Teachers’ social–emotional competencies are essential to educational quality. This study aimed to describe the theoretical background and relevance of teachers’ social–emotional competencies. We conducted a systematic review with a critical, theoretical review approach. The results showed that the concept has an increasingly complex history and followed a structured course from 1920 to present. Five main models have been identified: emotional regulation, prosocial classroom, Collaborative Association of Social Emotional Learning, Bar-On emotional intelligence, and emotional intelligence. There are measurement instruments consistent with four of the identified models; however, the model that does not have its own instrument uses different available scales. Specific recommendations are proposed to develop social and emotional competencies in educational public policies, which include school leadership, assessment, and teacher professional training. In conclusion, it is relevant to have clear guidelines that conceive and conceptualize social–emotional competence univocally. These guidelines would allow the design of instruments with a comprehensive and sufficient theoretical base that reflect the multidimensionality of the concept, provide a precise measure to assess the effectiveness of intervention programs, and enlist teachers who seek the development of the different skills that involve social–emotional competencies.

Self-regulation is relevant to understanding the teaching–learning process; however, few studies have focused on teachers’ self-regulatory processes. The aim of this study was to characterize and analyze the relationship between teachers’ and students’ self-regulation. The design was cross-sectional and correlational. The sample consisted of 1481 participants (students n = 1123 and teachers n = 358) from 25 secondary schools in 17 cities of the Biobío region of Chile. In students, self-regulatory strategies were found to be deployed only half of the time; women were more self-regulated, and there was no difference in the levels of self-regulation according to grade. Teachers, it was found, almost always self-regulate their teaching, and the variables that influence their self-regulation are motivation, gender, and age, explaining between 25% and 28% of the variance. Positive and small correlations were evidenced between teacher role disposition with learning performance (rho = 0.10, p < 0.05) and teacher role self-evaluation with both learning performance and self-evaluation of learning in their students (rho = 0.12, p < 0.05). This study provides relevant evidence and proposes changes that could have a positive impact on teacher training and improve current teaching–learning practices in Chile, which would contribute to the quality of education.

Introduction/Objective: The resilience and emotional intelligence of teachers are crucial in order to face the daily educational challenges. To determine the association between teacher’s emotional intelligence and resilience during Emergency Remote Learning. Method: A quantitative approach and a cross-sectional predictive non-experimental design were used. Participants were 1329 teachers from Chilean schools. The WLEIS Emotional Intelligence Scale and the RS-14 resilience scale were used. Spearman correlation analyses and Yuen’s test were used for the comparative analysis by sex, and in the case of comparison by specialty the one-way ANOVA test was used; multiple regressions were performed. Results: High levels of resilience and between medium to high emotional intelligence; significant, positive and high relationship between emotional intelligence and resilience. Both in the emotional regulation variable and in the emotional intelligence variable significant differences were found regarding sex and specialty. The results of the predictive model with all emotional intelligence variables as predictors explained 43.5% of the observed variability of resilience. Conclusion: During the pandemic, teachers’ emotional intelligence and resilience are essential for facing the educational adversities and challenges that arise as a consequence of a context susceptible to constant and deregulatory change.

Due to the COVID-19 pandemic, students worldwide have continued their education remotely. One of the challenges of this modality is that students need access to devices such as laptops and smartphones. Among these options, smartphones are the most accessible because of their lower price. This study analyzes the usage patterns of smartphone users of undergraduate Science, Technology, Engineering, and Math (STEM) students during the COVID-19 pandemic. This cross-sectional descriptive study included 365 students: 162 (44.4%) women and 203 (55.6%) men from a Chilean university. The results revealed that students often accessed the learning management system (LMS) with their computers rather than with their smartphones. Students were connected to the LMS for more hours on their computers than on their smartphones. However, they spent more hours simultaneously connected on their computers and smartphones than just on their computers. During the day, students accessed the LMS mainly from 13:00 to 1:00. The number of connections decreased from 1:00 to 8:00 and increased from 8:00 to 13:00. The LMS resource that students accessed the most using smartphones was discussion forums, while the one they accessed the least was wiki pages. We expect these results to motivate faculties to schedule their activities during the hours students tend to be online and promote discussion forums.

The Learning Management Systems (LMS) have garnered attention in Higher Education due to their significant potential as a robust learning tool; however, their mere existence does not guarantee adoption and acceptance. The objective of this study was to analyze quantitative research on the intention and usage of LMS among university professors. The method employed was a systematic review following PRISMA guidelines. Databases such as Scopus, WOS, EBSCOhost, and SciElo were explored from 2013 to 2023. The results indicated that (a) the most frequent objective was to determine factors influencing LMS usage, (b) the average number of participants was 239, (c) the highest productivity (61%) was observed in Asia, (d) the most common limitation about the sample, (e) the most frequently used theoretical model (69%) was the Technology Acceptance Model, (f) the models also included other variables grouped into personal, technological, social, and institutional factors; (g) The predictive power of the models on LMS usage intention was moderate, while for current LMS usage, it ranged from small to moderate; (h) measurements were self-reported; (i) ultimately, the majority measured only the intention of LMS usage (54%), 15% measured only the current usage of LMS, and 31% measured both. In conclusion, limitations, future research directions, and recommendations for the integration and consolidation of LMS usage by faculty are presented.

Introducción. El ingreso de la juventud a la universidad es un periodo desafiante e importante para su vida, tanto en términos académicos como personales. Se requiere disponer de un conjunto de habilidades que le permitan ajustarse satisfactoriamente a las demandas del nuevo contexto educativo. El ajuste a la vida universitaria se vuelve una variable clave, dado que permite hacer frente a los requisitos de motivación, ejecución y rendimiento propios de la experiencia universitaria en los ámbitos, académicos, sociales, institucionales y personales del estudiantado. Por tanto, es necesario conocer aquellas variables que predicen un adecuado ajuste del estudiantado para proponer intervenciones oportunas de mejora. Objetivo. Evaluar la capacidad predictiva del engagement y la motivación académica en el ajuste de estudiantado universitario. Metodología. Diseño predictivo-transversal, participaron 512 estudiantes de primer año de una universidad tradicional en Chile (hombres= 297; mujeres= 215). Promedio de edad 19 años (DE=1.49). Resultados. Los modelos de regresión propuestos fueron estadísticamente significativos. El engagement fue el mayor predictor del ajuste académico (β =.511; p<.01; r2=.40), institucional (β=.30; p<.01; r2=.37), social (β =.29; p<.01; r2=.15) y personal-emocional (β = .30; p<.01; r2=.10), seguido de la motivación autónoma. Conclusiones. El engagement académico es relevante no solo en la promoción del rendimiento académico, sino también en los procesos de integración y adaptación del estudiantado en el contexto universitario. Recomendaciones. Para contribuir con el ajuste del estudiantado durante los primeros años, se hace relevante la implementación de estrategias que potencien el engagement académico y la motivación autónoma.