Document Type
Article
Publication Date
9-4-2024
Publisher
Association for Computing Machinery
Abstract
Proper waste management is a critical aspect of sustainable living. Many sustainable communities have implemented various initiatives to support sustainability through better waste management. However, the knowledge required for proper waste management is increasingly complex, and the process of waste classification can be very confusing. In this work, we present a home-grown web-based educational technology, Waste Genie (WG), that supplies bite-size interactive learning content with a scalable Human-AI collaborated design to support sustainability learning. WG leverages large language models to provide personalized feedback to guide the users through practicing waste sorting; it also synthesizes informative posts to facilitate learning. In addition, various social and sustainability awareness features (i.e. virtual carbon credits visualizer, waste scanner, personal learning progress, etc.) are engineered in WG to support cultivating self-directed learning in waste management. A user study was conducted to examine the impacts of the informal learning content in bite size and the overall usability of the application. The results demonstrated that WG effectively improved users’ sustainability awareness while providing a user-friendly and engaging learning experience. This study highlighted the potential of human and AI integration for the creation of educational content for a sustainable digital future.
Recommended Citation
Sun, Q., & Hsiao, I.-H. (2024). An AI-infused Educational Technology to Cultivate Self-directed Learning in Sustainable Waste Management. Proceedings of the 2024 International Conference on Information Technology for Social Good, 127–134. https://doi.org/10.1145/3677525.3678652
Comments
This work is licensed under a Creative Commons Attribution International 4.0 License.