Designing the Smart Oasis of Tomorrow: A Project-Based Approach to Climate Resiliency and AI Literacy in Riyadh
This quantitative assessment investigates the impact of “Design Empathy” Summer-Autumn Program on 34 high school students in Riyadh. This project-based course tasked students with prototyping smart resilient towns aligned with Sustainable Development Goals (SDGs), supported by emerging technologies such as Artificial Intelligence (AI). Survey results from 31 respondents indicate significant gains in knowledge levels and positive attitude shifts, with no noticeable gender-based differences. Findings corroborate with existing literature on the pedagogical soundness of project-based learning. Learner support and academic-industry partnership also account for the program's success in harnessing students’ socioemotional and vocational development. Exemplifying Student-AI Collaboration (SAC) through the use of AI-powered software VillageOS™, the synthesis of climate education and hands-on AI interactions provides a unique venue for data model visualization and machine learning techniques. Insights from the preliminary outcomes can inform future practitioners technological integration in teaching climate science. It is also imperative that policymakers and institutional stakeholders continuously broaden the access to similar educational initiatives for all students, thereby galvanizing youth's boundless potential in innovation and environmental stewardship. “Design Empathy” underscores climate resiliency and digital literacy, demonstrating equitable benefits across genders for its inclusive and versatile design. Future iterations will explore multisite implementations, sample diversification, deepened AI integration, and longitudinal studies.
Authors
- Jason S. Ehrlich
- Shuhan Li (ORCID: https://orcid.org/0000-0001-9174-3691)
- Roozbeh Aliabadi
- Alexandra Albinus
Institutions
- The Art Institutes (US)
- Stanford University (US)
Publication Details
- Published
- 2025-07-18
- DOI
- https://doi.org/10.1145/3715335.3735457
- Citations
- 1
- Primary Topic
- Smart Cities and Technologies
- Type
- article
- Field-Weighted Citation Impact
- 1.14