The Atypical Learners Research Group focuses on understanding and supporting the learning experiences of children and adolescents with atypical developmental trajectories. Our work addresses a broad spectrum of learning challenges, including neurodevelopmental disabilities, specific learning difficulties, and learning loss resulting from disruptions such as the COVID-19 pandemic.
Guided by principles of inclusivity and innovation, the group explores how tailored interventions, assistive technologies, and inclusive teaching strategies can reduce learning barriers and improve outcomes. Our interdisciplinary team draws on expertise in educational psychology, learning sciences, cognitive psychology, special education, and neuroscience to develop and evaluate evidence-based practices that support meaningful, equitable learning for diverse learners.
We welcome collaboration with educators, researchers, and community partners who share our commitment to inclusive education and advancing learning opportunities for all.
This group explores the use of cutting-edge technologies to enhance human learning and development. Key areas include artificial intelligence (AI), immersive techniques (AR/VR), gamification, learning analytics and educational data mining. It also investigates how technologies such as AI-powered platforms and predictive analytics can optimise learning, workforce development and organisational learning. Research aims to integrate advanced cognitive and neuroscience principles with technology to create personalised, engaging, and impactful learning and development experiences.
Key Research Areas:
Cognitive and Brain-Based Learning Models
Researching advanced cognitive and neuroscience learning principles, and how they can be integrated with advanced learning tools to support deeper learning, problem-solving and critical thinking.
Learning and Development Enhancement through Advanced Technologies and Methods
Investigating how emerging technologies, combined with innovative methods, can enhance learning environments for diverse learners by increasing engagement, personalising learning, and optimising outcomes.
Learning Analytics and Data Mining
Using big data and machine learning techniques to analyse learner performance data, predict learning outcomes and inform data-driven decision-making in learning.
Learning Experience Design (LXD)
Merging design thinking with learning principles to create impactful, learner-centred experiences that are both functional and emotionally engaging.
The CogitoAI Research Group brings together expertise from cognitive science, artificial intelligence (AI), psychology, neuroscience, and computer science to build models that mimic human thought and behaviour. The group focuses on simulating key cognitive processes such as perception, memory, decision-making, learning, and problem-solving through algorithmic representations. By modelling how the mind works in computable terms, CogitoAI aims to deepen the theoretical understanding of cognition while driving innovations in artificial intelligence. Its research contributes to the development of intelligent systems that reflect human-like reasoning and adaptability, shaping the future of AI through human-centred cognitive modelling.
Key Research Areas:
Cognitive Modelling
Developing computational models that simulate human cognitive processes, such as perception, learning, memory, decision-making and problem-solving, to understand and predict human behaviour and improve intelligent systems. Areas of research include but are not limited to cognitive architectures, affective computing, and neuro-cognitive computing.
Data Science in Cognitive Modelling
Employing data science to analyse, optimise and validate cognitive models.
Data-Driven Models
Utilising data-driven models for decision-making and predictive analytics.
AI Research and Development
Investigating advanced AI algorithms and techniques to improve the cognitive capabilities of intelligent systems, enabling them to adapt more effectively to human needs and provide more customised experiences. Quantum computing techniques in AI will be investigated in this research domain.
Adaptive and Personalised Intelligent Systems
Applying cognitive models to build personalised systems that adapt to an individual's cognitive styles and requirements.
This research group is dedicated to advancing the understanding and optimisation of human interaction with a wide range of digital technologies and complex systems. Grounded in the principles of Human Factors and Ergonomics (HFE), we focus on enhancing human well-being, performance, safety, and overall system effectiveness. Our approach is inherently multidisciplinary, drawing on expertise from psychology, social science, computer science, cognitive neuroscience, and the foundational principles of Human-Computer Interaction (HCI). We aim to design, evaluate, and understand how humans engage with and are impacted by digital environments, including digital games, immersive technologies, and AI-driven systems.
Our core research themes encompass:
Human-Centred Design and Evaluation for Well-being and Performance
- Applying Human-Centred Design (HCD) principles ensures that digital systems are developed with user needs, capabilities, and limitations at the forefront, specifically targeting improved well-being and performance outcomes.
- Conducting user-centred Evaluations using rigorous methods to assess the impact of digital interventions and systems on user experience (UX), satisfaction, performance metrics, and desired outcomes.
- Promoting inclusive design ensures that AI and immersive technologies are accessible, usable, and beneficial for diverse populations, including people with disabilities and individuals from varied cultural backgrounds.
- Developing systems that provide personalised experiences, potentially utilising AI, to customise interactions, interventions, and content to individual needs, preferences, and contexts, thereby enhancing personal well-being and performance.
Cognitive and Social Ergonomics in Human-Digital Interaction
- Investigating the cognitive processes and neurological underpinnings involved in Brain and Human Interaction, particularly how users process social cues, emotions, and spatial information in immersive environments to inform the design of more natural and engaging interactions.
- Exploring the design and impact of digital systems on social and emotional experiences, including the potential of immersive technology and games to foster empathy, connection, collaboration, and positive social change.
- Integrating principles of Physical and Cognitive Ergonomics optimises user comfort, minimises workload, reduces fatigue, and enhances performance across various digital interactions, from using standard interfaces to navigating immersive virtual spaces.
- Researching the potential of digital technologies, such as AI and VR, for cognitive enhancement involves exploring their use in improving functions like memory, attention, problem-solving, and learning.
Applications and Design of Digital Games and Immersive Technologies
- Exploring the diverse applications of immersive technologies (AR, MR, VR, XR) across fields such as education, healthcare, training, and entertainment, while identifying opportunities and challenges from a HFE perspective.
- Designing and evaluating gamified experiences that leverage game mechanics, dynamics, and aesthetics in non-game contexts to motivate, engage, and inspire specific behaviours or skill development.
- Utilising digital games and gamification technologies as platforms and tools to encourage positive behaviours and facilitate significant behaviour change through engaging and ergonomically sound interaction design.
Data-Driven Methods and Analytics
- Developing robust research instruments and methodologies grounded in psychology, social science, computer science, and HCI to collect comprehensive and relevant data on human behaviour and system interaction.
- Employing data-driven evaluation through quantitative and qualitative methods, including statistical analysis, data mining, AI models, and predictive analytics, to rigorously assess the effectiveness of interventions and make evidence-based decisions for enhanced user experiences and system design.
- Conducting Digital Game Analytics to utilise in-game data for identifying and predicting patterns and trends in player behaviour, which informs both game design optimisation and provides broader insights into human behaviour within interactive systems.
Ethics of AI and Digital Technologies
- Focusing on the development of ethical guidelines and frameworks for the design, deployment, and use of AI, immersive technologies, and digital games, while considering potential risks such as bias, privacy, manipulation, addiction, and ensuring fairness, transparency, and accountability from a human-centric perspective rooted in HFE principles.
The research group adopts interdisciplinary approaches, both clinical and non-clinical, to advance mental health and resilience through preventive and therapeutic interventions, aiming to wellbeing across diverse populations and contexts.
The group is tailored to meet the unique needs of the human population, considering diverse factors such as age, culture, socioeconomic background and life experiences.
Key research areas:
Design and Development Interventions: Mental Health and Resilience
Tech-Supported Mental Health Innovations
Inclusive and Diverse Community Studies
Digital Age and Character Development
This group focuses on advancing leadership capabilities, competency assessment and talent management to foster individual, team, and organisational growth. Research includes the development of competency frameworks, profiling tools and assessment mechanisms to enhance performance and align with strategic goals. Leadership development emphasises succession planning, high-potential talent identification and the integration of emotional intelligence and agile leadership training. Talent management explores employee engagement, diversity and inclusion, alongside strategies for workforce optimisation. Rooted in HRD principles, the group also investigates methods to maximise human potential, bridging the gap between theory and practice to create sustainable high-performance cultures. In counselling, this area of research emphasizes the preparation, development and professional growth of counsellors.
Key areas of focus include:
Development of competency assessment profiling tailored to organisational needs.
Enhancement of core competencies for employees.
Creation of competency frameworks, assessment tools and feedback mechanisms to optimise
performance.
Alignment of competency profiles with civil service strategic objectives.
Use of AI-driven evaluation systems to improve performance and efficiency.
Role of continuous professional development, performance feedback and targeted training in
fostering a high-performance culture.
Building a more effective and accountable civil service responsive to public needs.
Enhancing leadership competencies and identifying high-potential talent.
Development of competency-based leadership programmes.
Talent management strategies and succession planning practices.
Use of technology in leadership training, including AI-driven talent analytics, virtual
leadership coaching and digital mentorship platforms.
Enhancement of curriculum design and development of Counselling.
Practical application of counselling theories and techniques.
Supervision in counselling in the aspect of counsellor development, ensuring ethical and
effective practice support and guidance.
This group will focus on employees’ performance and wellbeing to support organisational effectiveness, innovation and sustainability. The research emphasises how domains such as employees, employer, work factor, environment, policies and technology drive organisational competitiveness in addressing the future needs of the workforce.
Key Research Areas:
Work-life Balance
Explore the factors, effects and strategies to achieve wellbeing in managing work, family and life to maximise human potential.
-Work-life balance
-Quality of life
-Mental health and well-being
Sustainability and Green Management
Explore the development of green skills, sustainability leadership and strategies to embed sustainability in the workforce practices.
-Designing training programmes for green jobs
Fostering employee engagement in sustainability initiatives
-Developing policies that align with environmental, social and governance (ESG) goals.
-Workforce reskilling for renewable energy sectors
-Promoting circular economy practices in organisations
-Supporting employees through green transitions.
Ageing Workforce
The ageing workforce presents a multifaceted challenge across various industries and societal domains. This domain aims to explore strategies for bridging these gaps, fostering inclusivity, and maintaining organisational and societal competitiveness.
-Technological adaptation in an ageing workforce
-HRD policy frameworks for inclusivity
-Economic and organisational impacts.
