Personalized Recommender System for Improving Urban Exploration and Experience Documentation of International Students

Madjid Sadallah, Marie Lefevre

2025

Abstract

International students face significant integration challenges in new urban environments. Documenting their experiences is crucial for reflection and adaptation; however, linguistic and cultural barriers often hinder effective documentation. This study introduces a personalized recommender system designed to facilitate this process, enhancing social engagement. The system provides targeted prompts that guide students towards richer, more reflective annotations. Utilizing a mixed-methods approach—quantitative analysis of user interactions and qualitative feedback—we evaluated its impact. Our analysis demonstrates that the recommender system substantially enriches student documentation, fostering deeper connections with new surroundings, enhancing textual and emotional expression, and promoting diverse and reflective perspectives. These findings highlight the system’s potential to accelerate international student adaptation and offer insights for future technologies aimed at improving their global integration and well-being.

Paper Citation

in Harvard Style

Sadallah M. and Lefevre M. (2025). Personalized Recommender System for Improving Urban Exploration and Experience Documentation of International Students. In Proceedings of the 17th International Conference on Computer Supported Education - Volume 2: CSEDU; ISBN 978-989-758-746-7, SciTePress, pages 923-930. DOI: 10.5220/0013202800003932

in Bibtex Style

@conference{csedu25,
author={Madjid Sadallah and Marie Lefevre},
title={Personalized Recommender System for Improving Urban Exploration and Experience Documentation of International Students},
booktitle={Proceedings of the 17th International Conference on Computer Supported Education - Volume 2: CSEDU},
year={2025},
pages={923-930},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013202800003932},
isbn={978-989-758-746-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Conference on Computer Supported Education - Volume 2: CSEDU
TI - Personalized Recommender System for Improving Urban Exploration and Experience Documentation of International Students
SN - 978-989-758-746-7
AU - Sadallah M.
AU - Lefevre M.
PY - 2025
SP - 923
EP - 930
DO - 10.5220/0013202800003932
PB - SciTePress