Computational techniques for data science applied to broaden the knowledge between citizen science and education

Abstract

Comunicació presentada a: 18th International Conference on Cognition and Exploratory Learning in the Digital Age (CELDA 2021) celebrat del 13 al 15 d'octubre de 2021de manera virtual

This paper describes a preliminary study of how computational methods allow us to know more about citizen science and its connection with education. Citizen science is a practice involving a general public in scientific tasks and generating knowledge and scientific results. Previous studies have shown that the education sector can take benefit of the knowledge and activities organized or resources generated in CS projects. Previous studies have shown that the education sector can take advantage of the knowledge and activities organized in CS projects. In this papers, we analyze three citizen science platforms (Eu.Citizen science platform, Observatorio de la ciencia ciudadana and Oficina de la ciència ciutadana) with computational analytics techniques to provide initial insights of how educators can take benefit of the analysis of large amounts of data from CS. Finally, different visualizations and dashboards have been developed as illustrative examples of tools to support educators and learners. These tools provide information about citizen science projects, an overview of scientific vocabulary, access to validated resources and examples of technology used in scientific inquiry that can be used with educational purposes.

This work has been partially funded by the CS Track project, European Union’s Horizon 2020 research and innovation programme under grant agreement No 872522. Patricia Santos acknowledges the support by the Spanish Ministry of Science and Innovation under the Ramon y Cajal programme.