As part of the broader ASC 2025 program, a series of sessions dedicated to statistics and data science education will take place across Thursday and Friday of conference week. On Thursday, statistical education will feature prominently within the main conference program. Friday will be fully dedicated to special sessions organised by the SSA’s Statistics Education Section.

Welcome Message

We invite you to take part in the Statistical Education Sessions at ASC 2025, under the theme Statistics and Data Science Education: Adapting to a Changing World.

These sessions will explore the evolving landscape of statistics and data science education and its growing significance across industry, government, business, and research. As data-driven decision-making becomes increasingly central in all sectors, students—from undergraduate to postgraduate levels—require strong statistical reasoning and applied skills to thrive in a rapidly changing world shaped by post-COVID realities and generative AI technologies.

In addition to technical knowledge, ethical responsibility in data science is vital. Promoting transparent, fair, and responsible data practices is an essential component of modern education. These sessions will highlight the importance of cross-disciplinary collaboration, curriculum design, and aligning educational outcomes with the needs of today’s workforce.

The program will include contributed talks addressing contemporary challenges and innovations in statistics education, and panel discussions examining the intersection of teaching, technology, and practice.

Topics will span approaches to teaching at the introductory and advanced levels, strategies to support postgraduate students and professionals, and methods to foster engagement across diverse learning environments.

Join us for this opportunity to connect with peers and shape the future of statistics and data science education.

Stat Ed Section organised session’s themes are: 

1. Evidence-based teaching and learning practices in statistics and data science education.  

2. Inclusive curriculum design that supports diverse learners and non-traditional students. 

3. Innovative approaches and practices in a post-COVID-19 and Generative AI world.  

4. Teaching probability and statistical thinking in statistics education.  

5. Including employability into the statistics and data science curriculum.  

6. Helping students see the practical value of statistics in their careers.  

7. Ethical data practices in statistics and data science education.  

8. Indigenous perspectives and knowledge in statistics and data science education.