It-vest Symposium

09.15: Arrival

10.00: Session 1: Opening 

Paul Denny: Five Years of Research in Programming Education – Key Challenges and Opportunities

11.00 Break

11.30: Session 2: Lightning talks I 

Initiatives and experiences from SDU, AAU and AU, incl. student voices

12.30: Lunch

13.20: Session 3: Invited presentations I

Leo Porter: Helping Faculty Integrate AI into CS Education
The advent of GenAI necessitates changes to the CS curriculum and our courses. These changes include updating our assessment practices, tools for supporting students, and the skills we teach.  Given the scale of these changes and the rapid pace of AI advancements, this talk will outline the challenges faculty face when incorporating GenAI into their CS classes. For each challenge, I'll share lessons learned from our introductory programming course at UC San Diego.  Lastly, we'll discuss how the GenAI in CS Education Consortium seeks to help faculty navigate this evolving landscape.

Natalie Kiesler: Students' Engagement with GenAI Tools and their Feedback

Juho Leinonen: Generating Learning Resources with AI
Generative AI can support the creation of teaching materials for computing education, including programming exercises, interactive online textbook content, and lecture slides. Drawing on examples from course development, I will highlight where AI is genuinely helpful, where human expertise remains essential, and how educators can use AI as a drafting and ideation partner without compromising pedagogical quality.

David Smith: Code-generation Based Grading: EiPL and Prompt Problems
The advent of GenAI is shifting the skills we teach novice programmers, with growing emphasis on prompting and code comprehension over writing code from scratch. In this talk, David will describe code-generation-based grading, a mechanism for scalable, formative practice in these skills. It powers two activities: Explain in Plain Language (EiPL), where students describe in natural language what a piece of code does, and Prompt Problems, where students write the prompt that gets a model to produce code matching a set of examples. In both, the student's response is turned into code and run against unit tests, providing immediate feedback. The talk concludes by situating these activities within a broader effort to enable effective formative practice in natural-language programming, particularly forms in which students are empowered to bring their full meaning-making repertoire—all varieties of natural language (not only English), diagramming, and drawing—to bear on programming task.
 

15:00 Break

15.30: Session 4: Lightning talks II 

Initiatives and experiences from SDU, AAU and AU, incl. student voices

16:30 Break

17.00: Session 5: Round table discussions

18.00: Session 6: Wrap-up over a glass of crémant

Presentation of “posters” – one-minute madness

20.00: Dinner 

Times, sessions and speakers are subject to change

09.00: Session 7: Industry voices 

Industry representatives sharing sharing current experiences and expected future practices

10:30 Break

11.00: Session 8: Invited presentations  II 

Arto Hellas: Teaching Software Engineering with Large Language Models

Hieke Keuning: Generative AI for Computing Education at UU

Andrew Luxton-Reilly: Assessment Policies and Issues: An Associate Dean Perspective
Generative AI has fundamentally altered the education landscape, impacting most immediately on assessment. Our practices and policies must necessarily adapt. This talk explores the issues from an institutional perspective.

James Prather: A Vision of the Future of Computing Education
Generative AI (GenAI) has drastically changed the software engineering industry in just three years. We know our curriculum must change to incorporate GenAI, but the details are unclear. What should we start teaching? What should we stop teaching? Some initial approaches have continued the previous paradigm with GenAI on top. These do not go far enough as the field itself has moved into an entirely new paradigm. In this talk, I will present a new vision for Computing Education that focuses on three big ideas: a new introductory course, a new model for learning programming fundamentals, and a new approach to software engineering courses.

12.40: Lunch

13.30: Session 9: The future of computing education (panel) 

Discussion of challenges, opportunities, and joint initiatives

14:30 Break

15.00: Session 10: Ideas for R&D activities and projects 

16.00: The end

Times, sessions and speakers are subject to change