Firas Moosvi
Lecturer
Academic Information
Though Firas mainly teaches computer science and data science courses now, he is a multidisciplinary educator with a PhD in Physics and broad interests in teaching and learning. In between his bachelor's of science degree and his PhD (both from UBC in physics), he also earned a Masters degree from the University of Toronto in medical biophysics. His research interests fall under three main umbrellas: alternative grading systems (particularly in large STEM classes), scholarship of teaching and learning (SoTL), and learning analytics. Most recently, he is looking at how the field of learning analytics can provide insight to surface and reduce inequities in STEM programs. Firas has a deep appreciation for data visualization, active learning, and open source projects!
Firas is always happy to collaborate on teaching and learning projects - feel free to email me anytime. Firas also frequently takes on students for honours thesis or directed studies projects in data science and scholarship of teaching and learning.
Selected Publications
Moosvi, Firas, and Simon Bates. "Authentic and inclusive (summative) assessments." In Effective Teaching in Large STEM Classes, pp. 5-1. Bristol, UK: IOP Publishing, 2023.
Bates, Simon, and Firas Moosvi. "Effective teaching in large classes; looking through and beyond the COVID-19 pandemic." In Effective Teaching in Large STEM Classes, pp. 12-1. Bristol, UK: IOP Publishing, 2023.
Englund, L., F. Moosvi, and I. Roll. "Interface and interaction design for an online, asynchronous peer instruction tool." Interactive Learning Environments 31, no. 5 (2023): 2809-2829.
Moosvi, Firas, Giulia Toti, and Elisa Baniassad. "Demystifying Alternative Grading Systems." In Proceedings of the 25th Western Canadian Conference on Computing Education, pp. 1-1. 2023.
Moosvi, Firas, Stefan Reinsberg, and Georg Rieger. "Can a hands-on physics project lab be delivered effectively as a distance lab?" International Review of Research in Open and Distributed Learning 20, no. 1 (2019).
Moosvi, Firas, Dirk Eddelbuettel, Craig Zilles, Steven A. Wolfman, Fraida Fund, Laura K. Alford, and Jonatan Schroeder. "Creating Algorithmically Generated Questions Using a Modern, Open-sourced, Online Platform: PrairieLearn." In Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 2, pp. 1177-1177. 2022.
Research Areas
Interests
- Scholarship of Teaching and Learning
- Alternative Grading Paradigms
- Learning analytics
- Data visualization and science communication
- Computer Science Education research