Supporting Informal Sustainability Learning with AI-assisted Educational Technology
Abstract
This paper presents Waste Genie (WG), a novel web-based educational platform designed to enhance learning about sustainable waste management. WG employs bite-sized interactive content and leverages artificial intelligence to support sustainability education. To assess WG's efficacy, we conducted a user study involving 21 college students. The study aimed to evaluate improvements in sustainability awareness, waste sorting skills, and overall user experience. Results showed a notable increase in participants' understanding of waste management practices and their ability to correctly classify waste items. This research demonstrates the potential of combining emerging technologies like large language models with interactive learning approaches to address environmental education challenges.
Keywords: Educational technology, sustainability learning, waste management
DOI: 10.54941/ahfe1005567
Cite this paper
More from this volume
- Implementing an AI Fatigue Risk Management System for Aviation Maintenance SMS: A Technology Enhanced Critical Process Human Factors Safety Plan
- Deep Learning Forecast of Perceptual Load Using fNIRS Data
- Artificial intelligence in the function of improving port systems
- Formalizing Trust in Artificial Intelligence for Built Environment Decision-Making
- Artificial Intelligence and Design: Innovation, Practical Applications, and Future Creative Horizons
- An assessment of the maintenance of heritage buildings using AI and IoT: a South African perspective
- What if we Could Entangle Drones? Towards the Management of a Swarm of Drones as a Non-Local Quantum Object
- Engaging All Elderly Residents in Community Renewal: Designer Spotlight Interview Tool for LLM Building
- AI Play in Higher Education: Students’ perceptions of play and co-creation of knowledge with generative AI
- Optimizing AI Involvement in Engineering University Courses Based on Students' Personality
- Predictive Model for Partner Agencies Dependency on Food Banks
- Investigating common factors needed for consumers to trust AI\ML


AHFE Open Access