Self-other agreement measures of acceptance in predicting academic achievement: A longitudinal analysis

This research focused on sed light to the process that surrounded accuracy perception of acceptance status during adolescence from a non-componential view of social perception. With a longitudinal data of adolescents, mediational models are proposed in order to understand the different types of accuracy measures developed, and how they worked to finally predict academic achievement..

What leads to loneliness?An integrative model of Social, Motivational and Emotional approaches in adolescence

Loneliness has been linked to many physical and mental health problems, especially during adolescence. From evolutionary, social needs, and cognitive approaches, this study examined whether emotional repair, relatedness need, and peer-rated indicators of relations behave in predicting loneliness, considering all approaches together. The sample consisted of 373 adolescents measured longitudinally at three time points. Results of a cross-lagged panel design found that, considering all the influences together, relatedness need showed the highest strength to predict loneliness. Furthermore, adolescents who were accepted by their peers and whose relatedness need was satisfied activated emotional regulation which additionally produced a decrease in prospective feelings of loneliness. In addition, loneliness has been shown to be a consequence of these variables

Perceptions and final academic results in university students. Does the type of exam matter?

Academic achievement results are one of the main goals of university students. This research focused in accuracy perceptions of youths' academic achievement in exam tasks during university studies. The sample comprised students of psychology and teaching education degrees from 1st to 4th courses..

Emptiness in the study of emotions in the teaching-learning process of reading-writing during the COVID-19 pandemic

The teaching-learning process of reading and writing has great relevance in the psycho-emotional and socio-psychological development of school-age children. This is an exercise in which they develop imagination, attention and memory capacity and through this process the management of emotions and sensitivity and capacity of apprehension of reality. The crisis derived from the COVID-19 pandemic transformed reality in an unprecedented way in the recent history of humanity and the educational context was shaken by all these changes. With confinement, the teaching-learning process of reading and writing, which is designed to take place in person, had to be developed in a hybrid or online way, which was a major challenge for teachers and families and, of course, also for children who were in the process of learning. One of the aspects that was blurred in this context was the role of the teacher, which in this case is one of the most important elements, to achieve adequate learning of reading and writing. On one hand, the teacher is in charge of helping to manage the emotions derived from the learning process itself and, on the other hand, he is a key figure so that this is not only technical learning but also contributes to the child’s socio-emotional development. The aim of this study was to analyze the impact of the socio-psychological changes that have occurred in the educational context since the COVID-19 pandemic on the emotions linked to the teaching process, learning of reading and writing through a systematic review of the studies carried out on the subject, in order to provide recommendations for face-to-face learning in the post- COVID-19 era. A systematic review strategy was devised and the literature search was conducted. The search was conducted using ERIC, Dialnet, Scopus, WoS, EBSCO, and Google Scholar databases. This systematic review took place during the month of May 2022. The results show that given the scarce presence of empirical studies on the subject, the objective has only been partially met. However, a systematic review of the studies carried out on the subject. For the identification of recommendations in the development of face-to-face learning in the post-covid era, it has been possible to identify some ideas of interest for future curricular designs in primary school students who are immersed in learning to read and write

Integrating artificial intelligence to assess emotions in learning environments: a systematic literature review

IntroductionArtificial Intelligence (AI) is transforming multiple sectors within our society, including education. In this context, emotions play a fundamental role in the teaching-learning process given that they influence academic performance, motivation, information retention, and student well-being. Thus, the integration of AI in emotional assessment within educational environments offers several advantages that can transform how we understand and address the socio-emotional development of students. However, there remains a lack of comprehensive approach that systematizes advancements, challenges, and opportunities in this field.AimThis systematic literature review aims to explore how artificial intelligence (AI) is used to evaluate emotions within educational settings. We provide a comprehensive overview of the current state of research, focusing on advancements, challenges, and opportunities in the domain of AI-driven emotional assessment within educational settings.MethodThe review involved a search across the following academic databases: Pubmed, Web of Science, PsycINFO and Scopus. Forty-one articles were selected that meet the established inclusion criteria. These articles were analyzed to extract key insights related to the integration of AI and emotional assessment within educational environments.ResultsThe findings reveal a variety of AI-driven approaches that were developed to capture and analyze students’ emotional states during learning activities. The findings are summarized in four fundamental topics: (1) emotion recognition in education, (2) technology integration and learning outcomes, (3) special education and assistive technology, (4) affective computing. Among the key AI techniques employed are machine learning and facial recognition, which are used to assess emotions. These approaches demonstrate promising potential in enhancing pedagogical strategies and creating adaptive learning environments that cater to individual emotional needs. The review identified emerging factors that, while important, require further investigation to understand their relationships and implications fully. These elements could significantly enhance the use of AI in assessing emotions within educational settings. Specifically, we are referring to: (1) federated learning, (2) convolutional neural network (CNN), (3) recurrent neural network (RNN), (4) facial expression databases, and (5) ethics in the development of intelligent systems.ConclusionThis systematic literature review showcases the significance of AI in revolutionizing educational practices through emotion assessment. While advancements are evident, challenges related to accuracy, privacy, and cross-cultural validity were also identified. The synthesis of existing research highlights the need for further research into refining AI models for emotion recognition and emphasizes the importance of ethical considerations in implementing AI technologies within educational contexts

New Insights on Structures Forming the Lignin-Like Fractions of Ancestral Plants

In the present work, lignin-like fractions were isolated from several ancestral plants –including moss (Hypnum cupressiforme and Polytrichum commune), lycophyte (Selaginella kraussiana), horsetail (Equisetum palustre), fern (Nephrolepis cordifolia and Pteridium aquilinum), cycad (Cycas revoluta), and gnetophyte (Ephedra fragilis) species– and structurally characterized by pyrolysis-gas chromatography-mass spectrometry (Py-GC/MS) and two-dimensional nuclear magnetic resonance (2D-NMR) spectroscopy. Py-GC/MS yielded marker compounds characteristic of lignin units, except in the H. cupressiforme, P. commune and E. palustre “lignins, ” where they were practically absent. Additional structural information on the other five samples was obtained from 2D-NMR experiments displaying intense correlations signals of guaiacyl (G) units in the fern and cycad lignins, along with smaller amounts of p-hydroxyphenyl (H) units. Interestingly, the lignins from the lycophyte S. kraussiana and the gnetophyte E. fragilis were not only composed of G- and H-lignin units but they also incorporated significant amounts of the syringyl (S) units characteristic of angiosperms, which appeared much later in plant evolution, most probably due to convergent evolution. The latter finding is also supported by the abundance of syringol derivatives after the Py-GC/MS analyses of these two samples. Regarding lignin structure, β−O−4′ alkyl-aryl ethers were the most abundant substructures, followed by condensed β−5′ phenylcoumarans and β−β′ resinols (and dibenzodioxocins in the fern and cycad lignins). The highest percentages of alkyl-aryl ether structures correlated with the higher S/G ratio in the S. Kraussiana and E. fragilis lignin-like fractions. More interestingly, apart from the typical monolignol-derived lignin units (H, G and S), other structures, assigned to flavonoid compounds never reported before in natural lignins (such as amentoflavone, apigenin, hypnogenol B, kaempferol, and naringenin), could also be identified in the HSQC spectra of all the lignin-like fractions analyzed. With this purpose, in vitro synthesized coniferyl-naringenin and coniferyl-apigenin dehydrogenation polymers were used as standards. These flavonoids were abundant in H. cupressiforme appearing as the only constituents of the moss lignin-like fraction (including 84% of dimeric hypnogenol B) and their abundance decreased in those of S. Kraussiana (with amentoflavone and naringenin representing 14% of the total aromatic units), and the two ancient gymnosperms (0.4–1.2%) and ferns (0–0.7%)

Cultural and leadership predictors of corporate social responsibility values of top management: A GLOBE study of 15 countries.

This paper examines cultural and leadership variables associated with corporate social responsibility values that managers apply to their decision-making. In this longitudinal study, we analyze data from 561 firms located in 15 countries on five continents to illustrate how the cultural dimensions of institutional collectivism and power distance predict social responsibility values on the part of top management team members. CEO visionary leadership and integrity were also uniquely predictive of such values. Journal of International Business Studies (2006) 37, 823–837. doi:10.1057/palgrave.jibs.8400230

European Diploma in Psychology: a Common Framework for Psychology Education in Europe

No abstract available

European Diploma in Psychology: a Common Framework for Psychology Education in Europe

No abstract available

Un programa informático para el cálculo y la representación de índices y valores sociométricos

Validation of the Rivermead Behavioural Memory Test (rbmt) in a sample of spanish population over 70 years old. The Rivermead Behavioural Memory Test (RBMT) is a test for detecting everyday memory problems. Recently, a Spanish version of the RBMT has been published although without information about its reliability and validity, and without norms for the interpretation of the scores in Spanish populations. In order to correct this problem, studies with samples of Spanish children have been conducted. Nevertheless, there are no norms available for the elder population, a group of special importance given the high incidence of memory problems and complains usually associated to aging. The purpose of the present study was to validate the test and to obtain norms for the interpretation of the RBMT scores in the Spanish population over 70. Data about validity and reliability of the test are presented, along with the norms for the interpretation of scores in this age group.El Test Conductual de Memoria de Rivermead (RBMT) es una prueba destinada a detectar problemas de memoria de la vida cotidiana. Recientemente, ha aparecido una versión en español del RBMT aunque sin información acerca de su fiabilidad, validez y sin normas sobre la interpretación de las puntuaciones con población española. Para subsanar este problema se han realizado estudios con muestras de niños españoles. Sin embargo, se carece de normas para la población anciana, un colectivo de especial importancia por ser donde se centra el mayor número de quejas y déficits relacionados con el funcionamiento de la memoria. El presente trabajo tiene como finalidad la validación y obtención de normas de interpretación del RBMT con población española mayor de 70 años. Se presentan datos acerca de la validez y fiabilidad de la prueba, así como de las normas de interpretación para este colectiv