Prompts First, Precision Later: Reviving the Vision of Natural Language Programming for Computing Education
Generative AI (GenAI) is disrupting Computer Science Education, proving to be increasingly capable at more and more challenges. Although some educators consider this a threat to computing education, we argue that the move towards natural language was inevitable. Since the beginning, our discipline has continually increased the level of abstraction in each new representation. We have progressed from hardware dip switches, through special purpose languages and visual representations like flow charts, all the way now to “natural language” expressions of problems that serve as “prompts” for generating solutions.
Authors
- Claus Brabrand (ORCID: https://orcid.org/0000-0001-5093-5806)
- Paul Denny (ORCID: https://orcid.org/0000-0002-5150-9806)
- Juho Leinonen (ORCID: https://orcid.org/0000-0001-6829-9449)
- Stephen MacNeil (ORCID: https://orcid.org/0000-0003-2781-6619)
- Andrew Luxton-Reilly (ORCID: https://orcid.org/0000-0001-8269-2909)
- James Prather (ORCID: https://orcid.org/0000-0003-2807-6042)
- Brent N. Reeves (ORCID: https://orcid.org/0000-0001-5781-1136)
- Sebastian Mateos Nicolajsen (ORCID: https://orcid.org/0000-0002-3498-0970)
Institutions
- University of Auckland (NZ)
- Abilene Christian University (US)
- IT University of Copenhagen (DK)
- Temple University (US)
- Aalto University (FI)
Publication Details
- Published
- 2025-11-06
- DOI
- https://doi.org/10.1145/3769994.3770039
- Primary Topic
- Teaching and Learning Programming
- Type
- article
- Field-Weighted Citation Impact
- 0.00