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Improving Computer Science Education
Members of our lab are continually conducting research in innovative curriculum and pedagogy for Computer Science, with a particular interest in how to support underserved populations in the field. Areas of investigation have included:
- Flipped Classrooms: to have students consume informational content outside of class, typically through short video lectures, and then have students participate in active learning activities in class (replacing the lecture time) where the students can get help applying the content to problem sets from peers, TAs and professors.
- Lightweight Teams: a small team of students assigned to work with each other all semester long, in a fixed seating plan, but who only work together in the classroom on low-stakes activities that have little or no impact on final grades.
- Code-Diagram Queries (CDQs): diagrammatic questions that probe a student mental models of code execution for a programming language and how it interacts with a computer.
- Two-Stage Exams: a relatively new format of high-stakes assessment in which students write an exam individually, and after the individual portion is complete and students submit their exams, they are then placed into groups and retake the same (or a very similar) exam as a group.
Project Publications
Using a Two-Stage Final Exam in an Intro CS Course: Student Perceptions and Grade Impacts
Celine Latulipe and Lauren Himbeault. 2023. Using a Two-Stage Final Exam in an Intro CS Course: Student Perceptions and Grade Impacts. In Western Canadian Conference on Computing Education (WCCCE ’23), May 4–5, 2023, Vancouver, BC, Canada. ACM, New York, NY, USA, 2 pages. https://doi.org/ 10.1145/3593342.3593355
Comparing Student Experiences of Collaborative Learning in Synchronous CS1 Classes in Gather.Town vs
Celine Latulipe and Amy De Jaeger. 2022. Comparing Student Experiences of Collaborative Learning in Synchronous CS1 Classes in Gather.Town vs. Zoom. In Proceedings of the 53rd ACM Technical Symposium on Computer Science Education V. 1 (SIGCSE 2022). Association for Computing Machinery, New York, NY, USA, 411–417.
Using Discrimination Response Ideation to Uncover Student Attitudes about Diversity and Inclusion in
Lina Lee, Celine E Latulipe, and Tonya K. Frevert. 2022. Using Discrimination Response Ideation to Uncover Student Attitudes about Diversity and Inclusion in Computer Science. (August 2022).