The landscape of statistics teaching and learning has been changing dramatically in recent years, with the rise of data science and enrollment growth, advances in machine learning and artificial intelligence, and the widespread adoption of generative AI. This raises important content and pedagogy questions and presents a valuable opportunity for us to re-examine what students truly need to learn and how educators can effectively facilitate their learning. Now is the time to lead, innovate, and shape the future of our discipline through thoughtful curriculum renewal, research, and evidence-based pedagogical practices.
In response to this challenge, the Canadian Journal of Statistics (CJS) is planning a special issue on challenges and opportunities in statistics and data science education. We invite research papers and other forms of scholarly work, such as comprehensive reviews of research and scholarly teaching practice, and position papers from statistics and data science education scholars that offer evidence-based recommendations. Submissions focused on the teaching and learning of statistics or data science at any educational level are encouraged, and authors may submit their work in either English or French. CJS, the official journal of the Statistical Society of Canada, has an international outlook, so this special issue welcomes submissions from educators, practitioners, and researchers around the world.
Authors wishing to contribute original work to this special issue are encouraged to submit an expression of interest using this form (https://forms.gle/uq33iS5Nh5xoQFC2A) by June 15, 2026. Completion of this form is optional but signals the author’s intent to submit a full manuscript, which will be subject to peer review. The expression of interest will be reviewed by the editorial team only to help them understand the proposed topics and review scope and will allow for early feedback; it will not be peer‑reviewed.
The paper submission deadline is October 15, 2026, and publication decisions will be made after the peer review process. Please submit your paper through the CJS submission website (link to the login/registration page below), specifying, at the step labelled Additional Information, that the submission is for the special issue on “Modern Issues in Statistics Education”:
https://authors.wiley.com/journal/CJS
If you need assistance with the submission process or have any other questions, contact the journal manager at cjsassist@ssc.ca. The guest editors for the special issue are Bethany White (University of Toronto) and Léo Belzile (HEC Montréal).