Statistics is a tricky subject to teach and learn. Even putting anxiety and computing aside, we are still faced with the challenge of trying to communicate often complex and unintuitive concepts to students. The statistics pedagogy SIG are interested in finding the most effective ways of teaching and learning statistical concepts.

SIG Lead: Hilary Watt, Paul Hewson, Helen Barnett

In recent years, the utilisation of AI in statistics education has seen substantial growth and rapid evolution. This technology is not only expanding but also transforming the landscape, enhancing administrative functions, aiding teachers, and providing support to students. The Artificial Intelligence in Statistics Education Special Interest Group (SIG) aims to delve into the multifaceted role of AI in the administration, teaching, and learning aspects of statistics education. The focus of the group is on researching the potential of using AI in statistical education as well as research on understanding how to use it and research on the consequences of AI in statistical education."

SIG Leads: Chelsi Slotten

Learning isn´t filling in knowledge into students. Learning is an active process of learners constructing knowledge on their own. Instruction needs to support learners in doing so by providing, among other things, conditions, materials, and an atmosphere conducive to learning. But how can that look like in statistics education? How can we apply ideas from other learning sciences to statistics education? Are there ideas or considerations that need to be different for statistics education? How can we deal with active learning the various forms statistics education happens in – from individual consultation with PhDs and researchers to introductory lectures with hundreds of students? In this SIG we want to think through and do research that brings our knowledge about active learning and statistics education together.

SIG Leads: Sarah Rhodes, Ioanna Papatsouma

Up until recently, most undergraduate-level introductory statistics modules on non-specialist degree courses (i.e., outside of, e.g., maths, computing etc.) commonly used SPSS. There has been a recent shift away from SPSS towards using free software, such as JASP and Jamovi and even the command-line-based software, R. This SIG is interested in exploring questions about the educational pros and cons of different statistics software and how to teach and learn them effectively.

SIG Leads: Alyssa Counsell

Statistics anxiety is a hot topic in statistics education. We know that a lot of students seem to have it, but there is little consensus on what causes it, what its impact is, how to reduce it, or even what the construct actually is. The statistics anxiety SIG is interested in trying to answer these questions.

SIG Leads: Letetia Addison, Fareena Alladin 

Statistics education research is fraught with challenges. How can we conduct ethical, ecologically valid, controlled experimental research with our students? How are we measuring often nebulous and ill-defined constructs, such as 'achievement'? What is the impact of siloed literatures developing in different disciplines? Is there a theoretical grounding? The research methods SIG concerns itself with meta-scientific questions such as these. 

SIG Leads: Margaret MacDougall, Paddy O'Connor