The Computer-Based Testing Facility (CBTF) aims to solve a key problem in teaching and learning: helping instructors run digital assessments at scale securely and equitably. The easiest way to describe the CBTF is to imagine it as a network-filtered computer lab dedicated to running digital assessments in 50-minute increments throughout the day, invigilated by trained proctors. Students are typically given a multi-day window to write their tests at a time and location convenient for them. With network filtering, centralized invigilation, a distributed exam model, and flexibility for students and instructors, the mission of the CBTF is to spur pedagogical innovation at the university in a broad range of classes, programs, and departments. Though not the initial motivation, recently the CBTF has also been used to maintain exam integrity in the face of modern AI tools, particularly for computer-based exams where any element of programming is needed under controlled environments. This session will be useful for a range of people including faculty members teaching courses, administrators, IT staff, grad students as well as anyone with an interest in pedagogy and innovative teaching methods. We’ll also hear about the experience of several Statistics faculty members in using the CBTF in their courses as pilots in previous terms. There will be plenty of time for Q&A and a larger conversation around migration to computer-based testing and different learning technologies. The CBTF currently supports a variety of assessment options including Canvas, PrairieLearn, MTA and others. We will also discuss the advantages and disadvantages of different learning technologies in the CBTF from a pedagogical, logistical, and financial perspective.

To join this seminar virtually, please request Zoom connection details from hr.ops@stat.ubc.ca. 

Building data literacy requires intentional design—both inside and outside the classroom. As statistics educators, we are uniquely positioned to help learners not only analyze data but also communicate, question, and connect with it in meaningful ways. This talk will explore several initiatives that promote inclusive and engaging approaches to developing data literacy across different educational levels.

First, I will discuss a range of outreach activities designed to introduce statistical thinking to elementary and secondary students through play, storytelling, and authentic data contexts. These activities—ranging from constructing visualizations using the Spotify API to exploring sampling methods with geodes and “dinosaur fossils”—have been implemented at events such as Florence Nightingale Day and Pursue STEM. Such initiatives align with calls to cultivate early data literacy and “real-world statistical reasoning” among pre-tertiary learners (Ben-Zvi & Garfield, 2004; Ridgway, 2016).

Second, I will highlight innovations in postsecondary statistics education, focusing on the integration of Universal Design for Learning (UDL) principles (CAST, 2018) in a large third-year course (STA304: Surveys, Sampling, and Observational Data). Through flexible grading, grace period, and generative AI policies, the course design supports diverse learners while maintaining academic rigor. Student feedback illustrates how flexibility can enhance motivation, equity, and engagement—findings that echo recent work on inclusive assessment and learning autonomy in statistics education (Engel, 2017).

Together, these projects demonstrate how flexibility, communication, and creativity can support inclusive data literacy education across age groups. By integrating outreach and UDL-informed teaching, we can expand access to data-driven inquiry and foster a more diverse and data-confident generation of learners.

To join this seminar virtually, please request Zoom connection details from ea@stat.ubc.ca. 

Most universities offer centralized teaching development programs for Teaching Assistants (TAs), but discipline-specific initiatives – particularly in statistics and actuarial science – are often limited or informal. In response to this gap, the Department of Statistics and Actuarial Science at the University of Waterloo launched a comprehensive TA Program in 2023. This initiative encompasses all aspects of graduate teaching assistantships and includes the Foundations for University Teaching in Statistics and Actuarial Science certificate training program.

Developed in collaboration with the university’s Centre for Teaching Excellence, our program provides structured, sequential training tailored to the unique demands of statistics and actuarial science courses. It equips incoming and current graduate TAs with the skills needed to confidently and effectively fulfill their roles, including proctoring, grading, facilitating tutorials, and preparing and delivering lecture content.

In this talk, we will outline the state of our TA training prior to 2023, share the motivations behind the creation of our program, and describe its current structure. We will present data on TA participation, share feedback from past trainees, and discuss future directions for the program, including its potential adaptation by other departments and institutions.

To join this seminar virtually, please request Zoom connection details from ea@stat.ubc.ca.