# Towards Integrating Emerging AI Applications in SE Education

arXiv: https://arxiv.org/abs/2405.18062 · HTML: https://mlsanity.com/paper/2405.18062/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 May 2024.

## Built on by (most cited first, 4 of 4)

- [Large Language Models in Computer Science Education: A Systematic Literature Review](https://mlsanity.com/paper/2410.16349/) (2024)
- [Perspective of Software Engineering Researchers on Machine Learning Practices Regarding Research, Review, and Education](https://mlsanity.com/paper/2411.19304/) (2024)
- [Assessing the Software Security Comprehension of Large Language Models](https://mlsanity.com/paper/2512.21238/) (2025)
- [Integrating AI into Requirements Quality Learning in Software Engineering Education: A TPACK-Guided Empirical Study](https://mlsanity.com/paper/2607.28176/) (2026)

## Abstract (arXiv)

Artificial Intelligence (AI) approaches have been incorporated into modern learning environments and software engineering (SE) courses and curricula for several years. However, with the significant rise in popularity of large language models (LLMs) in general, and OpenAI's LLM-powered chatbot ChatGPT in particular in the last year, educators are faced with rapidly changing classroom environments and disrupted teaching principles. Examples range from programming assignment solutions that are fully generated via ChatGPT, to various forms of cheating during exams. However, despite these negative aspects and emerging challenges, AI tools in general, and LLM applications in particular, can also provide significant opportunities in a wide variety of SE courses, supporting both students and educators in meaningful ways. In this early research paper, we present preliminary results of a systematic analysis of current trends in the area of AI, and how they can be integrated into university-level SE curricula, guidelines, and approaches to support both instructors and learners. We collected both teaching and research papers and analyzed their potential usage in SE education, using the ACM Computer Science Curriculum Guidelines CS2023. As an initial outcome, we discuss a series of opportunities for AI applications and further research areas.