hub for educational research, innovation, and evaluation, fostering a scholarly community of practice for academic and professional staff. We actively build capacity and capability, particularly among education-focused staff, while supporting all who are committed to advancing teaching and learning. Through applied research, we identify and address barriers to excellence in educating the next generation of engineers and computing professionals.聽
We leverage existing scholarly practices in educational innovation and lead evidence-based approaches for communicating, engaging with, and motivating students. By collaborating across disciplines and engaging with global best practices, CARE ensures that the Faculty remains at the forefront of engineering education. We take leadership in sharing our insights internationally, shaping the future of personalised learning at scale and strengthening the University鈥檚 global impact in education.聽
The Faculty of Engineering has recognised the need to significantly enhance the quality of its educational offerings, and has built this into a range of initiatives within its new strategic plan.
One of these initiatives 鈥 the development of this Centre 鈥 will focus in two key areas:
A core element in achieving high learning outcomes and an outstanding student experience is having every student feel individually supported. Whilst many institutions have achieved this with small numbers of students, a key challenge is to understand how this can be achieved at scale. Addressing and leading in this challenge is core to the Faculty鈥檚 educational strategy.
Within this context, the Centre will:聽
Our actions and outputs will be underpinned by evidence and their impact will be tracked and monitored over time. We will embrace calculated risks in exploring educational innovations and navigate setbacks with support from our leaders. We will evaluate our progress and learn from our mistakes. As a centre for experimentation, innovation and shared learning, the centre will support continuity and sustainability of innovations and drive adoption of innovation across the faculty.聽
The Faculty of Engineering has a range of projects being worked on simultaneously, broken down into 3 key areas.
Our Experts: Dr , A/Prof , Dr , Mr Thomas Elton, Mr Peter Lok, Mr Sebastian Kobler
Generative AI (genAI) technologies are changing the nature of the core competencies and skills that future engineers will need to help them succeed in their careers. Programming is a core skill and critical component of current engineering curricula that is relevant to a large variety of modern engineering work and is particularly sensitive to disruption by advances in genAI technologies.
This research project will seek to map how the core competencies needed by engineers in programming and computational thinking are changing in a post-genAI world. The study will examine the perspectives of educators, industry and employers, graduate engineers and current students, and will provide new competency frameworks that inform the adaptation and evolution of introductory computing curriculums for future engineering students.
Our Experts: Dr , Prof Mary , Dr Elliot Varoy
This project aims to identify ways in which a human educator supported by NLP tools can achieve outcomes that are not possible to achieve by either humans or tools alone. This project expects to generate new knowledge in the area of natural language processing using innovative approaches for conversation-level analysis and interpretability of classification and clustering decisions. Expected outcomes of this project include new models, systems, and datasets for artificial intelligence research in the education domain. This should provide significant benefits, such as robust assessment of student learning outcomes, educator understanding of student learning patterns, and new ways to measure progress of artificial intelligence models.
Our Experts: Dr , Prof , Mr Hisham Akhtar, Mr Thomas Elton, and Mr Jacob Elmasry
As generative AI tools become embedded in everyday student life, universities face an urgent question: how can we ensure students use these technologies ethically, effectively, and in ways that genuinely enhance learning?
This project investigates how engineering students are adopting and integrating generative AI into their studies. It explores how often students use AI and for what purposes, such as learning support, assessment preparation, skill development, or convenience. It also investigates whether and how this use contributes to meaningful learning outcomes.
Our Experts: Dr Elliot Varoy, Dr Nataliia Stratiienko, Dr ,听顿谤 Hazem El-Alfy, Dr , Dr Muhammad Sajjad Akbar, Mr Rafael Franca Dutra, Mr Ross West
Student engagement in the Faculty of Engineering has shown signs of decline across lectures, tutorials, recorded content, online platforms, and academic support sessions. While analytics and staff observations indicate reduced participation, there is limited understanding of how students are engaging across delivery modes, or why they make these choices in a post-COVID learning environment. This project will seek to understand the behavioural engagement patterns evident across teaching modes and what motivates students鈥 participation decisions.
Quantitative analysis of learning analytics will inform a predictive model to identify students at risk of disengagement, enabling earlier and more targeted support. Qualitative interviews, guided by Self-Determination Theory, will examine how autonomy, competence, and relatedness influence participation choices. By integrating behavioural analytics with motivational insight, the project will inform evidence-based decisions about teaching models, resource allocation, and learning design to better support student success.
Our Experts: Dr Mafruha Hossain, Prof , Dr Elliot Varoy, Dr , Dr , Dr Natalia Stratiienko, Ms. Yihong Yuan, Mr Jacob Elmasry
Whilst some students make good choices, this flexibility might lead others to make poor choices. This project thus explores whether, when students are given a choice, they make choices that are beneficial or harmful to their learning.
Our Experts: Dr ,听础/笔谤辞蹿 , Anne Jin
Our Collaborators: Dr Tony Vo (Monash University), Veronica Halupka (Monash University), Dr Emily Cook (Swinburne University of Technology), Dr Shannon Rios (The University of Melbourne), Dr Joshua Burridge (The University of Melbourne), Dr Amy Young (Queensland University of Technology), Dr Amr Omar (University of New South Wales Sydney), Dr Tania Machet, A/Prof Scott Daniel (University of Technology Sydney)
Classroom educators (e.g. tutors, demonstrators) educating students in small-scale classes like tutorials, workshops and labs are a key component of the tertiary engineering education workforce in Australia and Aotearoa New Zealand. Currently, little is documented about the scope and nature of the training and professional development offered to these educators.
This study will work to address this by conducting an online survey of academic and professional staff designing and delivering said training. The study asks questions of what is being taught, to whom, in what ways, working to expand an already-developed community of practice that will collaboratively co-design shared resources around commonly reported training topics.
We are actively seeking collaborators.
Our Experts: A/Prof ,听顿谤 , Dr , Dr
Our Collaborators: Sam Cunningham (Queensland University of Technology), Sarah Dart (Queensland University of Technology), Karen Whelan (University of Technology Sydney) and Anna Lindqvist (University of Technology Sydney)
This project is developing a validated method using LLMs for cluster and sentiment analysis on open-text response data at scale in order to analyse and understand the variance in student expectations over time. The project draws on 10 years of qualitative student feedback data across three Australian Engineering Faculties to determine: How student expectations have shifted over time with respect to their learning experience; variance in expectations across subdisciplines and study levels; and, trends in expectations that will enable us to take a proactive approach to improving student experience.
Our Experts: Dr , Dr , A/Prof , Dr , Mr , Mr Peter Lok
Developing transferable professional skills within technically focused degrees remains a persistent challenge. As such, this project seeks to design, implement, and evaluate experiential learning interventions that will be embedded across several undergraduate units. This initiative integrates project-based learning activities aligned with the Project Management Institute's power-skill framework.
CARE currently has two co-directors who jointly set the direction of the research centre:
CARE has also employed a research fellow to assist the planning and delivery of engineering education projects throughout the faculty:
