# Generative AI in Computing Education: Perspectives of Students and Instructors

arXiv: https://arxiv.org/abs/2308.04309 · HTML: https://mlsanity.com/paper/2308.04309/

## Key facts

- Cited by 17 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Aug 2023.

## Built on by (most cited first, 17 of 17)

- [The Robots are Here: Navigating the Generative AI Revolution in Computing Education](https://mlsanity.com/paper/2310.00658/) (2023)
- [The Widening Gap: The Benefits and Harms of Generative AI for Novice Programmers](https://mlsanity.com/paper/2405.17739/) (2024)
- [Exploring the Design Space of Cognitive Engagement Techniques with AI-Generated Code for Enhanced Learning](https://mlsanity.com/paper/2410.08922/) (2024)
- [Large Language Models in Computer Science Education: A Systematic Literature Review](https://mlsanity.com/paper/2410.16349/) (2024)
- [Generative AI in Higher Education: Seeing ChatGPT Through Universities' Policies, Resources, and Guidelines](https://mlsanity.com/paper/2312.05235/) (2023)
- [How Novice Programmers Use and Experience ChatGPT when Solving Programming Exercises in an Introductory Course](https://mlsanity.com/paper/2407.20792/) (2024)
- [How Do Programming Students Use Generative AI?](https://mlsanity.com/paper/2501.10091/) (2025)
- ["ChatGPT Is Here to Help, Not to Replace Anybody" -- An Evaluation of Students' Opinions On Integrating ChatGPT In CS Courses](https://mlsanity.com/paper/2404.17443/) (2024)
- ["Like a Nesting Doll": Analyzing Recursion Analogies Generated by CS Students using Large Language Models](https://mlsanity.com/paper/2403.09409/) (2024)
- [Novice Developers' Perspectives on Adopting LLMs for Software Development: A Systematic Literature Review](https://mlsanity.com/paper/2503.07556/) (2025)
- [Coding With AI: From a Reflection on Industrial Practices to Future Computer Science and Software Engineering Education](https://mlsanity.com/paper/2512.23982/) (2025)
- [A Review of Generative AI in Computer Science Education: Challenges and Opportunities in Accuracy, Authenticity, and Assessment](https://mlsanity.com/paper/2507.11543/) (2025)
- [Integrating Generative AI in Hackathons: Opportunities, Challenges, and Educational Implications](https://mlsanity.com/paper/2401.17434/) (2024)
- [Perceived Importance of Cognitive Skills Among Computing Students in the Era of AI](https://mlsanity.com/paper/2604.10730/) (2026)
- [To Tab or Not to Tab: Measuring Critical Engagement in AI Code Completion Tools Using Behavioral Signals and Attention Checks](https://mlsanity.com/paper/2606.30549/) (2026)
- [The Capability Ladder: A Curriculum-Modernization Framework for Workforce Readiness in the AI Era](https://mlsanity.com/paper/2608.07779/) (2026)
- [Cognitive Skills in the Age of AI: Computing Students and Experts Perceptions](https://mlsanity.com/paper/2609.31272/) (2026)

## Abstract (arXiv)

Generative models are now capable of producing natural language text that is, in some cases, comparable in quality to the text produced by people. In the computing education context, these models are being used to generate code, code explanations, and programming exercises. The rapid adoption of these models has prompted multiple position papers and workshops which discuss the implications of these models for computing education, both positive and negative. This paper presents results from a series of semi-structured interviews with 12 students and 6 instructors about their awareness, experiences, and preferences regarding the use of tools powered by generative AI in computing classrooms. The results suggest that Generative AI (GAI) tools will play an increasingly significant role in computing education. However, students and instructors also raised numerous concerns about how these models should be integrated to best support the needs and learning goals of students. We also identified interesting tensions and alignments that emerged between how instructors and students prefer to engage with these models. We discuss these results and provide recommendations related to curriculum development, assessment methods, and pedagogical practice. As GAI tools become increasingly prevalent, it's important to understand educational stakeholders' preferences and values to ensure that these tools can be used for good and that potential harms can be mitigated.