ECO-DATA: Sustainable School Garden with Heirloom Seeds and nMachine Learning
Tuba Güler, teacher (Turkey)
Haki Peşman, academic professor (Turkey)
Abstract
This project, titled "ECO-DATA:
A Sustainable School Garden Project Integrating Heritage Seeds and Machine Learning," is rigorously aligned with the Ministry of National Education's "Green Homeland" vision and the UN Sustainable Development Goals (SSD). The primary objective is to transcend traditional environmental education by actively integrating 21st-century skills, particularly Artificial Intelligence (AI) and Machine Learning (ML), into ecological management. It also fosters digital competence within the European qualifications framework. The primary objective of the project is to empower students to become active technology producers and environmental stewards. The methodological implementation begins with students collecting, documenting, and cataloging local Heritage Seeds. Students then develop a simple image classification model using high-resolution images of these seeds using Machine Learning (ML) platforms, thereby developing practical competence in AI data literacy and scientific classification. Following successful identification, students conduct scientific research to determine the optimal germination and growth conditions for each identified heritage seed. This data-driven approach embodies the principles of Smart Agriculture, informing a precise and scientific planting and resource management plan in the schoolyard. During the growing season, students assume the role of field scientists, meticulously recording quantitative growth data (e.g., height, leaf count). This collected data is then converted into analytical graphs and charts and integrated into a dynamic "Artificial Intelligence Journal" (Digital Artificial Intelligence Journal). The impactful final phase involves students developing a basic mobile app prototype. This app serves as the primary promotional tool, sharing real-time growth progress, data insights, and the critical importance of heritage seeds with families and the broader community, ensuring the project's longevity and societal impact. This initiative successfully combines ecological conservation with the practical application of cutting-edge technology, preparing students for a sustainable future. This study will be tested using scales developed as a result of the project to assess students' academic achievement, digital competence, and environmental attitudes, and will be presented at the congress.
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Keywords |
Machine Learning, Heritage Seeds, Sustainable Education, Green Homeland, Smart Agriculture, STEM Integration |
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REFERENCES |
[1] T. A. Vatan, Yeşil Vatan Benim Okulum Geleceğe Çare Proje Rehberi, MEB Yayınları, 2025. [2] U. B. Kurumu, Türkiye Tohum Gen Bankası ve Biyoçeşitlilik Raporu, 2024. [3] Beers, S. (2021). Teaching 21st Century Skills: An Overview. Learning Forward. [4] European Commission. (2020). Digital Education Action Plan 2021–2027. Brussels. [5] FAO. (2021). The State of the World’s Biodiversity for Food and Agriculture. Rome: FAO. [6] Holmes, W. (2022). Artificial Intelligence in K-12 Education: Opportunities and Challenges. Computers & Education, 179, 104403. [7] OECD. (2023). AI and the Future of Education: Policy Directions for 2030. Paris: OECD Publishing. [8] UNESCO. (2020). Education for Sustainable Development Goals: Learning Objectives. Paris: UNESCO. ENV,STEM,SOC |
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