An Interdisciplinary Model for Teaching with Open Climate Data across Mathematics, Informatics, and Geography
An Interdisciplinary Model for Teaching with Open Climate Data across Mathematics, Informatics, and Geography

Summary/Abstract: This paper presents an interdisciplinary educational model that integrates open climate data into the teaching of informatics, mathematics, and geography, with a focus on developing data literacy, geospatial thinking, and climate awareness. Using datasets from the Copernicus Climate Data Store (CDS) and open-source tools, we designed and tested a series of interactive lessons in Jupyter Notebooks that focus on climate data visualization, time series analysis, and spatial patterns of temperature change. The lessons were successfully implemented using open software such as Python and QGIS, and they introduced students to key STEM competencies, including computational thinking, geostatistical reasoning, and environmental interpretation. The model proved effective in enhancing student engagement, improving comprehension of abstract climate concepts, and developing digital competencies relevant to the 21st-century classroom. By offering a flexible structure adaptable to different technological contexts and curriculum profiles, the model contributes to climate education by providing scalable, open-access resources that support interdisciplinary learning aligned with EUdigital and green education priorities.

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