Dagstuhl-Seminar 25311
Generative AI in Programming Education
( 27. Jul – 01. Aug, 2025 )
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Organisatoren
- Brett A. Becker (University College Dublin, IE - in memoriam, † September 30, 2024)
- Michelle Craig (University of Toronto, CA)
- Paul Denny (University of Auckland, NZ)
- Natalie Kiesler (Technische Hochschule Nürnberg, DE)
- James Prather (Abilene Christian University, US)
Kontakt
- Andreas Dolzmann (für wissenschaftliche Fragen)
- Susanne Bach-Bernhard (für administrative Fragen)
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Programm
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Generative AI stands to significantly disrupt education in general and programming education is no exception. In addition, learning to program has several unique requirements and characteristics that require specific approaches. Evidence from the past several decades on how humans learn programming supports the commonly adopted approach of having students write many small programs. Often these are checked, and feedback is provided, by automated assessment tools. However, Generative AI has likely rendered this approach obsolete given that easy-to-use tools are now readily available that can solve introductory computing problems with natural language prompts. At the same time, it is well known that the large language models that power Generative AI tools sometimes provide outputs that are either incorrect or inappropriate for the current understanding of a learner, raising concerns around student over-reliance and poor learning outcomes.
Educators are currently taking a variety of approaches, including ignoring the issue. Generative AI is a nascent, yet very rapidly developing field and new challenges and opportunities arise frequently making it extremely difficult for educators to keep pace with developments. Prototype tools that leverage Generative AI to facilitate learning are appearing, however most have yet to be deployed or adopted at scale. New pedagogical approaches are also emerging to foster the development of new kinds of skills, such as effective prompt creation, and new learning resources such as textbooks are appearing that teach programming hand in hand with Generative AI. Such approaches, however, have not yet been evaluated at scale as the field is developing so rapidly.
This Dagstuhl Seminar aims to bring together experts and stakeholders in Generative AI and computing education to foster collaboration and to chart a way forward as Generative AI continues to improve and proliferate. It is the goal of this seminar to leverage the experience and knowledge of dozens of programming education experts from around the world to form an enduring community of practice. During the Dagstuhl Seminar, we intend to develop strategies for incorporating LLMs into programming education and to rigorously evaluate their use and impact. This seminar will explore the following topics in the context of Generative AI in programming education: accessibility; diversity, equality, and inclusion; resources; introductory programming for computer science majors and non-majors; advanced courses (that use programming); curriculum changes; novel pedagogies, approaches and tools; and industry use and changes that may lead to new learning outcomes. These discussions will be informed by participants’ prior research and address the following objectives:
- Identify current implications of Generative AI on programming education, learning objectives, and curricula.
- Develop recommendations for the pedagogical integration of Generative AI in programming courses.
- Identify and establish interdisciplinary research objectives and questions to investigate Generative AI in programming education.
Creative Commons BY 4.0
Brett A. Becker, Michelle Craig, Paul Denny, and Natalie Kiesler
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- Ibrahim Albluwi
- Imen Azaiz
- Jamie Benario
- Dennis Bouvier
- Claus Brabrand
- Laura E. Brown
- Neil Brown
- Michelle Craig
- Paul Denny
- Rodrigo Duran
- Virginia Grande Castro
- Carolin Hahnel
- Austin Henley
- Earl Huff
- Amanpreet Kapoor
- Majeed Kazemitabaar
- Hieke Keuning
- Natalie Kiesler
- Tobias Kohn
- Dennis Komm
- Juho Leinonen
- Colleen Lewis
- Kevin Lin
- Dominic Lohr
- Andrew James Luxton-Reilly
- Stephen MacNeil
- Leo Porter
- James Prather
- Brent Reeves
- Karen Reid
- Eddie Antonio Santos
- Jaromír Šavelka
- Daniel Schiffner
- Janet Siegmund
- Adish Singla
- David H. Smith IV
- Sven Strickroth
- Claudia Szabo
- Shubbhi Taneja
- Christina Weers
- Michel Wermelinger
- Titus Winters
- Daniel Zingaro
Klassifikation
- Artificial Intelligence
- Computers and Society
- Software Engineering
Schlagworte
- Computer Programming
- Large Language Models
- Generative AI
- Artificial Intelligence
- Computing Education
