The Data Analytics in Education program investigates and applies innovative data science methodologies to analysis of individual learning and teaching outcomes using large-scale longitudinal social survey and administrative education data.
Under the leadership of Professor Michele Haynes, research from the Data Analytics in Education program is concerned with modelling trajectories of learning outcomes and well-being for students and preservice teachers; the impact of learning performance on transitions into the workforce; and identifying the factors that intervene to change the course of a trajectory.
The methodological research from the team addresses advancements in statistical and computational methodologies for dealing with problems associated with large-scale longitudinal education and social data including missing observations, measurement error and integration of data from multiple sources. This area of expertise enables research that uses data for evidence to address the research priorities of improving education transitions, pathways and lifelong learning for diverse learners.
The Data Analytics in Education program is linked and provides expertise to the Research Centre for Digital Data in Education and Assessment at ACU.
The Data Analytics in Education team are experts in the fields of statistical methodology, longitudinal data analysis, administrative data analysis, survey methods, and data analytics for education research.
This project examines the evidence from administrative data on the factors that impact on long term achievement and retention for students with autism spectrum disorder in Queensland government schools.
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