We integrate research into child health, education, and digital and social connectedness. Innovating across disciplines, our evidence-based research focuses on the opportunities, risks and innovations provided by digital technologies that can benefit children and their futures.
Explore the Centre of Excellence for the Digital Child website
Mission and priorities
Our vision is for Australian children to be healthy, educated and connected in a digital world.
Technology innovation
Evidence-based research and research dissemination to optimise children's use of digital technology.
Policy development
Policy recommendations to inform policy stakeholders about optimising children's digital experiences.
Educators
Curriculum and pedagogy recommendations to enable child-directed digital learning, participation and enjoyment.
Community stakeholders
We are a global first, focussing on children from birth to eight years of age with a detailed seven-year research program, including a longitudinal family cohort study with 3000 families.
The centre provides guidelines and resources for parents, educators and communities about safe and effective digital practices.
We undertake community and stakeholder engagement through centre activities that include the Children’s Technology Spaces, workshops and conferences, and outreach events.
Partnerships
The Centre is a collective of national and international partners across education, government, business and the community, all working together to achieve a singular vision.
We’re collaborating with a cohort of researchers from Australian universities, led by QUT and including Curtin University, Deakin University, Edith Cowan University, The University of Queensland and University of Wollongong.
Our partnerships with government agencies, technology developers, education sectors, policy makers and community groups will help us incorporate real-world insights and link our research to a wide range of real-world applications.
Research news
10 July
Study raises concerns about AI health-prediction models trained on unreliable datasets
Some AI models designed to predict stroke and diabetes risk may be based on datasets whose origins cannot be verified, according to new research.
6 July
Emotional ups and downs boost engagement but reduce sales in livestream influencer selling
Influencers who frequently switch between emotions during livestreams may attract more likes and comments, but they are likely to sell fewer products, according to new research from QUT.