Ongoing Research · Co-design · Responsible AI
SEED-AI
Co-designing Social Entrepreneurship Education
A collaborative research project developing a community-led social entrepreneurship module through participatory co-design, design thinking and the responsible use of generative AI.
The project brings together students, academics and East London community organisations to explore how real community challenges can inform entrepreneurship education.
Visit the SEED-AI project websiteResearch Context
SEED-AI explores how a social entrepreneurship university module can be co-designed with the people who will participate in and contribute to it. Rather than beginning with a fixed educational solution, the project uses collaborative research and design activities to understand community context, identify meaningful opportunities and develop a module structure around real-world challenges.
A central part of the research is understanding where generative AI can support learning and design activity, while also defining where human dialogue, lived experience and community expertise must remain central.
Collaborative Research
Students
Learners contributing perspectives on how entrepreneurship education can be engaging, accessible and relevant.
Academics
Supporting educational structure, research development and integration with university learning.
Community Organisations
Contributing contextual knowledge, lived experience and real community challenges from East London.
Co-design Approach
The project uses participatory co-design to develop the module with stakeholders rather than designing it for them in isolation. Workshops, conversations, reflection and iterative development are used to build understanding before educational activities and opportunities are defined.
- 01Empathise
- 02Define
- 03Ideate
- 04Prototype
- 05Test / Reflect
Empathise
Understanding the community context before defining the challenge.
The Empathise stage focuses on developing an authentic understanding of the community context before challenges or solutions are defined. The emphasis is on listening, relationship-building and recognising community expertise.
Key Questions
- Who are the community partners?
- What matters to them?
- What strengths already exist within the community?
- What assumptions need challenging?
- Whose voices have not yet been heard?
Methods
- Community conversations
- Stakeholder mapping
- Community asset mapping
- Walking interviews
- Observation
- Storytelling
- Reflective field notes
Evidence of Learning
- Stakeholder map
- Community profile
- Reflective journal
- Observation notes
- Initial opportunity statement
“Relationship-building comes before problem definition.”
Responsible GenAI
Generative AI is treated as a supporting design and learning tool rather than a substitute for community dialogue, judgement or lived experience.
Appropriate Use
- Background research
- Preparing interview questions
- Organising notes
- Supporting reflection
- Supporting idea exploration where appropriate
Not Appropriate
- Defining community priorities
- Replacing community dialogue
- Generating assumptions about lived experience
- Treating AI output as community evidence
From Research to Module Development
This five-stage design-thinking framework guides the ongoing research and development of the module.
- 01
Empathise
Understand people, context and existing strengths.
- 02
Define
Translate research into a focused opportunity or challenge.
- 03
Ideate
Explore multiple possible responses.
- 04
Prototype
Develop tangible learning activities, module elements or interventions.
- 05
Test / Reflect
Gather feedback, evaluate and refine.
Entrepreneurship Learning
The developing module also considers how design activities connect with entrepreneurship competencies rather than treating entrepreneurship as only business planning.
EntreComp competency mapping
EntreComp provides a framework for considering skills such as identifying opportunities, mobilising resources, taking initiative, working with others and learning through experience.
From Research to Educational Design
The research is intended to translate community engagement and co-design findings into a practical social entrepreneurship learning experience. The module structure is being developed around real challenges, iterative design activity, reflection and responsible use of generative AI.
- Community Context
- Research & Co-design
- Learning Opportunities
- Module Activities
- Reflection & Iteration
Current Development
The project is currently being developed into a structured module blueprint and a reusable educational resource that can support future social entrepreneurship learning.
Module Blueprint
A developing framework bringing together learning stages, community engagement, activities, evidence of learning and responsible GenAI guidance.
Reusable Educational Resource
A resource being refined to support future implementation and adaptation of the co-designed approach.
My Contribution
My work contributes to the research, development and refinement of the module framework, including the organisation of design-thinking stages, learning activities, evidence of learning and responsible GenAI guidance.
- Module-framework development
- Research organisation
- Co-design preparation
- Responsible GenAI integration
- Communicating the research through structured educational material
Research Principles
Listen Before Defining
Begin with context, relationships and existing strengths.
Co-design, Not Design For
Develop the work with stakeholders rather than in isolation.
AI Supports — It Does Not Replace
Keep dialogue, judgement and lived experience central.
Reflect and Iterate
Use feedback to refine the developing framework.
Current Status
SEED-AI remains an active research project. The module framework and supporting resources continue to develop through research, feedback and iterative refinement.