This study focuses on the relationships established between the elements that compose the community of inquiry (CoI): cognitive, social, and teaching presence. Using three questionnaires, we analyse the students’ perception of synchronous and asynchronous virtual in text-based communication (chats, forums and emails). Starting from the high correlations found between the three elements, we perform a multiple linear regression analysis. The findings show that relationships can be established in the model in which the cognitive elements are strongly predicted, to a greater extent by social presence than by teaching presence. In the forums the cognitive presence is better explained by other presences than in chats and emails. The results reveal the need to analyse the three kinds of presence jointly, assessing the impact of each on student learning. We also determine that the instructor benefits from knowing which tool is more valid for the learning objectives.

This work involves the content validation of a semi-structured interview, whose objective is to learn about the management of suffering in people. The interview items have been classified into several categories that define the suffering construct. For the content validation of the instrument, in addition to initially conducting a scientific review on the subject, the procedure known as expert judgement has been used. The results obtained in terms of the content validity achieved in the dimensions and areas assessed are, in general, satisfactory. However, some of these dimensions and certain areas have not exceeded the required minimum values for content validity. Therefore, it is necessary to modify the items comprising these dimensions in the areas evaluated with the additional incorporation of the qualitative suggestions for improvement indicated by the experts. As for agreement among experts, the results point to moderate agreement, which, moreover, is not due to chance.

The present study seeks to map and visualize up-to-date perspectives of the topic of active learning by analyzing and interpreting the different elements that make up learning ecosystems within the European Higher Education Area. With this aim, scientometric methods were employed to analyze a sample of 474 articles recovered from Web of Science (WoS) during the three-year period between 2018 and 2020. All articles examined the topic of active learning. Keywords (authors’ keywords and ‘keywords plus’) from the manuscripts were examined through co-occurrence analysis in order to establish the conceptual structure of active learning. Among the different trends and emerging topics identified, there is an important presence of topics related to technology applied to the field of education, where digital contexts acquire a preponderant role in current education. These innovative changes focused on the digital updating and exploitation of technology represent a methodological challenge that requires an involvement and commitment to this new space for educational practice by teachers and students.

The work addresses the criticism of the exclusive reliance on statistical significance (SS) in scientific research and proposes the use of effect size (ES) as a more robust and explanatory alternative. Two main weaknesses of SS are highlighted: its dependence on sample size and the arbitrariness of the p-value threshold (generally 0.05). These limitations can lead to misinterpretations and questionable practices such as "p-hacking" or data dredging. Effect size is presented as a quantitative measure of the magnitude of a phenomenon, independent of sample size, facilitating comparison between studies and diverse contexts. It is classified into various typologies: mean differences (Cohen's d, Hedges' g, Glass' Δ), correlations (Pearson's r, r²), analysis of variance (η², ω², Cohen's f), and odds ratios (Odds Ratio, Risk Ratio). The interpretation of ES varies according to context, but general guidelines suggest that values such as 0.2, 0.5, and 0.8 in Cohen's d represent small, medium, and large effects, respectively. Finally, a practical example is included to illustrate the application of these measures and how SS and ES can lead to contrasting conclusions. Resumen El texto aborda la crítica a la dependencia exclusiva de la significación estadística en la investigación científica y propone el uso del tamaño del efecto (TE) como una alternativa más robusta y explicativa. Se destacan dos principales debilidades de la significación estadística: su dependencia del tamaño muestral y la arbitrariedad del umbral del valor p (generalmente 0.05). Estas limitaciones pueden llevar a interpretaciones erróneas y prácticas cuestionables como el "p-hacking" o dragado de datos. El tamaño del efecto se presenta como una medida cuantitativa de la magnitud de un fenómeno, independiente del tamaño de la muestra, que facilita la comparación entre estudios y contextos diversos. Se clasifica en varias tipologías: diferencias de medias (d de Cohen, g de Hedges, Δ de Glass), correlaciones (r de Pearson, r²), análisis de varianza (η², ω², f de Cohen) y razones de probabilidades o cuotas (Odds Ratio, Risk Ratio). La interpretación del TE varía según el contexto, pero guías generales sugieren que valores como 0.2, 0.5 y 0.8 en d de Cohen representan efectos pequeños, medianos y grandes, respectivamente. Finalmente, se incluye un ejemplo práctico para ilustrar la aplicación de estas medidas y como la significación estadística y los tamaños del efecto pueden llegar a conclusiones contrarias.

The aim of this study was to design, develop, and validate a questionnaire evaluating attitudes toward refugee children. Method: The questionnaire was analyzed using SPSS Software version 21.0 (IBM Corp., 2012, Armonk, NY, USA). Results: Cronbach’s α was greater than 0.9. According to an expert’s review, the instrument provided arithmetic means higher than 2.5, the dimensions evaluated had interclass correlation coefficients greater than 55, and the corrected correlation values of the item-total were greater than 0.35. Conclusions: The Attitude Questionnaire toward Refugee Children was found to be an adequate instrument for better understanding and measuring the attitudes of host countries’ citizens toward refugee children.