Recent advances in generative and agentic AI are rapidly transforming software engineering practice and challenging long-standing assumptions about how software engineers should be educated, trained, and assessed. Increasingly autonomous AI agents can now participate in software development activities such as effort estimation, planning, implementation, code review, and decision-making, introducing new challenges related to trust, cognitive bias, overreliance, accountability, and human oversight. This keynote explores how recent research on large language models (LLMs) and human-AI collaboration can inform the future of software engineering education. Drawing on empirical findings from AI-assisted effort estimation research, the talk examines how LLMs can exhibit behaviours resembling human cognitive biases, such as anchoring bias, raising concerns about the reliability of AI-generated recommendations and the erosion of human critical judgment. The keynote also discusses emerging research on gaze-informed AI support for code comprehension, illustrating how adaptive AI systems may increasingly respond to developers’ cognitive processes and attention patterns to provide personalised assistance. Building on these perspectives, the keynote argues that software engineering education must move beyond teaching students how to produce code toward preparing them to critically evaluate, supervise, and collaborate with AI agents in socio-technical environments. The talk concludes by outlining a research agenda for evaluating software engineering competencies in the AI era, including human-AI collaboration, reflective reasoning, engineering judgment, and responsible interaction with agentic AI systems.

I am an Associate Professor (Senior Lecturer) in Software Engineering at the School of Computing Science, University of Glasgow, United Kingdom.

My research field is empirical software engineering with a focus on human aspects (cognitive and social psychology), accompanied by Data Analytics and Machine Learning. My vision is to enhance software practitioners’ decision-making to improve software quality by developing (1) tools and techniques based on cognitive psychology; and (2) ML systems (e.g., LLMs) with human in the loop that can be regarded as a joint cognitive system.

Previously, I worked as a postdoc fellow at The Open University, United Kingdom, and Ryerson University, Canada, and later as a lecturer (biträdande universitetslektor) at Chalmers | University of Gothenburg, Sweden. Before joining the University of Glasgow, I was a senior researcher in the Department of Informatics at the University of Zurich (UZH), Switzerland. I am a member of the IEEE Computer Society. The papers I coauthored received a Best Industry Paper Award at ESEM’2013 (Industry Track), an ACM SIGSOFT Distinguished Artefact Award at ICSE’2020, an ACM SIGSOFT Distinguished Paper Award at ICSE’2021 and an ACM SIGSOFT Distinguished Paper Award at ESEC/FSE 2022. I served as the ICPC 2024 ERA Track co-Chair. I serve as an Associate Editor for the ACM Transactions on Software Engineering and Methodology (TOSEM). My service is recognised by the Distinguished Reviewer Awards at ICPC’2022 and ICSME’2023.