The aim of this study is to experimentally assess the effects of an intervention program through a video game called “Aislados” for the improvement of subjective well-being, mental health and trait emotional intelligence of a sample of adolescents (n = 187). We used well-established measures with appropriate psychometric properties. The study used a quasi-experimental design of pre-test/post-test repeated measurements with a control group. First, a multivariate analysis of variance (MANOVA) and then descriptive analyses and variance analyses (ANOVAs) were carried out by the adolescents randomly assigned to the experimental and control conditions. Then, a multivariate analysis of covariance (MANCOVA) was performed on the study’s variables as a whole. Descriptive and covariance analyses of the post-test scores were carried out (ANCOVAs post-test, co-varying pre-test scores), in order to demonstrate the impact of the program. The effect size was reckoned (Cohen’s d). The results confirm statistically-significant differences in: Health-Related Quality of life, positive affect and mental health. The study provides an effective intervention tool which has been experimentally validated. The overall results allow for emphasizing the importance of the implementation of programs aimed at encouraging social and emotional learning throughout adolescence as protective resources in fostering emotional and behavioral adjustment in adolescents.

The objective of the present study was to experimentally assess the effects of a mindfulness-based intervention (MBI) for the improvement of subjective well-being, trait emotional intelligence (TEI), mental health, and resilience in a sample of women with fibromyalgia (FM). The sample consisted of 104 women, between 29 and 77 years old (M = 47.59; SD = 5.93). The measures used were as follows: Satisfaction with Life Scale (SWLS), Positive and Negative Affection Scale (PANAS), Trait Emotional Intelligence Questionnaire Short Form (TEIQue-SF), Mental Health Questionnaire (MH-5), and Resilience Scale (ER-14). A quasi-experimental design of repeated measures with a control group (CG) was used: before and after the application of the treatment and a follow-up assessment 6 months after the completion of the intervention. In order to assess the effect of the program, the participants were randomly assigned to the experimental and control conditions. In the pretest evaluation, a multivariate analysis of variance (MANOVA) and analysis of variance (ANOVA) were carried out. In the post-test evaluation, a multivariate analysis of covariance (MANCOVA) of the study variables as a whole was performed. Then, descriptive analyses and analysis of covariance (ANCOVA) of the post-test scores (covariate pretest score) were performed. In the follow-up evaluation, a MANCOVA of the study variables as a whole was performed. Then, descriptive and ANCOVA analyses of the follow-up scores (covariate pretest score) were performed. In addition, the effect size was calculated using partial eta-squared (μ²). The post-test results confirmed statistically significant differences in satisfaction with life (SWL), positive affect (PA), mental health, and resilience. The follow-up results showed statistically significant differences in SWL, PA, TEI, mental health, and resilience. The study provides an effective intervention tool that has been validated experimentally. The general results allow the emphasis of the importance of the implementation of MBIs framed in non-pharmacological treatments in FM.

Educational tasks for the development of competencies on the Sustainable Development Goals (SDGs) pose a challenge to educators due to the multidisciplinary and complex nature of these goals. It is necessary to develop innovative educational resources and tools that holistically account for this complexity and highlight the environmental and social components of these goals on an equal footing. A learning tool based on the serious games methodology, called BotBusters, is used to inoculate this type of knowledge and skills among young Europeans through a specific news verification activity. This game has been designed to collect interaction data (logs) and thus perform an analysis of players’ behavior, which allows us to understand their preferences and knowledge of the SDGs (specifically 3, 12, 13 and 15). The data collected yield interesting conclusions about the educational needs of young people in this field, showing their preferences for topics related to the environmental SDGs. This indicates that there is a need to promote awareness of the SDGs on social issues, especially those that require a more collective type of agreement and intervention.

Artificial Intelligence (AI) systems typically inherit biases from their training data, leading to discriminatory outcomes that undermine equity and inclusion. This issue is particularly significant when popular Generative AI (GAI) applications are used in educational contexts. To respond to this challenge, the study evaluates the effectiveness of dialogic reflection-based training for educators in identifying and mitigating biases in AI. Furthermore, it considers how these sessions contribute to the advancement of algorithmic justice and inclusive practices. A key component of the proposed training methodology involved equipping educators with the skills to design inclusive prompts—specific instructions or queries aimed at minimizing bias in AI outputs. This approach not only raised awareness of algorithmic inequities but also provided practical strategies for educators to actively contribute to fairer AI systems. A qualitative analysis of the course’s Moodle forum interactions was conducted with 102 university professors and graduate students from diverse regions of the Dominican Republic. Participants engaged in interactive activities, debates, and practical exercises addressing AI bias, algorithmic justice, and ethical implications. Responses were analyzed using Atlas.ti across five categories: participation quality, bias identification strategies, ethical responsibility, social impact, and equity proposals. The training methodology emphasized collaborative learning through real case analyses and the co-construction of knowledge. The study contributes a hypothesis-driven model linking dialogic reflection, bias awareness, and inclusive teaching, offering a replicable framework for ethical AI integration in higher education.

El proyecto europeo YouVerify! tiene como objetivo desarrollar un programa de cursos y actividades para estimular la alfabetización mediática e informacional (AMI) entre estudiantes, profesionales de la información y profesores de todos los niveles educativos. El diseño de recursos pedagógicos AMI requiere contextualizar el trabajo del estudiante en el mismo tipo de medios y tecnologías de comunicación social en los que hoy accede a la información, y que son parte de sus actividades educomunicativas. El modelo de diseño de cursos masivos en línea sociales, sMOOC, es como una herramienta educomunicativa capaz de implicar a los estudiantes e interesados en actividades colaborativas a través de medios y herramientas sociales. Con una metodología de análisis cuantitativo, a partir de los datos del cuestionario de satisfacción voluntario que aportaron los participantes que realizaron el sMOOC, se estudia el interés de los mismos en los mecanismos de desinformación y las herramientas para la verificación y refutación de noticias falsas. Se revisa su percepción de la metodología social y abierta del sMOOC y su interés en difundir estas nuevas competencias entre sus estudiantes o colaboradores. Como conclusión, se destaca el alto grado de satisfacción que suscitó la iniciativa en la alfabetización con espíritu crítico. También, y gracias al componente social del sMOOC, destacó el interés que mostraron los participantes para desarrollar sus propios proyectos AMI como profesores o influencers.