Our work is organised into six interlinked focus areas spanning empirical research, educational innovation, and practice guidance.
Study current patterns in AI-generated code use across development teams and educational settings.
Gather evidence from software engineering educators on benefits, risks, and teaching adaptations.
Investigate knowledge structures, cognitive load, and interaction models in AI-assisted coding.
Define learning outcomes, assessment strategies, and curriculum pathways embracing AI coding tools.
Refine responsible-use guidance through empirical evaluation and iterative feedback.
Adapt learning interventions as generative AI technologies continue to change.
Collaborate on AI-based code generation research, contribute to educational innovation, and engage with practitioners shaping responsible software development.