Computing and Engineering Sciences Education Research (CESER) series aims to promote dialog and research around Computing and Engineering Sciences Education Research. 


  • We envision CESER to be a catalyst and resource to respond to challenges in Computing and Engineering Sciences Education Research by fostering learning, engagement and discovery at Simon Fraser University (SFU) and beyond.


  • Raise awareness and build a community around educational research in Computing and Engineering Sciences
  • Attract thought-provoking speakers to share their work and their vision for Computing and Engineering Sciences Education
  • Advance discourse and learning around topics, challenges, and opportunities in Computing and Engineering Sciences Education
  • Facilitate opportunities for collaboration
  • Broaden participation and increase student interest in pursuing careers in Computing and Engineering Sciences Education

For enquiries on the CESER series, contact Dr. Diana Cukierman, School of Computing Science or Dr. Tenzin Doleck, Faculty of Education

2023 Computing and Engineering Sciences Education Research Series

Event Date: Monday, June 12, 2023

Time: 2:00 pm - 3:00 pm

Location: SFU Burnaby, TASC1 9204. Panelists will be over zoom and we will host the watch party here at the SFU Burnaby Campus

Speakers: Dr. Paul Denny, Associate Professor, School of Computer Science, University of Auckland, New Zealand. Dr. Juho Leinonen, Postdoctoral Researcher, School of Computer Science, University of Auckland, New Zealand. Dr. Brett Becker, Assistant Professor, School of Computer Science, University College Dublin. Dr. James Prather, Associate Professor, School of Computer Science, Abilene Christian University.                      

Title: Embracing the Future: Leveraging Generative AI in Computing Education

Register for this talk on Eventbrite


Large language models have  the potential to dramatically impact all aspects of education including computing education. These tools pose unknown impacts on teaching and learning including challenges like academic integrity. Despite this, the rising prominence of generative AI such as ChatGPT necessitates a balance between identifying opportunities and mitigating risks. This talk explores current challenges and concrete opportunities for computing educators, including short to medium-term possibilities, and long-term speculations in rethinking computing education. Despite this rapidly changing landscape, we stress the importance of harnessing these technologies to foster positive change in computing classrooms. 


Paul Denny (top left): Paul enjoys exploring how computing students engage with online learning tools, and is particularly interested in how their experience can be impacted through user interface design and tool feedback.  His research interests include developing and evaluating tools for supporting collaborative learning, particularly involving student-generated resources, and exploring the ways that students engage with digital learning environments. For more information on Paul, visit

Juho Leinonen (bottom right): Juho explores how to best support and engage diverse learner populations with educational technology and artificial intelligence. Recently, he has researched the potential opportunities that large language models could provide for introductory programming instructors such as automatically creating personalised exercises, enhancing programming error messages with LLMs, and creating code explanations for students using LLMs. For more information on Juho, visit

Brett Becker (bottom left): Brett is interested in how humans learn to program. He is far from alone in his belief that Generative AI will dramatically change the way programming is taught and learned. He is not sure if he is surprised or not that LLMs have offered yet another parallel between programming and natural languages, in that LLMs have demonstrated similar capabilities in both domains through very similar mechanisms. For more information on Brett, visit

James Prather (top right): James is very interested in human-computer interaction in the domain programming education. Specifically, he investigates how novices learn to code, novice programmer interaction with compiler error messages, and novice programmer metacognition and self-regulation. Recently he has worked on multiple papers on the impact of LLMs on introductory computing education. For more information on James, visit

2022 Computing and Engineering Sciences Education Research Series

Event Date: Tuesday, September 20, 2022

Time:  10:00 am - 11:00 pm

Location: SFU Burnaby, TASC/ ASB Building (TBD)

Speaker: Dr. Amy J. Ko, Professor, The Information School, University of Washington, Seattle.

Title: The Promise and Problems of CS for All


Register for this talk on Eventbrite


Computing has been transformational in nearly every aspect of society — except for one: education. The vast majority of youth, despite often being surrounded by computing devices, the internet, and content created with and for computers, never learn anything about computation. It is a great irony that youth learn about their bodies in biology, chemistry, and physics; their values and communities in social studies and language arts; and their creative capacity in the arts, but almost nothing about the phenomena that connects them so powerfully to friends, family, stories, play, while simultaneously amplifying so many of the harmful forces of inequity and injustice in the world. In this talk, I discuss why primary and secondary education has largely overlooked computing, the role of both research, teaching, service, and activism in bringing computing to education, and the critical role of higher education in catalyzing these changes. Throughout, I discuss my own path from computer scientist to computing education researcher and the many kinds of research I’ve learned to do along the way.


Amy J. Ko is a Professor at the University of Washington Information School and an Adjunct Professor at the Paul G. Allen School of Computer Science and Engineering. She directs the Code & Cognition Lab, where she and her students study CS education, human-computer interaction, and humanity's individual and collective struggle to understand computing and harness it for creativity, equity, and justice. Her earliest work included techniques for automatically answering questions about program behavior to support debugging, program understanding, and reuse. Her later work studied interactions between developers and users, and techniques for web scale aggregation of user intent through help systems; she co-founded AnswerDash to commercialize these ideas. Her latest work investigates effective, equitable, and inclusive ways for humanity to learn computing, especially how data, algorithms, APIs, and AI can both empower and oppress. Her work spans more than 140 peer-reviewed publications, with 13 receiving best paper awards and 4 receiving most influential paper awards. She is an ACM Senior Member, a member of ACM SIGCHI, SIGCSE, and SIGSOFT, and a member of the SIGCHI Academy, for her substantial contributions to the field of human-computer interaction. She received her Ph.D. at the Human-Computer Interaction Institute at Carnegie Mellon University in 2008, and degrees in Computer Science and Psychology with Honors from Oregon State University in 2002.