Facultad de Ciencias Sociales y Humanas

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    Mapping Adolescent Well-Being: A Network Analysis of Subjective and Psychological Well-being in Ecuador
    (Springer Science and Business Media LLC, 2026-07-24)
    Moreta-Herrera, Rodrigo
    ;
    Salinas-Palma, Alexandra
    ;
    Gavilanes Gomez , Guillermo Daniel  
    ;
    Rodas, Jose A.
    ;
    Jara-Rizzo, Maria F.
    The objective is to identify the relationship between Subjective Well-being (SWB) and Psychological Well-being (PWB) in a sample of Ecuadorian adolescents, as well as to explore gender differences using a psychological network approach. A descriptive, relational, cross-sectional study employing psychological network analysis was conducted. A total of 567 adolescents participated, 57.1% were girls and 42.9% boys, aged between 12 and 18 years (M = 15.87, SD = 1.31). These adolescents were enrolled in 15 educational institutions across three provinces of Ecuador. The results show that SWB and PWB form a stable network with bridge nodes connecting the two theoretical communities, indicating co-occurrence, particularly through nodes associated with the cognitive component of SWB and mediated by affect. Gender-based comparisons revealed no significant differences between boys and girls, indicating an absence of differences in the network. It is concluded that the BS-BP network reveals specific mechanisms through which these components connect and their importance within the theoretical model of hedonic and eudaimonic well-being. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2026.
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    Data-Driven Profiling of Reading Processes in Secondary Students: Learning Analytics Insights From PROLEC Assessment
    (Springer Nature Switzerland, 2026)
    Espinosa Pinos, Carlos Alberto  
    ;
    Núñez Torres, María Giovanna  
    The integration of Learning Analytics (LA) into traditional psychometric assessments offers a transformative path for personalizing secondary education. This study proposes a “psychometric-first” analytical pipeline that converts item-level responses from the PROLEC-SE-R battery into actionable learner models for Interactive Learning Ecosystems (ILE). Using data from 256 Ecuadorian secondary students, we applied Categorical Principal Component Analysis (CATPCA) to address the ordinal nature of the psychometric data, identifying four latent dimensions of reading: lexical, syntactic, semantic, and integration processes. Subsequently, a k-means clustering algorithm identified three distinct cognitive profiles: At-Risk (12.0%), Average (56.8%), and High-Performance (31.2%). The internal validity of these clusters was confirmed through a Davies-Bouldin index of 1.206 and stability analysis via Jaccard bootstrapping. To bridge the gap between psychometric profiling and Human-Computer Interaction (HCI), we developed a rule-based mapping for UI/UX adaptations, where profiles trigger differentiated scaffolding—such as intensive audio-support for at-risk students and complex inferential challenges for high-performers. Results demonstrate that this scalable approach provides a theoretically grounded alternative to hardware-dependent analytics (e.g., eye-tracking) in low-resource contexts. This study contributes to the field of educational data mining by operationalizing latent cognitive features into dynamic instructional interventions, fostering more inclusive and adaptive digital learning environments. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.
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    Vocational guidance and personality traits in adolescents: a systematic review of broad personality models and RIASEC associations with vocational outcomes
    (Frontiers Media SA, 2026-06-25)
    Faz Tapia , Andrea Nicole  
    ;
    Jaramillo-Cumbicus, Kayla
    ;
    Faz-Cevallos, Eduardo
    Background The associations between broad personality traits, as captured by the Big Five and related taxonomies and vocational outcomes (career maturity, career decision-making self-efficacy, vocational identity, vocational interests, and the congruence between RIASEC vocational personality and career aspirations) constitute an important field of inquiry for understanding adolescents' career development. Objective The aim of this systematic review was to synthesize the available scientific evidence (2020-2025) on these associations in adolescents, and to examine, where reported, the congruence between RIASEC vocational personality profiles and career aspirations. Methods The review followed the PRISMA 2020 guidelines. Searches were conducted in four databases (PubMed, Scopus, EBSCO, and ERIC) using three complementary search strings, in addition to a manual search. Inclusion criteria comprised: empirical studies of adolescents aged 12-18 years (or with a mean age within this range), published between 2020 and 2025 in English or Spanish, that explicitly examined associations between personality traits assessed under the Big Five model, the HEXACO model (which shares four broad factors with the Big Five), or Holland's RIASEC vocational interests model, and at least one vocational variable (career decision-making, vocational identity, vocational interests, career choice, or career maturity). From a total of 242 records identified, 14 studies were included in the qualitative synthesis. Results Conscientiousness and openness to experience are positive correlates of career maturity, career decision-making self-efficacy, and vocational identity in several, though not all, of the included studies; the strength and direction of the conscientiousness-outcome association varied across vocational outcomes and depended on which other predictors (e.g., RIASEC interests, self-efficacy) were modeled. Neuroticism (and its HEXACO counterpart, Emotionality) was consistently associated with greater decisional difficulties and lower vocational commitment. Studies that applied Holland's RIASEC model to assess vocational interests yielded mixed evidence on cross-cultural congruence: in the small number of studies available (one per cultural context), moderate congruence was observed in a collectivistic Asian sample, while low congruence was reported in a rural Latin American context. These context-specific patterns should be interpreted as preliminary, given that they rest on a single study per cultural setting. Discussion Significant gaps were identified in longitudinal studies, personality-based interventions, and evidence from Latin America. These findings underscore the value of integrating personality trait assessment into vocational guidance programs for adolescents, while acknowledging that the contribution of any single trait depends on contextual and outcome-specific factors. Systematic review registration: https://osf.io/zmdks , identifier 10.17605/OSF.IO/ZMDKS.
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    Loneliness, Emotional Fatigue, Social Dysfunction, and Suicide Risk in Ecuadorian University Students: A Mediation Analysis
    (Russian Psychological Society, 2026)
    Moreta-Herrera, Rodrigo
    ;
    Gordón-Villalba, Paulina
    ;
    Rodas, Jose A.
    ;
    Cuesta Andaluz, Evelyn Esther  
    ;
    Revelo-Sánchez, Priscila
    Background. Suicidal risk in university students does not require analysis solely from clinical parameters; it is also necessary to understand it from the perspective of psychosocial factors and the everyday life situations to which the students are mostly exposed. Furthermore, it is a phenomenon with multiple causes, so studying it by integrating the complexity of various actors can help us understand not only direct dynamics but also indirect, multifaceted ones. Objective. To estimate a sequential and latent multiple mediation model of emotional fatigue and social dysfunction in the relationship between loneliness and suicidal risk in Ecuadorian university students. Design. A descriptive, cross-sectional, multiple mediation study using structural equation modelling (SEM). The sample comprised 943 undergraduate students (64.4% women, 35.6% men) from six universities (61.1% public) in four Ecuadorian cities, aged between 18 and 47 years (M=21.62, SD=3.81). Results. Loneliness, emotional fatigue, and social dysfunction are latent predictors of suicidal risk, explaining 60% of its variance. Loneliness exerts both a direct effect on suicide risk and an indirect effect through the sequential multiple mediation of emotional fatigue and social dysfunction. Conclusion. Academic risk factors such as loneliness, emotional fatigue, and social dysfunction are key attributes to consider for preventing suicidal behavior in university students. These predictors can dynamically interact to generate both direct and indirect effects, allowing for a better understanding of the complexity of this phenomenon. © Moreta-Herrera, R., Gordón-Villalba, P., Rodas, J.A., Cuesta-Andaluz, E., Revelo-Sánchez, P., 2026.
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    The emotional cost of service: a comparison between health and education professionals
    (2025)
    Albuja Urvina, María Gabriela  
    ;
    Daphne S. Narváez-Almeida
    There is an emotional toll on healthcare workers and also on educators, who experience stress and trauma in their daily work. The objective of this study is to compare the manifestation of Compassion Fatigue and Compassion Satisfaction in these two groups. To measure this emotional toll, the PROQoL IV test was administered. The results showed that while both groups experience greater Compassion Fatigue the longer they have been in their profession, it is educators who show a deeper burnout. It is suggested that future tools be developed to enable teachers to manage these situations effectively without compromising their quality of life. © 2025 IEEE.
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    Beyond Linear Statistics: A Machine Learning Ecosystem for Early Screening of School Bullying
    (2026)
    Espinosa Pinos, Carlos Alberto  
    ;
    Paúl Bladimir Acosta-Pérez
    ;
    Aitor Larzabal-Fernández
    ;
    Francisco Sebastián Vaca-Pinto
    This study developed and validated a Machine Learning (ML) ecosystem for the early screening of school victimization among Ecuadorian adolescents, a phenomenon that poses a critical barrier to educational equity. Addressing previous methodological limitations, this research intentionally eliminated circular reasoning by excluding all internal psychometric items from the feature set, focusing strictly on sixteen socio-environmental and demographic predictors. A quantitative study was conducted with 1413 students in the province of Tungurahua, utilizing the Synthetic Minority Over-sampling Technique (SMOTE) to correct class imbalance. Supervised classification algorithms, including SVM, Random Forest, and XGBoost, were compared. The results demonstrated that the Random Forest model achieved the most balanced performance, reaching an Accuracy of 60.3% and a Macro F1-score of 0.382. Feature importance analysis identified household structure (Living_With_Monoparental) and Family_Coping_Capacity as the most significant predictors of high-risk profiles. These findings provided a statistically honest and ecologically valid tool for Student Counseling Departments (DECE), enabling a transition toward proactive risk identification grounded in observable social vulnerability rather than reactive symptom reporting.
      5
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    Propiedades psicométricas del European Bullying Intervention Project Questionnaire (EBIPQ) y el European Cyberbullying Intervention Project Questionnaire (ECIPQ) en una muestra de adolescentes del Ecuador
    (2025)
    Evelyn Cuesta-Andaluz
    ;
    Rodrigo Moreta-Herrera
    ;
    Lascano Arias, Giovanni  
    ;
    Marco Pino-Falconí
    ;
    Esteban Moreno-Montero
    Introduction: School bullying has sparked considerable research interest, leading to the development of specific measures aimed at assessing both traditional bullying and cyberbullying (CB). Objective: To identify evidence of validity for the European Bullying Intervention Project Questionnaire (EBIPQ) and the European Cyberbullying Intervention Project Questionnaire (ECIPQ) in a sample of Ecuadorian adolescents. Method: A cross-sectional descriptive and psychometric study analyzing the construct validity, internal consistency, and convergent validity of both instruments. Sample: 341 adolescent students (56% female, 44% male), aged 14 to 19 years (M = 15.72; SD = 0.85), from different cities in Ecuador. Results: Oblique fit models with two dimensions per instrument provide the best factor representation. They also demonstrate adequate internal consistency across their dimensions and a high correlation between the two questionnaires. Conclusion: The EBIPQ and ECIPQ prove to be valid, reliable, and relevant instruments for measuring bullying and cyberbullying among adolescents in Ecuador.
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    Gamification for psychomotor development: an experience with Genially in pre-school education
    (2024)
    Núñez-Naranjo, Aracelly Fernanda  
    ;
    Acuña Mayorga, José Miguel  
    ;
    Viviana Lourdes Martinez
    Psychomotor skills in early childhood are notably affected due to the pandemic, which is why the objective of the research was to implement gamified strategies in Genially that seek to improve psychomotor development in early education, the research had a mixed and field approach, with a proposal in which 21 students participated for 4 weeks; before the application of the proposal and after it, tests were applied, where the results obtained fulfilled the expectations of improvement in the teaching process.
      47
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    Design of the Attitudinal Assessment Scale Towards Artificial Intelligence (EVAIA-1)
    (2023)
    Subia Arellano, Andrés  
    ;
    Pérez-Vega D.
    ;
    Guillen-Garcia S.
    ;
    Cáceres-Fierro N.
    In recent years, the exponential growth of artificial intelligence as a technological tool at the service of human beings has led to an ethical debate about its future implication. The existing instruments to evaluate attitudes towards artificial intelligence have non-specific dimensions and are designed for populations different from the Spanish-speaking. In this sense, it is necessary to have valid, reliable, and contextualized tools to evaluate people's attitudes toward the use of artificial intelligence. Therefore, the present study aimed to develop an attitudinal rating scale for artificial intelligence. There were 604 volunteer participants between 18 and 55 years of age, 311 men and 293 women. Bartlett's test of sphericity showed a significant result (approximate chi-square = 1502. 7862387833S;p <.001), and the Kaiser-Meyer-Olkin test of sample adequacy showed an index of.825. With this, it was considered feasible to factorize the data matrix, and thanks to the factor analysis, three components explain 52.76% of the total rotated variance. In addition, a high internal consistency index was obtained for the 12 items of the inventory (0.768). These findings indicate that the EVAIA-I is a valid and reliable tool to evaluate the attitude towards artificial intelligence in Ecuador and other Latin American countries. © 2023 IEEE.
      79
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    Intervention against school bullying through emerging technologies: a literature review
    (2025)
    Acosta Pérez, Paul Bladimir  
    ;
    Espinosa Pinos, Carlos Alberto  
    ;
    Saa, Fernando  
    ;
    Francisco Sebastián Vaca-Pinto
    School bullying remains a persistent issue that negatively affects students' well-being and academic performance. Private educational institutions face unique challenges in addressing this problem due to limited resources and teacher training. This literature review explores the use of emerging technologies - such as virtual reality (VR), mobile applications, and artificial intelligence (AI) - as innovative tools to prevent and mitigate school bullying. Recent studies that implement these technologies in educational settings were analyzed to assess their effectiveness and applicability. The findings suggest that such tools can foster empathy, facilitate anonymous reporting, and enable early detection of incidents, contributing to the development of safer and more supportive school environments. © 2025 IEEE.
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