A chance to travel

Team name: Chance

Use of AI tools :

• Which tool did we used ?
  Claude

• For what purposes ?
  We used AI tools to structure and refine our ideas, synthesize information, improve the clarity of our proposals, and critically reflect on the role of AI in higher education and international mobility. AI also helped us simulate how a conversational assistant could guide students through the administrative complexity of exchange programs such as Erasmus, MICEFA, or TASSEP.

• How did these tools support your work ?
  These tools acted as collaborative assistants throughout the project. They helped us rapidly organize information, reformulate complex administrative processes into accessible language, and explore different ways AI could support students without replacing human advisors. This allowed our multidisciplinary team to focus more deeply on ethical concerns, accessibility, inclusion, and the practical realities students face when preparing an international exchange.

External feedback & contributions :

Ndeye Sophie Seck – Feedback & Discussion:
Raised important pedagogical concerns regarding student autonomy and asked how the assistant could avoid over-simplifying administrative procedures while still ensuring that students understand the documents they sign and develop organizational skills.
Chinmay Das – Feedback & Discussion:
Highlighted the challenge of maintaining accurate and constantly updated information regarding visas, deadlines, scholarships, and exchange regulations.
KANKEU TAMEGHE – Feedback & Discussion:
Questioned how the system would ensure compliance with privacy laws and protect sensitive student data.
Haziel Álvarez – Feedback & Discussion:
Suggested that the assistant could also function as a diagnostic tool by identifying recurring administrative barriers, invisible financial aid issues, and the main causes of student dropout during exchange preparation.
Nipun Ranchhod Navadia – Feedback & Discussion:
Encouraged us to better clarify the distinct added value of the AI assistant compared to existing FAQ portals and university mobility services, while also questioning the assumptions behind administrative complexity as the main obstacle.
Hans Zúñiga – Feedback & Recommandation:
Supported the proposal for its contribution to reducing inequalities in access to international mobility and recommended strengthening the integration of official and regularly updated information sources.
Lucie Jacquet-Malo – Expert Feedback & Discussion:
Provided valuable recommendations regarding scalability, institutional integration, multilingual reliability, and progressive deployment strategies through university mobility platforms such as MoveOn.
Kashish Goel – Feedback & Discussion:
Highlighted the importance of further emphasizing the innovative dimension of the AI system beyond centralizing information and reminders, particularly regarding long-term scalability and intelligent personalization.

Initial contribution: link : A chance to travel

Final contribution: link :

Reflection on the process :
During Phase 1, our proposal mainly focused on simplifying access to information for students preparing an international exchange. During Phase 2, the project evolved into a broader reflection on responsible, inclusive, and human-centered AI for higher education. We progressively shifted from a simple “administrative chatbot” toward a system designed not only to assist students, but also to preserve autonomy, encourage critical engagement with information, and support mobility offices rather than replace them.

The most influential feedback concerned:

• the risk of students becoming overly dependent on AI tools,

• the importance of maintaining transparency and reliability of AI-generated information,

• privacy and GDPR concerns related to student data,

• and the necessity of ensuring multilingual accessibility and institutional scalability.

What changes did you make as a result?

Based on this feedback and our reflexion, we refined our proposal through several important adjustments:

1. Human-in-the-loop approach:
   We clarified that the assistant would not replace mobility advisors, but instead reduce repetitive information-seeking tasks so that human staff could focus on personalized support.

2. Student Autonomy:
   We integrated the principle that students should remain active participants in their administrative journey. The AI is designed to guide, redirect, and explain rather than complete tasks automatically.

3. Privacy Considerations:
   We strengthened our reflection on GDPR compliance and specified that the assistant would avoid direct access to highly sensitive personal documents.

4. Scalability & Integration:
   We expanded the project vision toward a progressive deployment model: first through mobility office websites, then potentially through integration into platforms such as MoveOn.

5. Multilingual & Inclusive Accessibility:
   We reinforced the importance of multilingual support to help students navigate non-French university websites and better access financial aid information regardless of their background.

How did this process strengthen our final proposal?
This iterative process transformed our project from a simple AI support concept into a more realistic and socially responsible proposal. By directly integrating concerns related to autonomy, transparency, privacy, scalability, and inclusion, we developed a solution that better reflects the real needs of students and universities. Our final proposal demonstrates that AI can be used not to replace human guidance, but to make international mobility more accessible, equitable, and understandable for all students.