Learning experiences with civic data for Global Citizenship
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Abstract
This study tracks the evidence of Global Citizenship that reveal the voices of participants when they are immersed in learning experiences related to data science. Civic data, visualization software and the principles of Global Citizenship were used to design learning experiences that embodied some type of global problem (global warming, surface water contamination, carbon dioxide emissions). Learning experiences were implemented with different populations: primary students, secondary students and in-service teachers and each meeting was recorded in audio and video. The meetings were transcribed verbatim and over the transcripts were tracked the clues of Global CItizhenship. The results suggest that the verbal statements of the participants offer evidence of Global Citizenship in the cognitive (knowledge), socio-emotional (empaty, responsibility, solidarity) and behavioral (acctions) dimensions as a result of the exposure to the learning experiences.
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References
AKKARI, A.; MALEQ, K. Global Citizenship Education: Critical and International Perspectives. Geneva: Springer, 2020.
ANDERSON, T.; SHATTUCK, J. Design-based research: A decade of progress in education research? Educational Researcher, v. 41, n. 1, p. 16–25. 2012. DOI: https://doi.org/10.3102/0013189X11428813.
BAKKER, A.; VAN MIERLO, X.; AKKERMAN, S. Learning to integrate statistical and work related reasoning. In: 12th INTERNATIONAL CONGRESS ON MATHEMATICAL EDUCATION. 2012, Seoul, Korea.
BARGAGLIOTTI, A., et al. PreK-12 guidelines for assessment and instruction in statistics education II (GAISE II). A framework for statistics and data science education. American Statistical Association; National Council of Teachers of Mathematics, 2020. Disponible en: https://www.amstat.org/asa/files/pdfs/GAISE/GAISEIIPreK-12_Full.pdf.
CABRERA, I. El análisis de contenido en la investigación educativa: propuesta de fases y procedimientos para la etapa de evaluación de la información. Revista Pedagogía Universitaria, v. 14, n. 3, p. 71-93. 2009.
ENGEL, J. Cultura estadística y sociedad: ¿Qué es la Estadística Cívica? In: TERCER CONGRESO INTERNACIONAL VIRTUAL DE EDUCACIÓN ESTADÍSTICA, 2019, Granada, España.
FELICES, M.; MORENO, C.; JIMÉNEZ, M. D. Ciudadanía global igualitaria y formación del profesorado. In: GARCÍA RUIZ, C. R. et al. (ed)., Deconstruir la alteridad desde la Didáctica de las Ciencias Sociales. Paris: Educar para una ciudadanía global, 2016. p. 236–245.
GAL, I.; NICHOLSON, J.; RIDGWAY, J. A conceptual framework for Civic Statistics and its educational applications. In: RIDGWAY, J. (ed.). Statistics for Empowerment and Social Engagement. Teaching Civic Statistics to Develop Informed Citizens. Switzerland: Springer Nature, 2022. p. 37-66. DOI: https://doi.org/10.1007/978-3-031-20748-8_3.
GAL, I.; OGRAJENŠEK, I. Official statistics and statistics education: Bridging the gap. Journal of Official Statistics, v. 33, n. 1, p. 79–100, 2017. DOI: http://dx.doi.org/10.1515/JOS-2017-0005.
GONZÁLEZ-VALENCIA, G., MASSIB SABATER, M. ; SANTISTEBAN FERNANDEZ, A. Critical Global citizenship education: A study on secondary school students. Teacher Education, v.7, 2022. DOI: https://doi.org/10.3389/feduc.2022.867113.
GOULD, R. BARGAGLIOTTI, A., JOHNSON, T. An analysis of secondary teachers' reasoning with participatory sensing data. Journal for Research in Statistics Education, v. 16, n. 2, 2017. Special issue: statistical reasoning about models and modelling in the context of informal statistical inference. DOI: https://doi.org/10.52041/serj.v16i2.194.
HERNÁNDEZ SASTOQUE, E.; ZAPATA-CARDONA, L. La investigación en Educación Matemática: Una mirada a la metodología en un estudio cualitativo. In: QUIROZ POSADA, R. (ed). Investigación para ampliar fronteras . Medellín, Universidad Pontificia Bolivariana, 2021. p.67 – 82. DOI: http://hdl.handle.net/20.500.11912/6277.
MAKAR, K.;FRY, K.; ENGLISH, L. Primary students learning about citizenship through data science. ZDM – Mathematics Education, 2023. DOI: https://doi.org/10.1007/s11858-022-01450-7.
MALDITA.ES. Las desinformaciones del video que niega el calentamiento global y su relacion con el CO2 y asegura que las temperaturas no han subido desde 1998. [Maldito Bulo, 2023 https://maldita.es/malditobulo/20230712/video-ferrandis-cambio-climatico-co2/]. Acceso 26/10/2023.
MARTÍNEZ-CASTRO, C. A.; ZAPATA-CARDONA, L. La reflexión en la formación inicial de maestros de estadística: un estudio piloto. In: III ENCUENTRO COLOMBIANO DE EDUCACIÓN ESTOCÁSTICA. Bogotá, Colombia: Asociación Colombiana de Educación Estocástica. 2018. p. 208-219. Disponible en: http://funes.uniandes.edu.co/12942/.
MEDELLÍN CÓMO VAMOS (2020). Informe de calidad de vida de Medellín, 2020. Disponible en: https://www.medellincomovamos.org/system/files/2021-09/docuprivados/Documento%20Informe%20de%20Calidad%20de%20Vida%20de%20Medell%C3%ADn%202020.pdf.
O’ NEIL, C. Weapons of math destruction. How big data increases inequalities and threatens democracy. New York: Crown. 2016.
PAK, S. Global Citizenship Education Goals and Challenges in the New Millennium. Seoul: UNESCO-APCEIU. 2013.
PORCIÚNCULA, M.; BATISTI, I. State of the knowledge about Statistical Education in the context of Early Childhood Education. Ensino Em Re-Vista, Uberlândia, v. 30, p. 1-27, 2023. DOI: http://doi.org/10.14393/ER-v30a2023-4.
POWELL, A. B.; FRANCISCO, J. M.; MAHER, C. A. An analytical model for studying the development of learners’ mathematical ideas and reasoning using videotape data. The Journal of Mathematical Behavior, v. 22, n. 4, p. 405–435. 2003. DOI: https://doi.org/10.1126/science.1064218.
SAGARIN, R.; MICHELI, F. Climate change in nontraditional data sets. Science, New Series, v. 294, n. 5543, p. 811. 2001. DOI: https://doi.org/10.1126/science.1064218.
SANDVIG, C., KARAHALIOS, K., LANBORT, C. Uncovering algorithms: Looking Inside the facebook News Feed. Civic Media – Creating Technology for Social Change. 2014. Disponible en: https://civic.mit.edu/index.html%3Fp=1180.html.
STROMQUIST, N. (2009). Theorizing global citizenship: discourses, challenges, and implications for education. Interamerican Journal of Education for Democracy, v. 2, p. 6–29, 2009. Disponible en: https://scholarworks.iu.edu/journals/index.php/ried/article/view/135.
United Nations Educational, Scientific and Cultural Organization [UNESCO]. Global citizenship education: Topics and learning objectives. UNESCO. 2015. Disponible en: http://unesdoc.unesco.org/images/0023/002329/232993e.pdf.
United Nations Educational, Scientific and Cultural Organization [UNESCO]. Education for Sustainable Development Goals: Learning Objectives. UNESCO: Paris, France. 2017. Disponible en: https://unesdoc.unesco.org/ark:/48223/pf0000247444.
United Nations Educational, Scientific and Cultural Organization [UNESCO]. Preparing teachers for global citizenship education: a template - UNESCO Digital Library. Bangkok: UNESCO. 2018
ZAPATA-CARDONA, L. The possibilities of exploring nontraditional datasets with young children, Teaching Statistics, v. 45, p. S22–S29. 2023, DOI: https://doi.org/10.1111/test.12349.
ZAPATA-CARDONA, L.; MARTÍNEZ-CASTRO, C. A. Statistical modeling in teacher education. Mathematical Thinking and Learning, v. 23, n. 1, p. 64-78, 2023. DOI: https://doi.org/10.1080/10986065.2021.1922859.