Statistics education research

Data Science

Our research focuses on data science and task design, blending graphic user interface-based (GUI) and code-driven statistical modelling to enhance students’ computational and statistical thinking.

As a New Zealand representative, we lead the International Data Science for Schools Project (IDSSP). This collaboration is developing a curriculum framework in data science education for the last two years of high school.

Meaningful learning in statistics and mathematics

Our history of student learning research covers both school and university settings. Our empirical and theoretical explorations consider student conceptual development and understanding of particular statistics topics across the curriculum and the identification of concepts embedded in statistical thinking and reasoning.

Design of statistical and mathematical resources

This research focuses on practical design, innovation and theoretical task design principles. To enhance teaching and learning in schools and universities, we design practical resources, including dynamic visualisation tools for developing students’ statistical and probabilistic concepts.

Curriculum development in response to changes in the statistics discipline

The statistics discipline is changing rapidly. What are the implications for school and university curricula? How can we support and advocate for change?

By actively pushing the boundaries through empirical and theoretical research, we aim to implement new statistical content, develop new ways of approaching statistics, and build up students’ conceptual infrastructure.

Examples include introducing the empirical enquiry cycle, posing questions, multivariate thinking, informal inference, bootstrapping, randomisation tests and statistical literacy into the school curriculum. 

iNZight
VIT (visual inference tools)
Markov processes
Eikosogram
Pachinkogram