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Las primeras experiencias de educación al desarrollo en España están vinculadas al nacimiento de las primeras organizaciones no gubernamentales que surgieron en España en la década de los años 50-60. La educación al desarrollo fue el instrumento que se pusieron al servicio de la sociedad española como medio para poder luchar, desde la concienciación, la corresponsabilidad y la fraternidad de todos los seres humanos, contra la pobreza y la desigualdad. En el presente artículo, se aborda las acciones de sensibilización y educación para el desarrollo de una de estas primeras organizaciones, Manos Unidas antes de la puesta en marchar de los boletines informativos periódicos.

El cambio climático, el desarrollo de la inteligencia artificial o la evolución de las democracias son los nuevos escenarios que tendrán que afrontar las generaciones del siglo XXI. Es por ello que, desde instancias internacionales como la UNESCO o la OCDE, se demande el tránsito de un modelo educativo disciplinar y especializado hacia un nuevo modelo transdisciplinar que capacite al alumnado para responder a los retos de un mundo global cada vez más complejo. La transdisciplinariedad implica el diálogo entre los diferentes ámbitos del conocimiento, los valores, la participación y el aprendizaje social. Esto conlleva a su vez una transformación cultural y una reorganización sistemática y planificada de la estructura y las metodologías educativas. El objetivo del presente artículo -de naturaleza teórica- es profundizar en la correcta compresión del modelo educativo transdisciplinar y establecer un marco conceptual claro que permita su definición y medición. Para ello se identifica el desarrollo del proceso de enseñanza-aprendizaje, las competencias a desarrollar, las diferentes metodologías contrastadas, los sistemas de evaluación y los entornos de aprendizaje.

El derecho a la educación, reconocido como derecho fundamental en 1948, ha asumido la innovación como práctica necesaria para aumentar la calidad de sus procesos y resultados. Los esfuerzos de los últimos veinte años en este sentido se han visto acelerados debido a la situación de pandemia. La adaptación a los entornos virtuales ha sufrido un cambio fruto de la propia evolución social y cultural, en los primeros años del nuevo milenio como recomendación y desde 2020 como proceso obligatorio y necesario. La pandemia de COVID-19 generó una coyuntura inédita que impactó en la sociedad en su conjunto y obligó a replantear todo el sistema educativo durante el confinamiento y el curso posterior. Esto ocasionó una serie de problemas que condicionaron la educación y su normal desarrollo entre todos los miembros que componen la comunidad educativa y, especialmente, entre los docentes y los discentes. En la presente investigación, se examinan de manera descriptiva los resultados de aprendizaje mediante el análisis de las notas de diversas asignaturas de los grados de Educación. Los resultados obtenidos, las lecciones extraídas, las prácticas consolidadas y los retos a futuro se proyectan como elementos fundamentales para entender los profundos cambios operados en la educación.

Abstract Background Cardiovascular diseases (CVDs) prevalence has significantly increased in the last decade and atherosclerosis development is the main trigger. MicroRNAs (miRNAs) are non‐coding RNAs that negatively regulate gene expression of their target and their levels are frequently altered in CVDs. Methods By RT‐qPCR, we analysed miR‐9‐5p, miR‐15a‐5p, miR‐16‐5p and miR‐199a‐3p levels in aorta from apolipoprotein knockout (ApoE−/−) mice, an experimental model of hyperlipidemia‐induced atherosclerosis, and in human aortic and carotid atherosclerotic samples. By in silico studies, Western blot analysis and immunofluorescence studies, we detected the targets of the altered miRNAs. Results Our results show that miR‐15a‐5p and miR‐199a‐3p are significantly decreased in carotid and aortic samples from patients and mice with atherosclerosis. In addition, we found an increased expression in targets of both miRNAs that participate in the inflammatory pathway of nuclear factor kappa B (NF‐κB), such as IKKα, IKKβ and p65. In human vein endothelial cells (HUVECs) and vascular smooth muscle cells (VSMCs), the overexpression of miR‐15a‐5p or miR‐199a‐3p decreased IKKα, IKKβ and p65 protein levels as well as NF‐κB activation. On the other hand, miR‐15a‐5p and miR‐199a‐3p overexpression reduced ox‐LDL uptake and the inflammation regulated by NF‐κB in VSMCs. Moreover, although miR‐15a‐5p and miR‐199a‐3p were significantly increased in exosomes from patients with advanced carotid atherosclerosis, only in the ROC analyses for miR‐15a‐5p, the area under the curve was 0.8951 with a p value of .0028. Conclusions Our results suggest that the decrease of miR‐199a‐3p and miR‐15a‐5p in vascular samples from human and experimental atherosclerosis could be involved in the NF‐κB activation pathway, as well as in ox‐LDL uptake by VSMCs, contributing to inflammation and progression atherosclerosis. Finally, miR‐15a‐5p could be used as a novel diagnostic biomarker for advanced atherosclerosis.

The extent to which learners benefit from instruction may be largely dependent on their individual abilities. However, there is relatively little work on the interaction between instructional effectiveness in second language learning and learner individual factors. In this study, we investigated the relationship between instruction, individual differences in cognitive abilities (working memory and declarative memory), and second language vocabulary acquisition in the context of web-based intelligent computer assisted language learning (ICALL). To this end, 127 adult learners of English, predominantly advanced-level, German-speaking learners, read news texts on the web for about two weeks using an ICALL system under two instructional conditions: form-focused and meaning-focused instruction. Learners in the form-focused condition read and completed automatically-generated multiple-choice gaps where phrasal verbs appeared in the text, while learners in the meaning-focused condition simply read and did not complete any gaps. Mixed-effects regression analyses showed that working memory was associated with vocabulary acquisition and that this association depended on the instructional context, with working memory being predictive of learning only in the form-focused condition, suggesting an aptitude-treatment interaction. Furthermore, declarative memory abilities were related to learning only as measured by the Continuous Visual Memory Task, and the relationship was not moderated by instructional condition. Overall, the study contributes to accounting for variability in second language learning in general, as well as in instructional contexts supported by intelligent CALL.

First language acquisition is implicit, in that explicit information about the language structure to be learned is not provided to children. Instead, they must acquire both vocabulary and grammar incrementally, by generalizing across multiple situations that eventually enable links between words in utterances and referents in the environment to be established. However, this raises a problem of how vocabulary can be acquired without first knowing the role of the word within the syntax of a sentence. It also raises practical issues about the extent to which different instructional conditions -- about grammar in advance of learning or feedback about correct decisions during learning -- might influence second language acquisition of implicitly experienced information about the language. In an artificial language learning study, we studied participants learning language from inductive exposure, but under different instructional conditions. Language learners were exposed to complex utterances and complex scenes and had to determine the meaning and the grammar of the language from these co-occurrences with environmental scenes. We found that learning was boosted by explicit feedback, but not by explicit instruction about the grammar of the language, compared to an implicit learning condition. However, the effect of feedback was not general across all aspects of the language. Feedback improved vocabulary, but did not affect syntax learning. We further investigated the local, contextual effects on learning, and found that previous knowledge of vocabulary within an utterance improved learning but that this was driven only by certain grammatical categories in the language. The results have implications for theories of second language learning informed by our understanding of first language acquisition as well as practical implications for learning instruction and optimal, contingent adjustment of learners' environment during their learning.

How can state-of-the-art computational linguistic technology reduce the workload and increase the efficiency of language teachers? To address this question, we combine insights from research in second language acquisition and computational linguistics to automatically generate text-based questions to a given text. The questions are designed to draw the learner's attention to target linguistic forms -- phrasal verbs, in this particular case -- by requiring them to use the forms or their paraphrases in the answer. Such questions help learners create form-meaning connections and are well suited for both practice and testing. We discuss the generation of a novel type of question combining a "wh"- question with a gapped sentence, and report the results of two crowdsourcing evaluation studies investigating how well automatically generated questions compare to those written by a language teacher. The first study compares our system output to gold standard human-written questions via crowdsourcing rating. An equivalence test shows that automatically generated questions are comparable to human-written ones. The second crowdsourcing study investigates two types of questions ("wh"- questions with and without a gapped sentence), their perceived quality, and the responses they elicit. Finally, we discuss the challenges and limitations of creating and evaluating question-generation systems for language learners.

Despite the promise of research conducted at the intersection of computer-assisted language learning (CALL), natural language processing, and second language acquisition, few studies have explored the potential benefits of using intelligent CALL systems to deepen our understanding of the process and products of second language (L2) learning. The strategic use of technology offers researchers novel methodological opportunities to examine how incremental changes in L2 development occur during treatment as well as how the longitudinal impacts of experimental interventions on L2 learning outcomes occur on a case-by-case basis. Drawing on the pilot results from a project examining the effects of automatic input enhancement on L2 learners' development, this article explores how the use of technology offers additional methodological and analytical choices for the investigation of the process and outcomes of L2 development, illustrating the opportunities to study what learners do "during" visually enhanced instructional activities.

Second language learning outcomes are highly variable, due to a variety of factors, including individual differences, exposure conditions, and linguistic complexity. However, exactly how these factors interact to influence language learning is unknown. This article examines the relationship between these three variables in language learners. Native English speakers were exposed to an artificial language containing three sentence patterns of varying linguistic complexity. They were randomly assigned to two groups--incidental and instructed--designed to promote the acquisition of implicit and explicit knowledge, respectively. Learning was assessed with a grammaticality judgment task, and subjective measures of awareness were used to measure whether exposure had resulted in implicit or explicit knowledge. Participants also completed cognitive tests. Awareness measures demonstrated that learners in the incidental group relied more on implicit knowledge, whereas learners in the instructed group relied more on explicit knowledge. Overall, exposure condition was the most significant predictor of performance on the grammaticality judgment task, with learners in the instructed group outperforming those in the incidental group. Performance on a procedural learning task accounted for additional variance. When outcomes were analyzed according to linguistic complexity, exposure condition was the most significant predictor for two syntactic patterns, but it was not a predictor for the most complex sentence group; instead, procedural learning ability was.

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