Designing a Universal Student Passport for Responsible AI-Driven Personalised Learning in Engineering Higher Education

Artificial Intelligence (AI), and particularly Generative AI, is increasingly being adopted in higher education to support content adaptation, feedback generation, concept explanation, and more personalised learning experiences. While these developments offer substantial promise, current approaches to AI-supported personalisation often remain fragmented, tool-driven, and insufficiently grounded in structured representations of learner needs and preferences. This creates a gap between the technical capabilities of AI and the pedagogical, organisational, and governance requirements necessary for its responsible integration in higher education. This paper proposes a conceptual architecture for a Universal Student Passport to support responsible AI-driven personalised learning in engineering higher education. The work is developed within the context of the Erasmus+ funded MultAI-PASS project, and is grounded in early project design activities, including a review of learning preferences and learner variability, as well as an analytical synthesis of learner-related dimensions relevant to personalised support. The paper focuses on the design rationale of the passport, its core architectural layers, its intended information flow, and the governance principles required to ensure transparency, student agency, and educator oversight. In doing so, it offers a structured conceptual bridge between learner-related preferences and AI-supported educational adaptation in engineering higher education.