Students as Partners in Transforming Statistics Education

Field-specific career survey courses are not present at many institutions, and where they are, they often do not address education level on career implications. In some fields such as medicine, it is well known that being a doctor requires going to medical school and residency, and what that career and salary path looks like. For areas such as mathematics and statistics, the implications of continuing or stopping one's education are not as clearly laid out to students. At some employers, the work you are allowed to perform and political influence you are allowed to wield are dictated by your education level, not just your level of experience. Currently statistics students arrive to the field with a mismatch of education level and goals for their work experience, as they were not advised on the implications of their choices.
A career survey activity was developed, with the goal of exposing undergraduate statistics and data science students to this concept, and therefore helping students align their educational plans with the types of jobs they want to have post-graduation. The project consisted of a pre- and post-survey to measure the efficacy of the activity by assessing changes in student perceptions, with flexibility in how an instructor utilizes class time. With IRB approval, interested instructors were sought to expand this research. In spring 2025 the career survey activity was deployed in a variety of institutions across the US including public and private and large and small, with both large and small undergraduate statistics and data science classes. The resulting changes in student perceptions on career expectations will be shared with the audience. 

Transformations of statistics education can take place on different scales, from modifications to a semester-long course, to redesign of an entire undergraduate or postgraduate programme, to system level changes to Higher Education provision. At each scale it is possible to include the student voice and transform mathematical education in partnership with students. In this paper I will discuss 3 case studies that illustrate student involvement at different scales.
At the national scale, England's Observatory for Mathematical Education recently surveyed 1000 undergraduate students from 65 universities to identify systemic issues which leave students unprepared for learning statistics. At the university scale, the University of Nottingham invited a team of students to co-create its new degree programmes in mathematics and statistics. At the module/course level, I have partnered with students to embed sustainability, group work and communication skills in a module for scientists.
Through these case studies, I will discuss the benefits that staff and students have gained from working in partnership and how this approach could transform statistics education.
 

A Students as Partners approach to a teaching and learning project involves a "collaborative, reciprocal process through which all participants have the opportunity to contribute equally" (Cook-Sather et al., 2014) and is guided by values that require the creation of an environment where students are empowered to participate in a way that ensures this reciprocity and collective responsibility (Healey et al., 2014). Creating such an environment can be especially challenging when the project's area of focus extends beyond students' classroom experiences or addresses a sometimes-contentious matter in higher education. For the practice of Students as Partners to develop into part of our regular practice, some recent literature suggests that it is important to begin interrogating and identifying the areas in which it can be most useful (Casey, 2024). With this in mind, we'll consider two recent Students as Partners projects, one in evaluation of a new statistics program of study and the other in student evaluation of courses, and steps we took to meaningfully engage students as co-creators. Key to each of these projects was a phase of learning together to establish a common basis for our work. We'll share the scaffolded steps we took to create conditions for the faculty, staff, and student partners to collectively build their knowledge and enhance their research skills. An important outcome of this phase was the breaking down of hierarchies and development of the trust necessary for genuine partnership. 

Many statistical classes include projects with scientific write-ups to evaluate different topics (e.g., simulation studies, applied data analyses, reports for collaborators, etc.). Oftentimes these projects are only viewed by the student and the instructor, creating a one-way and limiting dissemination of information. Instead, one can partner with students to create a two-way and broad dissemination of information in the form of a "published" classroom journal. In this presentation we build off of our previous work by focusing on strategies to engage students as partners in the process while noting the real-world skills that can be built through scientific writing, a low stakes setting to experience the process for "publication", and applying classroom concepts to a wide range of settings. 

This talk will highlight five key initiatives at Imperial College London in which students actively contributed to the development of statistics education. These include the Active Learning in Statistics project (2019), empowering students through hands-on learning, and the Engagement in Blended Learning project (2021), investigating student engagement with online resources and transition to blended learning. We'll also discuss the Mathematics Curriculum Mapping Tool project (2024), which delivered resources that help students to make better informed module choices, the MathsWiki project (2021–2024), a collaborative platform for sharing student-created course materials, and a project in collaboration with Nanyang Technological University (NTU Singapore), Crossing Borders: Engaging with Research Papers in Statistics (2025), fostering international student engagement with research in statistics. In this talk, we will share key insights from the projects, and student reflections on their experience.