Abstract
Network science is an interdisciplinary field that provides a wide range of analytical and computational tools to conceptualize, develop, analyze, and understand interconnected systems. The recent technological and social media developments based on this field explain the increasing interest to include network-based concepts across all educational stages. In this work, we present a web-based application to obtain networks from novels and/or movie scripts semi-automatically. These graphs can be used as teaching examples and in assignments, thus implementing differentiation by interest instruction and facilitating the adaptation of the contents to multicultural classrooms.
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Acknowledgements
The authors acknowledge financial support from the Spanish Ministry of Science, Innovation and Universities (excellence networks HAR2017-90883-REDC and RED2018‐102518‐T), and from the Junta de Castilla y León - Consejería de Educación through BDNS 425389 and the predoctoral grant awarded to Virginia Ahedo (supported by the European Social Fund). In addition, the authors would like to especially thank Dr. Luis Izquierdo for his insightful suggestions to improve the manuscript and Dr. Álvar Arnaiz-González, Yi Peng Ji and Alicia Olivares-Gil for their advice and help with some programming work.
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Cabrejas-Arce, L.M., Navarro, J., Ahedo, V., Galán, J.M. (2021). NetExtractor. A Semi-automatic Educational Tool for Network Extraction Conceived to Differentiate by Student Interest. In: Herrero, Á., Cambra, C., Urda, D., Sedano, J., Quintián, H., Corchado, E. (eds) The 11th International Conference on EUropean Transnational Educational (ICEUTE 2020). ICEUTE 2020. Advances in Intelligent Systems and Computing, vol 1266. Springer, Cham. https://doi.org/10.1007/978-3-030-57799-5_22
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