Coding: Challenges and Opportunities of AI – the new AI Code Generation?

The Year of 2023 has really been the Year of releases of AI (Artificial Intelligence) models so far. Everywhere people are talking about AI, be it in the public or private sphere of everyday life. Be it chatgpt, the new Bing AI Search Options, or so many more applications and websites where AI has gained attention. 

No wonder that we at Code4SP also thought about how AI might and is already changing Coding. How will it change the present and future Generation who is learning or will learn to code?

We researched and found a paper written by six researchers based in Ireland, USA, and New Zealand. The paper is called “Programming Is Hard – Or at Least It Used to Be: Educational Opportunities and Challenges of AI Code Generation”.  You can access it here: (last access: 30th August 2023).

The paper aims to plant a seed, opening the discussion about AI in the computing education community and addressing the importance of the computing education community acting quickly. Using AI to code is already possible and can be attractive to use. However, these AI tools present multiple opportunities and challenges. Opportunities can be that the AI models in the realm of the computational education community, can be an aid to students, who are learning to code. Challenges can be the appropriate use of those AI tools in the educational training.  The main Opportunities detected by the authors are Code Solutions for Learning, Producing Learning Resources, New Pedagocical Approaches. The main challenges mentioned are: Ethical Issues, Bias and Bad Habits, and Over-reliance. Underneath a table where we put together the Chapters and Subchapters which address the Opportunities and Challenges mentioned in the paper.

Overview of the Opportunities and Challenges mentioned by the authors





Code Solutions for Learning

Ethical Issues

       ·         Exemplar solutions                      

       ·         Variety of solutions

       ·         Code review of solutions

          ·         Academic misconduct

          ·         Attribution

          ·         Code reuse and licensing

          ·         Sustainability (-> consuming a lot of energy to train AI models and to use them)

Producing Learning Resources

Bias and Bad Habits

       ·         Exercise generation 

       ·         Code explanations

       ·         Illustrative examples

         ·         Appropriateness for beginners

         ·         Harmful biases

         ·         Security

New Pedagocical Approaches


       ·         Explaining algorithmic concepts clearly

       ·         Alleviating programmer’s writer’s block

       ·         Overcoming traditional barriers

         ·         Reinforcing behaviors that impede learning

The authors conclude: “We believe AI-generated code coupled with demands from industry will force us to face ethical issues in computing education from the very beginning of the curriculum. Without quick, concerted efforts, educators will lose advantage in helping shape what opportunities come to be, and what challenges will endure – in a landscape that is changing faster than ever.” (p.505).

The Opportunities and Challenges mentioned in the paper in the field of computational educational community, are similar to those Opportunities and Challenges discussed in other fields. Showing even more how important it is to have these kinds of discussions in our society, educational realms, and companies. Only by addressing the opportunities and challenges, discussing them, and finding ways to navigate the new present with AI models, we will be able to find ways which support our communities, societies, and environments. 


Brett A. Becker, Paul Denny, James Finnie-Ansley, Andrew Luxton-Reilly, James Prather, and Eddie Antonio Santos. 2023. Programming Is Hard - Or at Least It Used to Be: Educational Opportunities and Challenges of AI Code Generation. In Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1 (SIGCSE 2023). Association for Computing Machinery, New York, NY, USA, 500–506.