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.Now students can finally engage in problem solving via the abstraction level of the "language"with which they have been "problem solving"all their lives. And the arbitrary association of "computer programming"with "English"has finally been broken, thanks to the natural language translation capabilities of large language models. We must adjust our pedagogy to this new era. Similar to how we don't start teaching math by teaching decontextualised math notation, we shouldn't start teaching programming by requiring precise programming language syntax. New learners should start from the highest level of abstraction we have: prompts first.