Universidad Internacional De La Rioja

Higher education institutions (HEIs) have been permeated by the technological advancement that the Industrial Revolution 4.0 brings with it, and forces institutions to deal with a digital transformation in all dimensions. Applying the approaches of digital transformation to the HEI domain is an emerging field that has aroused interest during the recent past, as they allow us to describe the complex relationships between actors in a technologically supported education domain. The objective of this paper is to summarize the distinctive characteristics of the digital transformation (DT) implementation process that have taken place in HEIs. The Kitchenham protocol was conducted by authors to answer the research questions and selection criteria to retrieve the eligible papers. Nineteen papers (1980-2019) were identified in the literature as relevant and consequently analyzed in detail. The main findings show that it is indeed an emerging field, none of the found DT in HEI proposals have been developed in a holistic dimension. This situation calls for further research efforts on how HEIs can understand DT and face the current requirements that the fourth industrial revolution forced.

Abstract The Metaverse has been the centre of attraction for educationists for quite some time. This field got renewed interest with the announcement of social media giant Facebook as it rebranding and positioning it as Meta. While several studies conducted literature reviews to summarize the findings related to the Metaverse in general, no study to the best of our knowledge focused on systematically summarizing the finding related to the Metaverse in education. To cover this gap, this study conducts a systematic literature review of the Metaverse in education. It then applies both content and bibliometric analysis to reveal the research trends, focus, and limitations of this research topic. The obtained findings reveal the research gap in lifelogging applications in educational Metaverse. The findings also show that the design of Metaverse in education has evolved over generations, where generation Z is more targeted with artificial intelligence technologies compared to generation X or Y. In terms of learning scenarios, there have been very few studies focusing on mobile learning, hybrid learning, and micro learning. Additionally, no study focused on using the Metaverse in education for students with disabilities. The findings of this study provide a roadmap of future research directions to be taken into consideration and investigated to enhance the adoption of the Metaverse in education worldwide, as well as to enhance the learning and teaching experiences in the Metaverse.

The use of medicinal plants has been done since ancient times and may even be considered the origin of modern medicine. Compounds of plant origin have been and still are an important source of compounds for drugs. In this study a bibliometric study of all the works indexed in the Scopus database until 2019 has been carried out, analyzing more than 100,000 publications. On the one hand, the main countries, institutions and authors researching this topic have been identified, as well as their evolution over time. On the other hand, the links between the authors, the countries and the topics under research have been analyzed through the detection of communities. The last two periods, from 2009 to 2014 and from 2015 to 2019, have been examined in terms of research topics. It has been observed that the areas of study or clusters have been reduced, those of the last period being those engaged in unclassified drug, traditional medicine, cancer, in vivo study-antidiabetic activity, and animals-anti-inflammatory activity. In summary, it has been observed that the trend in global research is focused more on the search for new medicines or active compounds rather than on the cultivation or domestication of plant species with this demonstrated potential.

With the coronavirus (COVID-19) outbreak in China, the Chinese government decided to ban any type of face-to-face teaching, disrupting classes and resulting in over 270 million students being unable to return to their universities/schools. Therefore, the Ministry of Education (MoE) launched an initiative titled 'Ensuring learning undisrupted when classes are disrupted' by reforming the entire educational system and including an online education component. However, this quick reform in this unexpected critical situation of widespread COVID-19 cases harbours several challenges, such as the lack of time and teacher/student isolation. This paper discusses the possibility of using open educational resources (OER) and open educational practices (OEP) as an effective educational solution to overcome these challenges. Particularly, this study presents a generic OEP framework built on existing open-practice definitions. It then presents, based on this framework and based on the challenges reported by several Chinese education specialists during two national online seminars, a set of guidelines for the effective use of OER and OEP for both teaching and learning. Finally, this study presents some recommendations for the better adoption of OER and OEP in the future. The findings of this study can help researchers and educators apply OER and OEP for better learning experiences and outcomes during the COVID-19 outbreak.

The world’s population continues to grow at a high rate, such that today’s population is twice that of 1960, and is projected to increase further to 9 billion by 2050. This situation has brought about a situation in which the percentage of the global energy used in cities is increasing considerably. Biomass is a resource that is present in a variety of different materials: wood, sawdust, straw, seed waste, manure, paper waste, household waste, wastewater, etc. Biomass resources have traditionally been used, and their use is becoming increasingly important due to their economic potential, as there are significant annual volumes of agricultural production, whose by-products can be used as a source of energy and are even being promoted as so-called energy crops, specifically for this purpose. The main objective of this work was to analyze the state of research and trends in biomass for renewable energy from 1978 to 2018 to help the research community understand the current situation and future trends, as well as the situation of countries in the international context, all of which provides basic information to facilitate decision-making by those responsible for scientific policy. The main countries that are investigating the subject of biomass as a renewable energy, as measured by scientific production, are the United States, followed by China, India, Germany and Italy. The most productive institutions in this field are the Chinese Academy of Sciences, followed by the National Renewable Energy Laboratory, Danmarks Tekniske Universitet and the Ministry of Education in China. This study also identifies communities based on the keywords of the publications obtained from a bibliographic search. Six communities or clusters were found. The two most important are focused on obtaining liquid fuels from biomass. Finally, based on the collaboration between countries and biomass research, eight clusters were observed. All this is centered on three countries belonging to different clusters: USA, India and the UK.

The coronavirus disease (COVID-19) pandemic has been devastating in all senses, particularly psychologically. Physical activity (PA) is known to aid psychological well-being, and it is worth investigating whether PA has been a coping strategy during this pandemic. The objective of this literature review is to analyze the extent to which engaging in PA during the COVID-19 pandemic impacts psychological health in the adult population. The literature was searched in all databases from the EBSCOhost Research Database-MEDLINE, APA PsycArticles, between others-published between 1 January 2019 and 15 July 2020. From 180 articles found, 15 were eligible. The reviewed articles showed an association between mental health distress-e.g., stress, anxiety, depressive symptoms, social isolation, psychological distress-and PA. This research concludes that the COVID-19 pandemic and the lockdown measures caused psychological distress. Those studies that analyzed PA showed that, during quarantine, adults increased their sedentary time and reduced their PA levels, showing controversial psychological outcomes. This review discusses whether PA is an effective strategy to face the COVID-19 pandemic psychological effects contributing to a further putative increase in the prevalence of psychiatric disorders.

To date, few data on how the COVID-19 pandemic and restrictions affected children's physical activity in Europe have been published. This study examined the prevalence and correlates of physical activity and screen time from a large sample of European children during the COVID-19 pandemic to inform strategies and provide adequate mitigation measures. An online survey was conducted using convenience sampling from 15 May to 22 June, 2020. Parents were eligible if they resided in one of the survey countries and their children aged 6-18 years. 8395 children were included (median age [IQR], 13 [10-15] years; 47% boys; 57.6% urban residents; 15.5% in self-isolation). Approximately two-thirds followed structured routines (66.4% [95%CI, 65.4-67.4]), and more than half were active during online P.E. (56.6% [95%CI, 55.5-57.6]). 19.0% (95%CI, 18.2-19.9) met the WHO Global physical activity recommendation. Total screen time in excess of 2 h/day was highly prevalent (weekdays: 69.5% [95%CI, 68.5-70.5]; weekend: 63.8% [95%CI, 62.7-64.8]). Playing outdoors more than 2 h/day, following a daily routine and being active in online P.E. increased the odds of healthy levels of physical activity and screen time, particularly in mildly affected countries. In severely affected countries, online P.E. contributed most to meet screen time recommendation, whereas outdoor play was most important for adequate physical activity. Promoting safe and responsible outdoor activities, safeguarding P.E. lessons during distance learning and setting pre-planned, consistent daily routines are important in helping children maintain healthy active lifestyle in pandemic situation. These factors should be prioritised by policymakers, schools and parents. HighlightsTo our knowledge, our data provide the first multi-national estimates on physical activity and total screen time in European children roughly two months after COVID-19 was declared a global pandemic.Only 1 in 5 children met the WHO Global physical activity recommendations.Under pandemic conditions, parents should set pre-planned, consistent daily routines and integrate at least 2-hours outdoor activities into the daily schedule, preferable on each day. Schools should make P.E. lessons a priority. Decision makers should mandate online P.E. be delivered by schools during distance learning. Closing outdoor facilities for PA should be considered only as the last resort during lockdowns.

This article reports the results of a descriptive study on sex differences in the use of a second language. A questionnaire was administered to 581 Spanish‐speaking students learning Basque and English as L2 (279 males and 302 females) in order to answer these questions: Do male and female second language learners differ in (1) the number and (2) the range of vocabulary strategies they use? The results show that they differ significantly in the number of strategies used. Regarding the range of vocabulary strategies, 8 out of the 10 most frequent strategies are shared by males and females. However, a close analysis of the data also reveals differences, such as females’ greater use of formal rule strategies, input elicitation strategies, rehearsal strategies and planning strategies, and males’ greater use of image vocabulary learning strategies. In addition, the females’ total strategy usage percentages are higher than the males’, which points to either different perceptions of vocabulary learning behaviors or different patterns of vocabulary strategy usage for males and females.

Software-Defined Network (SDN) has become a promising network architecture in current days that provide network operators more control over the network infrastructure. The controller, also called as the operating system of the SDN, is responsible for running various network applications and maintaining several network services and functionalities. Despite all its capabilities, the introduction of various architectural entities of SDN poses many security threats and potential targets. Distributed Denial of Services (DDoS) is a rapidly growing attack that poses a tremendous threat to the Internet. As the control layer is vulnerable to DDoS attacks, the goal of this paper is to detect the attack traffic, by taking the centralized control aspect of SDN. Nowadays, in the field of SDN, various machine learning (ML) techniques are being deployed for detecting malicious traffic. Despite these works, choosing the relevant features and accurate classifiers for attack detection is an open question. For better detection accuracy, in this work, Support Vector Machine (SVM) is assisted by kernel principal component analysis (KPCA) with genetic algorithm (GA). In the proposed SVM model, KPCA is used for reducing the dimension of feature vectors, and GA is used for optimizing different SVM parameters. In order to reduce the noise caused by feature differences, an improved kernel function (N-RBF) is proposed. The experimental results show that compared to single-SVM, the proposed model achieves more accurate classification with better generalization. Moreover, the proposed model can be embedded within the controller to define security rules to prevent possible attacks by the attackers.

This paper presents an outline of the Lexical Constructional Model, a meaning construction model that integrates insights from functional models of language (especially, Role and Reference Grammar) and Cognitive Linguistics (especially, Goldberg's Construction Grammar and Lakoff's Cognitive Semantics). The initial claim is that a theory of semantic interpretation should be constructed on the basis of two representational mechanisms, lexical and constructional templates, and two basic cognitive operations, subsumption and conceptual cueing, that specify in what ways meaning representations from different levels may interact. It is further shown that both lexical-constructional subsumption and purely constructional subsumption –at any stage of the meaning construction process– is regulated by an inventory of both internal and external constraints. Internal constraints involve the semantic units encoded in a lexical or a constructional template, while external constraints result from the possibility or impossibility of performing high-level metaphoric and/or metonymic operations on the items involved in the subsumption or cueing processes.

Epidemic is a rapid and wide spread of infectious disease threatening many lives and economy damages. It is important to fore-tell the epidemic lifetime so to decide on timely and remedic actions. These measures include closing borders, schools, suspending community services and commuters. Resuming such curfews depends on the momentum of the outbreak and its rate of decay. Being able to accurately forecast the fate of an epidemic is an extremely important but difficult task. Due to limited knowledge of the novel disease, the high uncertainty involved and the complex societal-political factors that influence the widespread of the new virus, any forecast is anything but reliable. Another factor is the insufficient amount of available data. Data samples are often scarce when an epidemic just started. With only few training samples on hand, finding a forecasting model which offers forecast at the best efforts is a big challenge in machine learning. In the past, three popular methods have been proposed, they include 1) augmenting the existing little data, 2) using a panel selection to pick the best forecasting model from several models, and 3) fine-tuning the parameters of an individual forecasting model for the highest possible accuracy. In this paper, a methodology that embraces these three virtues of data mining from a small dataset is proposed. An experiment that is based on the recent coronavirus outbreak originated from Wuhan is conducted by applying this methodology. It is shown that an optimized forecasting model that is constructed from a new algorithm, namely polynomial neural network with corrective feedback (PNN+cf) is able to make a forecast that has relatively the lowest prediction error. The results showcase that the newly proposed methodology and PNN+cf are useful in generating acceptable forecast upon the critical time of disease outbreak when the samples are far from abundant.

This review focuses on papers on Hate Speech, particularly in legal and communication studies indexed in Web of Science. It analyzes output published in English and in Spanish as well as surveys the predominant disciplines in which these studies are written, their trend over time, by country, and type of document. This research is extended to determine the debates, lines of work of greatest interest, and the theories elaborated. The legal literature is intended to define hate speech and hate crime for the purposes of applying criminal sanctions. From the communication standpoint, the analysis of hate speech in the media is key to understanding the type of message used, its emitter, the way in which the message rallies supporters, and how they interpret the message. Spanish studies mostly fall within the legal area, in which they focus on cases of insult directed at the Catholic religion. We discuss the importance of interdisciplinarity and transversality and propose a mapping of hate speech that lends itself to comparisons between countries to assess measures to counteract their effects.

While services for fact-checking and verification to counter fake news in social media have increased, little research has investigated how journalists and the public perceive such services. This study reflects the outcomes of REVEAL, a three-year European Union research project investigating the use and impact of services for fact-checking and verification. Based on interviews with 32 young journalists and content analysis of social media users’ online conversations, we contribute new knowledge about the ways that journalists and social media users perceive online fact-checking and verification services. The findings suggest that, while young journalists were largely unfamiliar with or ambivalent about such services, they judged them as potentially useful in the investigative journalistic process. Yet, they were unwilling to rely exclusively on these tools for fact-checking and verification. A comparison of journalists’ perceptions with those of social media users reveals social media users are similarly ambivalent. Some accentuated the usefulness of such services, while others expressed strong distrust. However, the journalists displayed a more nuanced perspective, both seeing these services as potentially useful and being reluctant to blindly trust a single service. Design strategies to make online fact-checking and verification services more useful and trustworthy are suggested.

In late December 2019, a series of acute atypical respiratory disease occurred in Wuhan, China, which rapidly spread to other areas worldwide. It was soon discovered that a novel coronavirus was responsible, named the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2, 2019-nCoV). The impact of the COVID-19 pandemic on the population’s health is unprecedented in recent years and the impact on a social level even more so. The COVID-19 pandemic is the most large-scale pandemic on earth this century, and the impact in all life sectors is devasting and directly affected human activity in the first wave. The impact on the economy, social care systems, and human relationships is causing an unprecedented global crisis. SARS-CoV-2 has a strong direct acute impact on population health, not only at the physiological level but also at the psychological level for those who suffer it, those close to them, and the general population, who suffer from the social consequences of the pandemic. In this line, the economic recession increased, even more, the social imbalance and inequity, hitting the most vulnerable families, and creating a difficult context for public institutions to address. We are facing one of the greatest challenges of social intervention, which requires fast, effective, and well-coordinated responses from public institutions, the private sector, and non-governmental organizations to serve an increasingly hopeless population with increasingly urgent needs. Long-term legislation is necessary to reduce the vulnerability of the less fortunate, as well as to analyze the societal response to improve the social organization management of available resources. Therefore, in this scoping review, a consensus and critical review were performed using both primary sources, such as scientific articles, and secondary ones, such as bibliographic indexes, web pages, and databases. The main search engines were PubMed, SciELO, and Google Scholar. The method was a narrative literature review of the available literature. The aim was to assess the effects of the COVID-19 pandemic on population health, where the possible interventions at the health level are discussed, the impact in economic and social areas, and the government and health systems interventions in the pandemic, and finally, possible economic models for the recovery of the crisis are proposed.

La competencia digital docente se ha convertido en un aspecto esencial en la formación de los profesores que deben promover un aprendizaje en sus alumnos que se aleja del modelo de transmisión del conocimiento par acercarse a otro de desarrollo del talento. En este trabajo se valida un instrumento desarrollado por los autores para valorar la competencia digital de los docentes, de acuerdo con el marco actual establecido por el INTEF. Para el proceso de validación se utiliza una muestra de 426 profesores a los que se accede por un procedimiento online. La fiabilidad total del instrumento, estimada con el Alpha de Cronbach es de 0.98. La fiabilidad para las dimensiones de la escala de conocimiento varía entre 0.89 y 0.94 y para la escala de uso entre 0.87 y 0.92. En cuanto a la validez de constructo se ha pasado de un modelo inicial con 5 factores a otro con 4 factores y 4 subfactores. Las cargas factoriales de los ítems con la dimensión a la que pertenecen están en su mayoría por encima de 0.5 y en muchos casos de 0.70. En la escala de conocimiento solo hay 1 peso que no alcanza ese valor. Los resultados de ajuste global para ambas escalas muestran resultados óptimos, con unos valores inferiores a 3 para el índice de chi-cuadrado normalizado, valores por debajo de 0.06 en RMSEA y de 0.9 en IFI y CFI. Se ofrecen evidencias también respecto a la validez convergente y discriminante, que resultan significativas y aceptables. La fiabilidad del constructo para la validez convergente se aproxima en todos los casos a 0.90. En cuanto a la validez discriminante el modelo propuesto es mejor que sus alternativos, con ligeras variaciones en la escala de uso que serán objeto de futuros análisis. Este instrumento permitirá valorar las competencias de los profesores y ayudar en la planificación de itinerarios de formación personalizados en función de los resultados.Como citar este artículo: Tourón, J., Martín, D., Navarro, E., Pradas, S. y Íñigo, V. (2018). Validación de constructo de un instrumento para medir la competencia digital docente de los profesores (CDD) | Construct validation of a questionnaire to measure teachers’ digital competence (TDC). Revista Española de Pedagogía, 76 (269), 25-54. doi: 10.22550/REP76-1-2018-02Descriptores: competencia digital docente cuestionarios online validación de constructo validez convergente validez discriminante

With the global expansion of the COVID-19 pandemic, social or physical distancing, quarantines, and lockdowns have become more prevalent. Concurrently, Pornhub, one of the largest pornography sites, has reported increased pornography use in multiple countries, with global traffic increasing over 11% from late February to March 17, 2020. While some substantial increases have coincided with Pornhub making its premium services free to countries in lockdowned or quarantined jurisdictions, countries without such free premium access have also reported increases in the range of 4-24%. In addition, pornography searches using the terms "coronavirus", "corona", and "covid" have reached more than 9.1 million. In this letter, we discuss COVID-19-related pornography-use patterns and the impact they may have with respect to problematic pornography use.

Media convergence and massive usage of Internet-connected devices, distinguishing features of our current society, cause changes in the way that new generations learn and access knowledge. In addition, emerging new digital skills are necessary for the Z generation to face the challenges of a digital society. This quantitative study, with a sample of 678 Primary School students, aims to provide empirical evidence about the level of digital skills of students belonging to this generation. The results show that the acquisition of digital competences is not inherent to use, but require specific instruction. Otherwise, there is a danger of creating a digital divide, not due to frequency of use or access to connected devices but to lack of instruction on how to use them. The absence of significant variance in the overall level of digital competence among Primary School students of different grades reflects, to some extent, that this level is largely acquired by informal activities with ICTs in an informal context, rather than by developing competences in a school context that affords gradual and progressive skills acquisition. The results show the need to address digital competence in schools, focusing on the systematic development and enhancement of its component areas to move beyond the informal level and reach the academic level, thus facilitating digital natives’ access to future employment. La convergencia mediática y el uso masivo de dispositivos conectados a Internet, rasgos distintivos de la sociedad actual, provocan cambios en el modo en el que las nuevas generaciones aprenden y acceden al conocimiento. Además, emergen nuevas competencias, las digitales, que la Generación Z necesita para afrontar los retos de una sociedad digitalizada. El estudio presentado, de corte cuantitativo, con una muestra de 678 alumnos de Educación Primaria, pretende aportar evidencias empíricas sobre el nivel de competencia digital del alumnado perteneciente a dicha generación. Los resultados revelan que no adquieren habilidades digitales de forma inherente sino que precisan de educación al respecto, atisbándose el peligro de una brecha digital, no por uso o acceso a ellas, sino por falta de competencia. La ausencia de diferencia significativa en el nivel general de competencia digital entre el alumnado de diferentes cursos de la etapa de Educación Primaria refleja que, en cierta medida, ese nivel se adquiere más por convivencia con las TIC en contextos informales que por un adecuado desarrollo en el contexto escolar que potencie gradual y progresivamente su adquisición. De los resultados se desprende, por tanto, la necesidad de abordar la competencia digital en la escuela, incidiendo en el desarrollo de las áreas que la componen y potenciándola para superar el nivel de uso en la vida cotidiana y acercarla al nivel académico que facilitará su inclusión al mundo laboral.

Blended Learning (BL) is one of the most used methods in education to promote active learning and enhance students' learning outcomes. Although BL has existed for over a decade, there are still several challenges associated with it. For instance, the teachers' and students' individual differences, such as their behaviors and attitudes, might impact their adoption of BL. These challenges are further exacerbated by the COVID-19 pandemic, as schools and universities had to combine both online and offline courses to keep up with health regulations. This study conducts a systematic review of systematic reviews on BL, based on PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, to identify BL trends, gaps and future directions. The obtained findings highlight that BL was mostly investigated in higher education and targeted students in the first place. Additionally, most of the BL research is coming from developed countries, calling for cross-collaborations to facilitate BL adoption in developing countries in particular. Furthermore, a lack of ICT skills and infrastructure are the most encountered challenges by teachers, students and institutions. The findings of this study can create a roadmap to facilitate the adoption of BL. The findings of this study could facilitate the design and adoption of BL which is one of the possible solutions to face major health challenges, such as the COVID-19 pandemic.

Abstract The number of disabled students is rapidly increasing worldwide, but many schools and universities have failed to keep up with their learning needs. Consequently, large numbers of disabled students are dropping out of school or university. Open Educational Resources (OER) and Open Educational Practices (OEP) contain several relevant features, including the possibility of reusing and remixing, which have led researchers to consider using OER and OEP to facilitate meeting the needs of disabled and functional-diverse students in order to increase their accessibility and e-inclusion capabilities in educational settings. The very limited research to date, however, has provided a limited holistic understanding of accessibility within OER and OEP in order to aid researchers in pursuing future directions in this field. Therefore, this paper systematically reviewed 31 papers to provide insights about functional diversity within OER and OEP. The results obtained highlighted that accessibility is still in its infancy within OER and that researchers should focus more on considering the four accessibility principles — perceivable, operable, understandable and robust — when providing OER. Additionally, while several researchers have focused on several issues related to accessibility within OER, limited focus has been given to assistive technologies using OER. Finally, this paper provides several recommendations to increase accessibility within OER and help design more accessible OER for students with functional diversity.

This paper presents a neural network-based classifier to predict whether a person is at risk of developing chronic kidney disease (CKD). The model is trained with the demographic data and medical care information of two population groups: on the one hand, people diagnosed with CKD in Colombia during 2018, and on the other, a sample of people without a diagnosis of this disease. Once the model is trained and evaluation metrics for classification algorithms are applied, the model achieves 95% accuracy in the test data set, making its application for disease prognosis feasible. However, despite the demonstrated efficiency of the neural networks to predict CKD, this machine-learning paradigm is opaque to the expert regarding the explanation of the outcome. Current research on eXplainable AI proposes the use of twin systems, where a black-box machine-learning method is complemented by another white-box method that provides explanations about the predicted values. Case-Based Reasoning (CBR) has proved to be an ideal complement as this paradigm is able to find explanatory cases for an explanation-by-example justification of a neural network's prediction. In this paper, we apply and validate a NN-CBR twin system for the explanation of CKD predictions. As a result of this research, 3,494,516 people were identified as being at risk of developing CKD in Colombia, or 7% of the total population.