Emerging Trends in Statistics Education from 2017-2022 – What next?

Presented at: 25 September 2023; 20:00 UTC

Webinar duration: 90 minutes

Presenter(s): Maxine Pfannkuch, Gail Burrill

Based on input from an expert group of statistics education researchers, a review of articles related to statistics education research between 2017 and 2022, recently published in ZDM -Mathematics Education, identified four themes that seem to capture recent trends and directions: Data Science, Visibilizing Statistical Concepts, Social Statistics, and New Contexts for Learning. The review highlights publications that elaborate on these themes or aspects of these themes, selected because they challenged current thinking about what should be taught or suggested new ways of thinking about the teaching and learning of statistics. The session will include a discussion of the research needed to inform curricula in the next five years based on the four trends we have identified. Some avenues for future research are suggested in the paper, and the session will consider the continued implications of the ever-increasing capacity of technology and new research that has emerged since the papers in the review were written. Recognizing these trends is of importance to not only those who teach statistics but also to those who prepare those who will teach statistics. The demands of this data driven world make it an imperative that our education systems pivot to meeting the needs of those who live and work in such a world.

Webinar video

Gail slides

Maxine slides


Currently an Academic Specialist in the Program for Mathematics Education at Michigan State University, Gail Burrill, was a secondary mathematics teacher in Wisconsin and was awarded the Presidential Award for Teaching Mathematics. She served as President of the National Council of Teachers of Mathematics, President of the International Association for Statistical Education and is President of the Council of Presidential Awardees in Mathematics. She is an elected member of the International Statistics Institute. Her research interests are statistics education, the use of technology in teaching mathematics and statistics, and professional development for teachers.

Maxine Pfannkuch is an Honorary Associate Professor in the Department of Statistics at Auckland University, New Zealand. Before completing her PhD in 1999 on characterizing statistical thinking, she worked as a secondary mathematics teacher and in pre-service and in-service teacher development. Her research interests centered on enhancing 11-to-20-year-old students’ statistical and probabilistic reasoning and statistical literacy, as well as conceptual understanding using dynamic visualizations. She was Editor of SERJ (2014-2018).