The final year design project is one of the most important components of any undergraduate engineering program. Fair and efficient project allocation procedures can be vital in ensuring a great student experience and exceptional learning out of these projects, which then could contribute in shaping students’ future prospects. In this paper, we review a wide range of project allocation strategies used in various universities at undergraduate levels. We then focus on the project allocations in transnational education (TNE) contexts, which inherit additional allocation challenges. We highlight these challenges and provide recommendations to solve them. We present and compare project allocation strategies adopted at two of the largest TNE programs in China. We also present the factors that influence the project allocations, particularly regarding TNE provisions. Finally, we describe the challenges associated with the project allocations in the TNE scenario, along with proposing some feasible solutions to address these challenges.

This study investigates the implementation and impact of the Guided Personalised Learning (GPL) model, a structured pedagogical framework designed to operationalise personalised and student-centred learning in STEM higher education. The GPL model integrates three interconnected components: a three-dimensional knowledge and skill grid, Interactive Learning Progress Assessments (ILPA), and an adaptive learning resource pool. These components were embedded into two undergraduate engineering modules, Network Engineering and Software Engineering, at a UK university. A mixed-method evaluation, centred on student attainment data across two academic years, revealed statistically significant improvements among students who engaged with GPL, particularly those who completed ILPA activities. Participation was associated with higher mean grades, increased proportions of high achievers, and reduced failure rates. These findings demonstrate the GPL model’s effectiveness in supporting learner autonomy, formative assessment, and targeted feedback, while offering a scalable strategy for integrating personalised learning into mainstream STEM curricula.