Search Results (148)

This study evaluates the effect of simple data-level balancing techniques on predicting school dropout across all state public high schools in Espírito Santo, Brazil. We trained Logistic Regression with LASSO (LR), Random Forest (RF), and Naive Bayes (NB) models on first-quarter data from 2018–2019 and forecasted dropouts for 2020, with additional validation in 2022. Facing strong class imbalance, we compared three balancing methods—RUS, SMOTE, and ROSE—against models trained on the original data. Performance was assessed using accuracy, sensitivity, specificity, precision, F1, AUC, and G-mean. Results show that the imbalance severely harmed RF and NB trained without balancing, while Logistic Regression remained more stable. Overall, balancing techniques improved most metrics: RUS and ROSE were often superior, while SMOTE produced mixed results. Optimal configurations varied by year and metric, and RUS and ROSE made up most of the best combinations. Although most configurations benefited from balancing, some decreased performance; therefore, we recommend systematic testing of multiple balancing strategies and further research into SMOTE variants and algorithm-level approaches. Full article

School dropout and the recruitment of minors by criminal organizations have become deeply intertwined phenomena in Ecuador, particularly in territories marked by extreme violence and institutional fragility. This study investigates how Ecuadorian national media construct and frame these issues in 2025, using a qualitative content analysis of 85 opinion columns, editorials and analytical pieces published in leading outlets including El Comercio, El Universo, La Hora, Primicias, GK, Vistazo and Mercurio. Through a critical analysis of discursive patterns, the study identifies dominant narratives that reflect the normalization of violence, the erosion of schools as protective spaces, polarized portrayals of youth as victims or delinquents and a general critique of state inaction. Media narratives were found to vary ideologically, with some reinforcing stigma while others advocated for structural reform and rights-based approaches. The results highlight the role of media in shaping public understanding of educational exclusion and juvenile vulnerability in contexts of conflict. This research concludes that while Ecuadorian media serve as both mirrors and mediators of social crisis, their potential to influence educational policy and child protection efforts remains uneven. A more inclusive, critical and community-oriented media discourse is needed to confront the challenges of educational abandonment and youth recruitment. Full article

Education about epilepsy plays a vital role in reducing stigma, improving seizure response, and preventing school dropout among affected learners. Despite this importance, there is a lack of a structured conceptual framework guiding epilepsy education in primary schools, where children’s foundational learning and social development take place. This study aims to develop a conceptual framework that integrates epilepsy education into the life skills curriculum to reduce epilepsy-related stigma from an early age. A qualitative multi-methods approach was employed during the empirical phase, which was conducted in two stages using an exploratory–descriptive design. Data were collected from teachers, life skills education advisors (LEAs), and learners to explore their views on incorporating epilepsy education into the life skills curriculum of primary schools. The findings informed the development of a conceptual framework guided by the Three-Legged Stool Model and Dickoff’s Practice-Oriented Theory. This educational framework is tailored for primary school settings and highlights the roles of learners and teachers in promoting self-esteem through knowledge acquisition, value formation, and skill development, all underpinned by the Ubuntu philosophy. Full article

Student dropout remains a critical challenge in higher education, especially within public universities that serve diverse and vulnerable populations. This research presents the design and evaluation of an early warning system based on an XGBoost classifier, trained exclusively on data collected at the time of student enrollment. Using a retrospective dataset of nearly 40,000 first-year students (2014–2024) from a Mexican public university, the model incorporated academic, socioeconomic, demographic, and perceptual variables. The final XGBoost model achieved an AUC-ROC of 0.6902 and an F1-score of 0.6946 for the dropout class, with a sensitivity of 88%. XGBoost was chosen over Random Forest due to its superior ability to detect students at risk, a critical requirement for early intervention. The model flagged 59% of incoming students as high-risk, with considerable variability across academic programs. The most influential predictors included age, high school GPA, conditioned admission, and other family responsibilities and economic constraints. This research demonstrates that early warning systems can transform enrollment data into timely and actionable insights, enabling universities to identify vulnerable students earlier and respond more effectively, allocate support more efficiently, and enhance their efforts to reduce dropout rates and improve student retention. Full article

Climate change is a global crisis that disproportionately affects vulnerable agrarian communities, exacerbating food insecurity and health risks. This qualitative study explored the relationship between climate change and health in the following two rural sub-counties of Kilifi County, Kenya: Ganze and Magarini. In fall 2023, we conducted 16 focus group discussions with adolescent girls (14–17), young adults (18–30), and older adults (31+). Thematic analysis revealed that climate change adversely affects health through key social determinants, including economic instability, environmental degradation, limited healthcare access, food insecurity, and disrupted education. Participants reported increased food scarcity, disease outbreaks, and reduced access to medical care due to droughts and floods. Economic hardship contributed to harmful survival strategies, including transactional sex and school dropout among adolescent girls. Mental health concerns, such as stress, substance use, and suicidal ideation, were prevalent. These findings highlight the wide-ranging health impacts of climate change in agrarian settings and the urgent need for comprehensive, community-informed interventions. Priorities should include improving nutrition, reproductive and mental health services, infectious disease prevention, and healthcare access. Full article

Background: This study examined treatment outcomes for cannabis use disorder (CUD) among adolescents (12–17 years old) in the United States. Methods: Data from the 2018–2021 Treatment Episode Data Set-Discharges (TEDS-D) included 40,054 adolescents diagnosed with CUD. Descriptive statistics, Chi-square tests, and multivariable logistic regression assessed treatment outcomes and factors associated with treatment completion. Results: Only 36.8% of adolescents completed treatment. The most common reasons for not completing treatment were dropping out (28.4%) and transferring to another facility/program (17.0%). Males and Black non-Hispanic adolescents had lower odds of completing treatment (OR = 0.79, 95%CI: 0.75–0.84), while Hispanic (OR = 1.13, 95%CI: 1.08–1.18), Asian (OR = 1.56, 95%CI: 1.3–1.86) and Native Hawaiian/Pacific Islander adolescents (OR = 2.31, 95%CI: 2.04–2.61) had higher odds of completion compared to their White counterparts. Independent living arrangements, homelessness, arrests in the past 30 days and younger age (<15 years old) decreased the likelihood of treatment completion. Adolescents with co-occurring mental health and substance use disorders also had lower completion rates (OR = 0.79, 95%CI: 0.77–0.86). Referral from schools/employers and treatment settings were associated with a higher success, particularly with stays of 4–6 months and 7–12 months. Conclusion: This study highlights the need for targeted CUD treatment programs that support at-risk adolescents, especially those experiencing homelessness or facing legal issues. High dropout and transition rates suggest a need for continuity of care and program integration between facilities. Strengthening coordination among public health officials, community organizations, and stakeholders is essential to developing culturally responsive treatment interventions that address social determinants of health, substance use, and mental health in this vulnerable population. Full article

The aim of this study is to identify the key factors contributing to student dropout and to develop a predictive model that estimates the dropout risk of students based on their entry characteristics and enrolment registration data. Our analysis is based on the registration and academic data of 971 full-time and part-time bachelor’s students in five faculties, who were enrolled in the academic year 2021–2022 at the Latvia University of Life Sciences and Technologies (LBTU). The dropout analysis was done during the 3.5 years of study, when the students started their last semester in engineering and information technology, agriculture and food technology, economics and social sciences, and forest and environmental studies and when veterinary medicine students had completed more than half of their program of study. Survival analysis methods were used during the study. Students’ dropout risk in relation to gender, faculty, priority to study in the program, and secondary school performance (SM) was estimated using the Proportional hazard model (Cox model). The highest student dropout was observed during the first year of study. Secondary school performance was a significant predictor of students’ dropout risk; students with higher SM had a lower dropout risk (HR = 0.66, p < 0.05). As well, student dropout can be explained by faculty or study programme. Students in economics and social sciences were at lower dropout risk than the students from the other faculties. Results show the model’s concordance index was 0.59, and this indicates that additional or stronger predictors may be needed to improve model performance. Full article

Many vocational education and training (VET) students in the Netherlands struggle with the transition from education to the labour market, resulting in high dropout rates. VET institutions are actively seeking effective mechanisms to support their students during this transition. This research explored valuable strategies identified by education professionals to facilitate a sustainable transition from education to the labour market. This study employed a realistic evaluation framework using CIMO-logic (which focuses on the Context, Intervention, Mechanism, Outcome) for analysis in order to gain insight into the processes of change. In total, four cases were studied at two Dutch educational institutions. The research followed an inductive approach using within-case and cross-case analyses. Five key elements were identified: skills and competencies, Self-insight, Self-efficacy, Building a professional network, and bridging education and practice. In school-to-work guidance for VET students, these elements are relevant to consider in guidance programs. Full article

This study aims to predict and discover important factors for the learning performance of students belonging to two ethnic groups—Khmer and Chinese (Hoa) students—in Soc Trang with the use of random forest (RF) and Gaussian Naïve Bayes (GNB) classifiers based on students’ demographics and grade point average (GPA) scores. The study involved 174 Khmer and Chinese (Hoa) students in Grade 10 in a high school in Soc Trang Province, Vietnam. The results showed that, for Khmer students, GNB was better than RF, with an F1 score of 100%. Mathematics was the most important subject leading Khmer students to very good or poor performance. For Chinese (Hoa) students, both classifiers showed the same accuracy performance. Scores in Literature and English in Semester 1 impacted Chinese (Hoa) students’ performance. The results of this study provide a reference for formulating a policy to improve the learning performance of minority students to prevent dropouts. Full article

This study aims to explore the experiences and perceptions of service providers working in direct contact with out-of-school youth to identify ways to build a more sustainable and responsive support system within the community. Individual and group interviews were conducted with eight service providers, including a team leader and five directors from public out-of-school support institutions, as well as two schoolteachers from the Board of Education, who were experienced in assisting dropout students. Reflexive thematic analysis of the interview data revealed four key themes: connecting youth to the community system, diversifying programs, minimizing disparities, and increasing societal awareness of out-of-school youth. These findings highlight how various needs and access to opportunities can be provided to all youths, regardless of their school enrollment. The study underscores the importance of shared responsibility in building an inclusive, community-based approach. It also emphasizes the necessity of cross-sector and inter-ministerial collaboration to reduce structural barriers and promote equitable learning opportunities. By centering the voices of practitioners, this study contributes to the broader discourse on building a sustainable community in which out-of-school youth can receive opportunities and resources to thrive as healthy contributing members of the community. Full article

This study investigates the dropout risk among first- and second-year high school students in the peripheral areas of Southern Italy, where the dropout rates are extremely high. It focuses on individual and relational factors associated with dropout, analyzing data from 645 students (M_age = 14.64) who completed a self-report questionnaire. The examined variables include self-efficacy, amotivation, future orientation, peer relationships, and students’ trust in teachers. Hierarchical regressions assessed the influence of grade levels on these dimensions. Our findings show a positive developmental trend in second-year students, including higher self-efficacy, better peer relationships, and reduced intentions to drop out. However, trust in teachers declines during this transition. Moreover, relationships with teachers show no significant improvement across grades. Therefore, this study underscores the importance of fostering trust between students and teachers as a protective factor against dropout. It also reveals the need for interventions targeting both students and the educational environment to improve teacher–student relationships and support students’ educational aspirations. By addressing these relational aspects, stakeholders can better mitigate dropout risks and promote school engagement during critical transitions in adolescence. Full article

Background: Adolescents’ use of step tracker mobile applications (apps) could be influenced by their assessment of the mobile app used. Objectives: To analyze differences in the dropout rate, app assessment, and problematic mobile phone use based on prior physical activity levels and the app used. Methods: A study with a quasi-experimental design was carried out with the participation of 240 adolescents, who were further categorized as either active or inactive. The adolescents carried out a 10-week intervention promoted as a part of the physical education curriculum, three days a week, in which they randomly used the Pokémon Go, MapMyWalk, Pacer, or Strava mobile apps after school for cardiorespiratory training. Results: The results showed a higher dropout rate from Pokémon Go in the group of inactive adolescents (p = 0.012). No differences were found in the assessment of apps based on the level of activity of the adolescents, neither overall nor when analyzing this question based on the app used (p > 0.05). As for problematic mobile phone use, only previously inactive adolescents assigned to the Pacer group significantly increased their final score after the intervention (p = 0.044), with no changes being identified in the other groups or apps (p > 0.05). Furthermore, the active adolescents showed a positive relationship between the volume of training and problematic mobile phone use (p = 0.023), specifically with the conflicting use of this device (p = 0.017). Conclusions: The inactive adolescents had a higher dropout rate when using Pokémon Go. There were no differences in app assessment between the active and the inactive participants. However, the active adolescents showed a link between their training volume and problematic mobile phone use. Full article

Competency-Based Education (CBE) has been widely studied since the 1970s, yet it remains innovative due to its challenges across disciplines and cultures. Tecnológico de Monterrey, a Mexican private institution, implements CBE through its Tec21 model, which emphasizes challenge-based learning to develop disciplinary and transversal skills. Since its launch in 2019, Tec21 has generated extensive data, offering an opportunity to assess its performance and ensure quality. This study analyzes data from six academic semesters in the School of Engineering and Sciences to address key quality assurance questions. First, we evaluate whether initially enrolling in a generic area before selecting a specific program improves long-term student outcomes. Second, we examine competency development, identifying challenges in achieving certain skills and their links to dropout rates and module difficulty. Third, we explore the relationship between final grades, module credit allocation, and Tec weeks to assess curriculum alignment with academic performance. Using data from over 550,000 evaluations of 4500+ students, our analysis provides robust quality metrics. Findings suggest that students who start in generic areas perform better long term and highlight the complex interplay between competencies, module characteristics, and academic success. These insights deepen the understanding of CBE implementation and offer recommendations to improve educational strategies and quality assurance within competency-based frameworks. Full article

School dropout in higher education remains a significant global challenge with profound socioeconomic consequences. To address this complex issue, educational institutions increasingly rely on business intelligence (BI) and related predictive analytics, such as machine learning and data mining techniques. This systematic review critically examines the application of BI and predictive analytics for analyzing and preventing student dropout, synthesizing evidence from 230 studies published globally between 1996 and 2025. We collected literature from the Google Scholar and Scopus databases using a comprehensive search strategy, incorporating keywords such as “business intelligence”, “machine learning”, and “big data”. The results highlight a wide range of predictive tools and methodologies, notably data visualization platforms (e.g., Power BI) and algorithms like decision trees, Random Forest, and logistic regression, demonstrating effectiveness in identifying dropout patterns and at-risk students. Common predictive variables included personal, socioeconomic, academic, institutional, and engagement-related factors, reflecting dropout’s multifaceted nature. Critical challenges identified include data privacy regulations (e.g., GDPR and FERPA), limited data integration capabilities, interpretability of advanced models, ethical considerations, and educators’ capacity to leverage BI effectively. Despite these challenges, BI applications significantly enhance institutions’ ability to predict dropout accurately and implement timely, targeted interventions. This review emphasizes the need for ongoing research on integrating ethical AI-driven analytics and scaling BI solutions across diverse educational contexts to reduce dropout rates effectively and sustainably. Full article

This article examines the audiovisual representation of violence during the armed takeover of the Ecuadorian television channel TC Television on 9 January 2024, an unprecedented event in the country’s recent media history. Employing a film analysis methodology, the study deconstructs the live broadcast by segmenting it into visual sequences and analyzing elements such as narrative content, shot composition, camera movement, sound design, and editing techniques. The interpretive phase includes narratological, iconic, and psychoanalytic readings. From a psychoanalytic perspective, the study explores the emotional impact of the broadcast on viewers, focusing on responses such as fear, anxiety, identification, projection, and the activation of psychological defense mechanisms. It also reflects on the broader sociocultural consequences of such representations of violence in public media. The article concludes by emphasizing the need for public investment in inclusive and high-quality education as a structural response to youth vulnerability, school dropout, and the risk of recruitment by organized criminal groups in Ecuador. Full article