UBC recognizes the importance of educational leadership in enhancing teaching and learning across the university—not just within individual classrooms, but across programs, departments, and the broader higher education community. This approach emphasizes teaching excellence, curriculum design, and systemic educational improvement as central to UBC’s mission. In the Department of Statistics, faculty members engage in educational leadership by developing Open Educational Resources (OER), contributing to curriculum development, developing and sharing innovative teaching practices, writing papers in pedagogical research, and more.
Recent Highlights
Data Science: A First Introduction (R & Python)
T. Timbers, T. Campbell, M. Lee, J. Ostblom, L. Heagy
Data Science: A First Introduction (CRC Press) is an open-source, freely accessible textbook for teaching data science at the 1st year undergraduate level developed by four faculty in Statistics and one in EOAS at UBC. There are two versions of the book: one each for the R and Python programming languages, the two most popular languages for data science used across academia and industry. The book comes with a set of Jupyter notebook worksheets—one accompanying each chapter—that self-autograde and provide feedback without any additional software necessary. The materials are used for free by over 2,300 students yearly at UBC in the course DSCI 100: Introduction to Data Science.
Girls in Data Science Summer Camp
K. Burak
The Girls in Data Science Summer Camp at UBC is a three-day program held in July for girls and gender minorities in grades 8–12, offering an engaging introduction to data science and statistics. Taking place at UBC’s Vancouver campus from 10 a.m. to 3 p.m. daily, the camp provides hands-on, supportive learning experiences. Participants will explore key topics such as Jupyter and R basics, data wrangling, visualization, statistical concepts, experimental design, and the fundamentals of machine learning.