The rapid growth of Information and Computing Technologies (ICT) has a critical impact on what has been labelled the 21st century skills that students should acquire to become competent in the new society challenges and careers. In this respect, Software Engineering has gained even greater importance in education, as society increasingly relies on experts in this area. Universities are striving to provide such expertise, albeit with varying degrees of success, as the discipline itself is constantly evolving and presents inherent difficulties. Artificial Intelligence has played an important role in assisting Software Engineering Education for many decades in the context of Intelligent Tutoring Systems (ITS). The research on ITSs has achieved significant advances in personalization, adaptivity, collaborative learning and error diagnosis in many domains including programming and it is still evolving by incorporating techniques, such as neural networks, machine learning, fuzzy logic, decision theories and cognitive theories. However, the most recent advances of AI involve Large Language Models (LLMs), such as ChatGPT, which among other things, are widely available to students and teachers of Software Engineering and other disciplines. Recent advances in AI not only assist the process of Software Engineering Education but they are changing the targeted skills that students are required to gain for the 21st Century software engineering jobs. Indeed, Artificial Intelligence has become a game changer in Software Engineering education for three reasons: Firstly, it exerts a significant influence on the software engineering methodologies themselves, necessitating their inclusion in the curriculum of AI empowered Software Engineering. Secondly, it offers a range of supportive tools that greatly aid in teaching the technical aspects of software engineering, particularly programming skills. And thirdly, AI has inherent limitations, such as potential inaccuracies and a lack of explainability. These limitations highlight the need for a balanced approach to education that goes beyond technical skills. Soft skills, such as critical thinking, problem-solving, and ethical considerations, become increasingly important in the context of AI-driven software engineering. This keynote address presents a critical analysis of existing developments on AI in Software Engineering education and provides best practices that are sourced from the author’s extensive previous and current research. By examining significant findings, the keynote address seeks to identify key insights into future advances and challenges.

This keynote address presents a critical analysis of existing developments on AI in Software Engineering education and provides best practices that are sourced from the author’s extensive previous and current research. By examining significant findings, the keynote address seeks to identify key insights into future advances and challenges.