Last update: 2020-11-24

Current Projects

How can we incorporate sociopolitical and ethical thought into CS teaching? (2012 - 2013, 2018 - present)

With Eric Mayhew: what does critical pedagogy mean for a CS context?

With Emma McKay and Inès Moreno: how can we improve computer scientists’ awareness of the connections their work has to the land (e.g. sourcing of the compenents of the machines they use, conflict minerals, environmental effects etc)?

With Anna Ma: how has the history of the ACM’s CS curricula shaped socioethical education (or lack thereof) in undergraduate CS programmes?

With Horatiu Halmaghi: how can we teach science and technology studies (STS) to computer scientists and computer science students?

And presented recently:

  • I gave a talk on “rendering technical” at 4S 2020
  • Horatiu presented at 4S 2019, on an autoethnography of runnning a workshop for CS people about sociopolitical issues

Previously, I participated in an ITiCSE 2012 working group on ‘Computing for Social Good’, focusing on sharing CS1 assignments with social context.

What can a critical disability studies lens show us about computer science education? (2019 - present)

Looking at the relationship between disability, technology, and computer science education. What would a crip technoscience approach to teaching CS look like?

With Michelle Lin: what is the state of ableism in CS education?

With Loreina Chew: how can we improve user interface education for accessibility?


  • I presented at CSA 2019, discussing social theory for understanding “spoonies” (people with chronic fatigue/pain)
  • I presented at 4S 2019 on chronotypes, chronodiversity, and technology

What implications do institutional policies have on who studies CS? (2013 - present)

How do policymakers think about diversity in CS? What policies affect diversity and how? And what kinds of policies should be promoted to effectively improve diversity?

And with Horatiu Halmaghi: what are the sustainability implications of policies to promote access to CS?

What’s been published so far:

Why is participation in computing gendered? (2013 - present)

How can we explain the historical and geographical variances in how computer is gendered?

With Jess Quynh Tran: what insights can queer theory give us for understanding how computing is gendered?

With Hana Darling-Wolf: how is the gendered performance of “passion” involved in the development of a CS identity?

What’s been published so far:

And presented recently:

  • Jess will be presenting their work at 4S 2019

Past Projects

How do machine learning educators understand their practice? (2018 - 2019)

With Lis Sulmont. What pedagogical content knowledge is needed to teach machine learning, parcticularly to people without a CS/math/stats background?

What’s been published so far:

  • An Exploration of Pedagogical Content Knowledge for Teaching Machine Learning to Non-Majors. Elisabeth Sulmont, Elizabeth Patitsas, Jeremy R Cooperstock. SIGCSE 2019. (pdf and slides here)
  • Sulmont, E., Patitsas, E., & Cooperstock, J. R. (2019). What is hard about teaching machine learning to non-majors? Insights from classifying instructors’ learning goals. ACM Transactions on Computing Education (TOCE), 19(4), 1-16. (pdf)

And presented recently:

  • And a talk accepted to 4S 2019 on algorithmic literacy

What affects the develompent of teaching assistants? (2009 - 2011, 2019)

Short answer: social support! Staff meetings and team teaching were beneficial for TAs in their development as educators.

With Pierre Theo Klein, we looked at how to better support tutors at the CS Help Desk.

Do early childhood experiences relate to computing activities later in life? (2017)

I participated in an ITiCSE 2017 working group examining whether adult reports of their early childhood activities correlated with their later engagement in computing.

Are CS grades bimodal? (2013 - 2016)

It’s commonly said that CS grade distributions are bimodal. But are they? Short answer: no. (with Jesse Berlin)

Blog post about our statistical findings. Excitingly, our findings were replicated! You can replicate our statistical analysis of grades distribution with our code too!

Does having students compare and contrast improve student learning? (2012 - 2013)

Short answer: yes! We found that teaching variants of data structures side-by-side, and having students compare and contrast the different data structures led to more student learning than if you present the different data structures sequentially.

How can we better teach digital logic? (2008 - 2012)

How do we make digital logic labs interesting and engaging for students? I was part of a project to redevelop the lab curriculum for the digital logic course at UBC. During the process I surveyed students and TAs about the labs, to evaluate the curriculum changes.

  • Effective Closed Labs in Early CS Courses: Lessons from Eight Terms of Action Research. Elizabeth Patitsas, Steve Wolfman. SIGCSE 2012. (pdf and slides here)
  • Revitalizing Labs: Lessons from 2.5 Years of Iterative Development and Assessment of Digital Logic Labs. Elizabeth Patitsas, Steven Wolfman, Meghan Allen. SIGCSE, March 2011. Also presented at the CWSEI End-of-Year Event, April 2011. (Poster here)
  • Changes in CPSC 121: Toward a Coherent Picture of Computation. Elizabeth Patitsas, Kimberly Voll. CWSEI End-of-Year Event, April 2010. Also presented at UBC Celebrate Learning, June 2010. (Poster here)
  • Circuits and Logic in the Lab. Elizabeth Patitsas, Kimberly Voll, Mark Crowley, Steven Wolfman. Western Canadian Conference on Computing Education, May 2010. (pdf)
  • Revising an Introductory Computer Science Course: Exploratory Labs, Interactive Lectures, and Just-in-Time Teaching. Gwen Echlin, Piam Kiarostami, Elizabeth Patitsas, Steven Wolfman. CWSEI End-of-Year Event, April 2009. (Poster here)