Resultados de investigación

Esta investigación de carácter naturalista, obtiene datos por medio de un cuestionario elaborado ad hoc para analizar las competencias digitales de los estudiantes del Grado de Maestro en Educación Primaria en tres universidades españolas., Financiado por el Proyecto I+d+i "Evaluación y desarrollo de dos competencias genéricas en estudiantes de primer año del grado de maestro en educación primaria", ref.: EDU2015-70491-R

Data Documentation for Fombona, J., Pascual, M.A., Pérez, M. (2020). Analysis of the Educational Impact of M-Learning and Related Scientific Research. Journal of New Approaches in Educational Research (NAER), 9(2), 167-180. DOI https://doi.org/10.7821/naer.2020.7. 470, El trabajo explora la penetración e impacto mundial de los dispositivos móviles que obliga a la comunidad científica a hacer análisis rigurosos sobre las implicaciones de este fenómeno, y determinar sus efectos reales, y cuáles son sus usos más adecuados para su aprovechamiento en la gestión de la información y la construcción del conocimiento. PALABRAS CLAVE: TIC; sociedad del conocimiento; aprendizaje móvil; dispositivo móvil, multimedia

Dataset with data to study the interaction of emigration and immigration with foreign direct investment, exports and imports, and international remittances. The sample comprises 112 countries with which Spain has closely interconnected migratory, commercial and investment exchanges, and they focus both on the period prior to the great recession, 1998–2007, and on the subsequent period, 2008–2016. We combined several sources: data on emigration and immigration from the Spanish National Statistics Institute, INE, ("Residential Variations Statistics"); data on Spanish FDI abroad, sourced from the Spanish Ministry of Economy and Finance, Datainvex (2018); and data on international trade (exports and imports) from the World Bank and covering the period from 1998 to 2016. Also we use the data on international remittances sent and received from and to Spain in relation with these countries for the period 2010 to 2015, obtained from the World Bank.

Version 1.0, This material has been created for pedagogical purposes to serve as guide for the management of scientific data for different users such as undergraduate students (e.g. basic experimental techniques, grade of physics), master and phD students, and post-doctoral researchers. In particular, this report describes the initial Data Management Plan (DMP) for the project ARIADNE (840195), which is funded by the European Commission through the Marie Skłodowska-Curie Actions (MSCA) as part of the Individual European Standard Fellowship Programme (IF-EF-ST). The coordinator of this DMP, who is also the experienced researcher associated to the funded fellowship, is Dr. Sándalo Roldán-Vargas from the department of applied physics at the University of Granada (UGR), Spain (the beneficiary institution). The purpose of this DMP is to provide a detailed description of the procedures and protocols for the management of the datasets generated during the lifetime of the project. This DMP will describe the main data management principles in terms of data standards and metadata, sharing, archiving, preservation, and security. This is an alive document that will be updated at regular intervals during the lifetime of the project and be allocated in the institutional repository of the UGR, DIGIBUG., European Commission- MSCA-IF-EF-ST (2018)

[EN] Social media platforms have had a significant impact on the public image of sports in recent years. Through the relational dynamics of the communication on these networks, many users have emerged whose opinions can exert a great deal of influence on public conversation online. This research aims to identify the influential Twitter users during the 2016 UCI Track Cycling World Championships using different variables which, in turn, represent different dimensions of influence (popularity, activity and authority). Mathematical variables of the social network analysis and variables provided by Twitter and Google are compared. As a result, no single variable assessed is sufficient to identify the different kinds of influential Twitter users. Having a certain type of account is not enough to make a user an influencer if they do not engage (actively or passively) in the conversation. Choosing some influencers or others will depend on the objectives pursued.

Twitter dataset for a research on the 2015 Spanish General Election. The tweets were obtained through the Twitter API's Search function since November 2 to December 21, 2015. Three criteria for filtering tweets were established: two general terms linked to the elections ("#20D", "20-D"); the name and usernames of the four main parties (PP, PSOE, Podemos and Ciudadanos), and the name and usernames of the four candidates from those parties. The research assessed the tweet's issue according to Patterson (1980)'s typology for evaluating political mediatisation. The dataset contains three files: the unlabelled collection of the 15.8 million tweet ids obtained through the API, the annotated sample of the 3,117 tweet ids for assessing the issue via machine learning, and the readme.txt file. It is recommended to open the file from a text editor or through a script. The id_str must be handled as a string. If the file is open from Excel, the id_str will be interpreted as a number, and then converted into a float, losing information in this transformation