Curriculum design in higher education has traditionally been something done to students rather than with them. Even where good intentions exist, such as embedding inclusivity, widening participation or flexible learning, decisions about content, assessment and delivery are often made without meaningful student involvement. At the same time, Generative AI is rapidly entering teaching spaces, frequently framed as a productivity tool for staff or a threat to assessment integrity.
What if we paused and reframed both challenges together?
Rather than asking how AI can help us design faster, or how students can better fit into existing structures, a more powerful question is this: how might students, educators and AI work together to co-design learning that genuinely reflects diverse needs and experiences?
Students as Partners: from consultation to collaboration
Student as Partners (SaP) is not a new idea, but it is often misunderstood. SaP is not about surveys at the end of a module or tokenistic student representation on committees. At its core, SaP is about shared responsibility, mutual respect and a redistribution of power in learning and teaching.
Advance HE has long championed partnership approaches because they improve engagement, belonging and curriculum relevance, particularly for students from underrepresented backgrounds. When students are invited into curriculum conversations early, before assessments are fixed, and teaching plans are finalised, they move from passive recipients to active contributors.
However, one of the most common concerns raised by staff is practical: how do we do this at scale, without adding unmanageable workload or losing academic rigour?
This is where Generative AI can play a surprising and constructive role.
Universal Design for Learning and EDI in practice
Universal Design for Learning (UDL) encourages educators to design learning environments that anticipate learner variability from the outset, rather than retrofitting adjustments later. It promotes flexibility in how students engage with content, demonstrate learning and stay motivated.
Yet UDL is often implemented as a checklist rather than a dialogue. We decide, in advance, what “options” students might need.
A partnership approach strengthens UDL by asking a simple but transformative question: What actually works for this cohort?
From an EDI perspective, this matters deeply. Inclusive curricula are not only are about whose knowledge is valued and whose voices shape the learning journey. When students contribute to decisions about assessment formats or learning activities, the curriculum becomes more reflective of their cultural, professional and lived experiences.
Generative AI as a co-design facilitator, not a shortcut
Much of the current debate positions GenAI as either a content generator or a policing problem. In a co-design model, its role is different.
Used transparently and critically, GenAI can act as a neutral idea generator that supports collaborative thinking. For example, in a co-design workshop, an educator might share the module learning outcomes and use a prompt such as:
“Suggest a range of assessment formats that could demonstrate understanding of these outcomes for a diverse group of students.”
The AI-generated list of podcasts, policy briefs, portfolios, simulations, and reflective narratives does not determine the assessment. Instead, it creates a shared starting point for discussion. Students and staff can debate feasibility, alignment and fairness, eventually agreeing on assessment choices that maintain standards while offering meaningful choice.
The same approach can be used to co-design learning pathways, generating different ways to engage with core topics through readings, videos, applied tasks, or community-based learning. This directly supports the UDL principle of multiple means of representation, while reinforcing student agency.
Crucially, the educator remains the academic lead. AI supports the process, not the judgment.
Reimagining active blended learning
Active Blended Learning is often described in terms of delivery mode: what happens online versus face-to-face. A co-design lens shifts the focus from where learning happens to who shapes it.
In practice, this can look like a simple four-phase cycle:
At the start of the module, students participate in guided co-design discussions around assessments and learning activities, supported by AI-generated prompts.
During online learning phases, students engage with materials they have helped select and may critique or adapt AI-generated starter content, building digital and critical AI literacy.
In face-to-face sessions, time is used for dialogue, problem-solving and collaborative activities chosen by the cohort. The educator’s role becomes that of facilitator and learning architect, rather than content deliverer.
Through ongoing feedback loops, mid-module evaluation becomes a second co-design moment, asking what should be sustained, changed or removed.
This approach aligns strongly with Advance HE’s emphasis on inclusive, reflective and evidence-informed teaching practice.
What changes for staff and students?
For students, the impact is often immediate. They report stronger ownership of learning, greater clarity about expectations and a sense that their perspectives matter. This is particularly significant for students who may feel marginalised by traditional academic norms.
For staff, there is an initial shift in mindset from control to collaboration, but many find that GenAI reduces, rather than increases, cognitive load by handling the “blank page” problem. Instead of inventing endless alternatives alone, educators can focus on mentoring, dialogue and disciplinary judgement.
Essentially, this is not about abandoning standards or consistency. It is about designing rigorously, inclusively and transparently, with students as contributors rather than consumers.
A question to leave you with
If students helped design your next assessment or learning activity supported by AI as a thinking partner, what might change about who succeeds, who feels they belong, and how learning is valued?
Dr Patrice Seuwou is an Associate Professor in Learning and Teaching, University of Northampton, with expertise in inclusive curriculum design, student partnership and digital pedagogy. His work focuses on operationalising equity and belonging through co-creation, Active Blended Learning and responsible use of Generative AI in higher education.