Data Science ARES: Tiffany Timbers

Join us at the Data Science Applied Research and Education Seminar (ARES) with:

Dr. Tiffany Timbers
Assistant Professor of Teaching, Department of Statistics
Co-Director, Master of Data Science Program (Vancouver option)
University of British Columbia

Talk Title: Opinionated practices for teaching reproducibility: motivation, guided instruction and practice

Abstract: In the data science courses at the University of British Columbia, we define data science as the study, development and practice of reproducible and auditable processes to obtain insight from data. While reproducibility is core to our definition, most data science learners enter the field with other aspects of data science in mind, for example predictive modelling, which is often one of the most interesting topic to novices. This fact, along with the highly technical nature of the industry standard reproducibility tools currently employed in data science, present out-of-the gate challenges in teaching reproducibility in the data science classroom. Put simply, students are not as intrinsically motivated to learn this topic, and it is not an easy one for them to learn. What can a data science educator do? Over several iterations of teaching courses focused on reproducible data science tools and workflows, we have found that providing extra motivation, guided instruction and lots of practice are key to effectively teaching this challenging, yet important subject. Here we present examples of how we deeply motivate, effectively guide and provide ample practice opportunities to data science students to effectively engage them in learning about this topic.

Speaker Profile: Tiffany Timbers is an Assistant Professor of Teaching in the Department of Statistics and an Co-Director for the Master of Data Science program (Vancouver Option) at the University of British Columbia (UBC). She received PhD in Neuroscience in 2012 from UBC, following which she held a Banting Postdoctoral Fellowship at Simon Fraser University where her research focused on cell biology & genomics. This postdoctoral research was data intensive and required the application of data science and statistical methodologies. After her research Postdoctoral Fellowship, Tiffany joined the founding team who developed the Master’s of Data Science program at UBC as a Postdoctoral Teaching and Learning Fellow. In 2018, she joined the Statistics Department at UBC in her current role of an Assistant Professor of Teaching. Currently she teaches and develops curriculum around the responsible application of Data Science to solve real-world problems. She has co-authored two open source textbooks, Data Science: A first introduction and Python Packages. The latter is used for one of her favourite courses she teaches – Collaborative Software Development, which focuses on teaching how to create R and Python packages using modern tools and workflows.