Transition to program-level assessment in engineering education: a stage-gate approach to assurance of learning in the age of AI

The mainstream adoption of generative artificial intelligence (GAI) poses a risk to academic integrity, questioning the ability to assess students’ learning. Quality assurance agencies recommend considering securing assessment throughout educational programs. These places renewed interest in program-level assessment, a holistic approach where assessment items are strategically set across the program to progressively support and evaluate learners’ development of knowledge and skills. In practice, though, the implementation has proven complex, and the assessment points remain vulnerable to students’ use of emerging technologies like GAI unless assessment is secured. This study aims to bridge the gap between the theoretical conceptualisation of program-level assessment and its practical implementation to better prepare students for professional practice and to address the challenges posed by emerging technologies. The research is based on the analysis of an instrumental case study, a Bachelor of Engineering (Honours) program at an Australian university. The findings provide a guide to rationalise assessment in engineering programs and facilitate a stepped transition to program-level assessment. The paper also discusses policy and structural changes to support the implementation.