Computing and Engineering Sciences Education Research Series (CESER)

SFU School of Computing Science

CESER promotes dialogue around Computing and Engineering Sciences Education Research.

Simon Fraser University

<h2>Embracing the Future: Leveraging Generative AI in Computing Education</h2>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.

<h2>About the Speakers</h2>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 <a href="https://profiles.auckland.ac.nz/p-denny" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">https://profiles.auckland.ac.nz/p-denny</a>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 <a href="https://juholeinonen.com/" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">https://juholeinonen.com/</a>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 <a href="https://www.brettbecker.com/" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">https://www.brettbecker.com/</a>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 <a href="http://jamesprather.com/" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">http://jamesprather.com/</a>

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Computing and Engineering Sciences Education Research Series (CESER)

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Computing and Engineering Sciences Education Research Series (CESER)

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