School Dropout Research Articles

Perceived stress and well-being in doctoral students: effects on program satisfaction and intention to quit

ABSTRACT Stress is a common negative emotion in students. Given the stress associated with doctoral studies, it is crucial to examine the influence of stress on well-being, program satisfaction, and retention in doctoral programs. This study examined stress-related issues and their relationships with intention to quit in a sample of 2,486 students enrolled in doctoral programs representing 38 disciplines. Participants completed a web-based questionnaire including sociodemographic and self-report measures assessing perceived stress, emotional, social, and psychological well-being, as well as program satisfaction and intention to quit. We tested three hypotheses based on Lazarus and Folkman’s transactional theory of stress and emotions and Núñez-Regueiro’s stress process model of school dropout. The results of Structural Equation Modeling (SEM) supported the hypotheses of the study and showed that perceived stress is negatively associated with emotional, social, and psychological well-being. The most significant finding from this study is that perceived stress, directly and indirectly contributes to lower program satisfaction in doctoral students and a stronger intention to quit. These study findings underscore the need for departments to actively support students in completing their dissertations by establishing explicit expectation norms.

Effect of the Social Safety Net on Child Labor and School Retention in Bangladesh: Empirical Evidence from Hies 2016

ABSTRACT: In Bangladesh Social Safety Net (SSN) interventions are intended to achieve specific goals, e.g., reduction in poverty, decrease in early school dropout, and nutrition supplementation. This study investigates the effectiveness of SSN participation on less explored goals of child labor reduction and school retention in Bangladesh. Empirical evidence is provided to evaluate the success of existing programs to combat child labor and early school dropout. This study utilizes the Household Income and Expenditure Survey (HIES), 2016 of Bangladesh. We employ the Propensity Score Matching (PSM) framework to show the causal relationship between SSN participation and its impact on the use of child labor and school retention. Given the nature and availability of data, the matching method provides us an estimate of the impact of SSN based on a quasi-experimental setting. We estimate counterfactuals based on observed characteristics of the household that affect both SSN participation and our outcome variables. Our results suggest that households that receive SSN tend to employ less child labor domestic or paid compared to their counterparts. Our Propensity Score Matching (PSM) results show that SSN participation reduces child labor prevalence in Bangladesh by 2.4% to 2.9%. This is an indication that families essentially substitute SSN income with child labor earnings. Thus, SSN programs in Bangladesh are effective in reducing child labor though the magnitude is not overwhelming. On the contrary, our results show that children from SSN-participating families have a higher incidence of early school dropout. This may be due to inefficiency or poorly designed programs that effectively keep the children in school. We estimate early school dropout is higher by 3.6% to 6.6% for households that receive SSN compared to the control group. Our findings are important for policymakers to redesign the programs that retain children in school. We suggest targeted interventions that will help to keep these children in school, which is conducive to human capital accrual and increasing lifetime earnings. Additionally, our insights will assist policymakers in rethinking SSN coverage, efficient selection of beneficiaries, and initiation of the correct intervention.

The Burden and Predictors of Early Sexual Initiation among School-Going Adolescents in Rural Settlements in Rivers State, Nigeria

Introduction. Early sexual initiation is the art of initiating sexual activity before age 15. This study aimed to identify the burden and predictors of early sexual initiation among school-­going adolescents in rural settlements in Rivers State, Nigeria. Materials and Methods. A cross-­sectional study was conducted among 420 school-­going senior secondary school adolescents of coeducational schools aged 15–19 from May 2023 to September 2023. A multi-­stage sampling procedure was used to select respondents from four senior secondary coeducational schools. Data were collected using a semi-structured interviewer-­assisted questionnaire. Frequency tables were generated and Logistic regression analysis was used to determine predictors of early sexual initiation at a 5% level of significance. Results. The mean age of respondents was 15.7 ± 0.8 years. The mean age at early sexual initiation was 12.2 ± 1.2 years. The burden of early sexual initiation and ever-had sex among the respondents was 46% and 54.8% respectively with poor academic performance, school dropout, STI infection, pregnancy, and HIV infection experienced as outcomes of first sexual initiation among the respondents. The statistically significant predictors of early sexual initiation were adolescents having worked for pay, currently working for pay, and adolescents’ age at first sexual partner (OR = 4.6; 95% CI = 1.6–12.7; P = 0.004, OR = 6.6; 95% CI = 1.9–23.7; P = 0.003 and OR = 3.1; 95% CI = 1.3–7.2; P = 0.009). Conclusion. Sexuality education and programmes aimed at encouraging school-­going adolescents to delay first-sex initiation should be encouraged.

Fighting Classroom Hunger : Analysis of Mid-day Meal Scheme of Odisha

India State Hunger Index (ISHI) reported that, “India is home to the world’s largest food insecure population, with more than 200 million people who are hungry.” Adding to this, the report urged that, the country’s poor performance is driven by its high levels of child under-nutrition and poor calorie count. Education plays a vital role in the development of human potential. State Governments are spending considerable portion of their resources to provide educational facilities all over the country. In spite of these efforts, the goal of cent percent universalization of elementary education appears to be far and elusive due to inherent socio-economic factors present in the society. Free and compulsory education up to the age of 14 years is the constitutional commitment and it is estimated that primary school children (6-14 years) form about 20% of the total population. Poor school enrolment and high school dropout rate are attributed to the poor nutritional status of the children compounded by poor socio-economic condition, child labour and lack of motivation. The researchers have used empirical research to find the real gap in the system.

Do Two Weeks in a Learning Camp after Ninth Grade Make a Difference? Experiences of Demotivated Boys with an Increased Risk of School Dropout.

School dropout may have important negative consequences for the individual as well as for society. Because school grades in lower secondary education are essential for the completion of upper secondary school, remotivating demotivated ninth graders with an increased risk of dropping out seems vital. This study focuses on the experiences of Norwegian ninth grade boys at a learning camp aimed at preventing school dropout through increasing school engagement, learning, and well-being before tenth grade. We interviewed 17 of the 29 participants in one particular camp to study their experiences and analyze how they were related to the theoretical underpinning of the camp. The participants described the learning camp as a motivation boost, focusing on experiences with academic progress and increased self-regulation, factors aligning with central theoretical underpinnings of the intervention. The participants placed "connecting with others", as in peers and teachers, among the top two factors that contributed to their re-motivation, well-being, and academic progress.

Advanced Deep Learning Model for Predicting the Academic Performances of Students in Educational Institutions

Educational institutions are increasingly focused on supporting students who may be facing academic challenges, aiming to enhance their educational outcomes through targeted interventions. Within this framework, leveraging advanced deep learning techniques to develop recommendation systems becomes essential. These systems are designed to identify students at risk of underperforming by analyzing patterns in their historical academic data, thereby facilitating personalized support strategies. This research introduces an innovative deep learning model tailored for pinpointing students in need of academic assistance. Utilizing a Gated Recurrent Neural Network (GRU) architecture, the model is rich with features such as a dense layer, max-pooling layer, and the ADAM optimization method used to optimize performance. The effectiveness of this model was tested using a comprehensive dataset containing 15,165 records of student assessments collected across several academic institutions. A comparative analysis with existing educational recommendation models, like Recurrent Neural Network (RNN), AdaBoost, and Artificial Immune Recognition System v2, highlights the superior accuracy of the proposed GRU model, which achieved an impressive overall accuracy of 99.70%. This breakthrough underscores the model’s potential in aiding educational institutions to proactively support students, thereby mitigating the risks of underachievement and dropout.

Analysis of push and pull factors influencing the migration of Ugandan domestic workers to Saudi Arabia

The study explored the push and pull factors driving Ugandan domestic workers to migrate to Saudi Arabia. The research paradigm employed was social constructivism, where individuals seek to understand their world and develop meanings based on their experiences. A qualitative approach using a phenomenological research design was utilised. Data was collected from a sample of eighteen (18) respondents through unstructured interviews to identify the factors contributing to the migration of Ugandan domestic workers to Saudi Arabia. Thematic analysis was conducted during data analysis. The migration factors were presented in concept maps created using Nvivo 10.0. The study uncovered that push factors varied from person to person, but major ones included poverty, unemployment, school dropout, family obligations, marital neglect, domestic violence, personal development goals, poor working conditions, work-related challenges, peer influence, and single parenting. Pull factors include the influence of Arabian family culture that promotes the demand for maids, bilateral labour agreements, adventure, attractive job prospects, free travel documents, cost-effective job processes, and an easy migration process. The study concluded that without effectively addressing push factors to provide long-term solutions, the migration of Ugandan domestic workers to Saudi Arabia will persist. It is recommended that the Government of Uganda take steps to create a conducive environment with satisfying employment opportunities for these young individuals to reduce the number of people seeking jobs outside Uganda. This involves generating employment opportunities to regulate internal domestic work and make it highly profitable, thereby encouraging young people to remain in Uganda.

Impact of Public Expenditure on Education in Chhattisgarh

This paper objective to investigate the correlation between public spending on education and the growth of the state of Chhattisgarh. Time-series data spanning from 2000 to 2021 was utilised. Public expenditure has several effects in economy. It can increase economic growth. It can increase social welfare. It is directly expected education is helps Positive Social change of citizen. The result shows that total public expenditure and Education expenditure is highly and statistically significant on economic growth indicator such as GER and DOR in primary level in Chhattisgarh.Public expenditure helps in achieving equitable distribution income and promote growth and welfare. The findings indicate that total public spending and education spending have a statistically significant and positive impact on economic growth indicators like the state's Gross Enrollment Ratio (GER) and the percentage of primary school dropout children (DOR) at the primary level. Education is directly expected to contribute to citizens' positive social transformation. The study's findings show that public spending on education and economic growth are correlated over the long term. Over time, there is a found unidirectional causal relationship between public education spending and Gross State Domestic Product (GSDP).

Application of the performance of machine learning techniques as support in the prediction of school dropout

This article presents a study, intending to design a model with 90% reliability, which helps in the prediction of school dropouts in higher and secondary education institutions, implementing machine learning techniques. The collection of information was carried out with open data from the 2015 Intercensal Survey and the 2010 and 2020 Population and Housing censuses carried out by the National Institute of Statistics and Geography, which contain information about the inhabitants and homes. in the 32 federal entities of Mexico. The data were homologated and twenty variables were selected, based on the correlation. After cleaning the data, there was a sample of 1,080,782 records in total. Supervised learning was used to create the model, automating data processing with training and testing, applying the following techniques, Artificial Neural Networks, Support Vector Machines, Linear Ridge and Lasso Regression, Bayesian Optimization, Random Forest, the first two with a reliability greater than 99% and the last with 91%.

Combating school dropout with Artificial Intelligence in brazilian higher education

This research explores the use of Artificial Intelligence (AI) as an innovative strategy to combat school dropout in Brazilian higher education. Faced with the increasing challenge of student retention in universities, the study focuses on evaluating the effectiveness of AI in this context, analyzing both its capabilities and limitations. The main objective is to understand how AI can be integrated into higher education, assessing its contributions to personalized learning and student engagement. The methodology consists of an extensive literature review, including the collection and detailed analysis of relevant studies on the use of AI in the educational field. The findings highlight that AI offers significant opportunities to tailor education to individual student needs, enhancing engagement and retention. Practical examples from the Brazilian context illustrate how AI implementation has contributed to reducing school dropout rates. However, the study also identifies key challenges, such as the need for adequate technological infrastructure and ongoing training for educators to effectively use AI tools. The conclusion is that AI holds substantial potential to mitigate dropout issues in higher education, but its successful implementation requires careful consideration. It is essential to take into account legal, ethical aspects, and institutional specifics to ensure effective integration of AI into the Brazilian educational system. This study provides valuable insights for strategic decision-making and the development of more efficient and contemporary educational policies.

Youth-led social accountability among service providers optimizing sexual and reproductive health rights outcomes in Kilifi County, Kenya


 Background: The demand side of the health system is gaining traction to improve health outcomes. Among adolescents and youths, this is needed, particularly in low- and middle-income countries (LMICs) where they account for the majority and demographic dividends require that they be healthy and productive to participate in national development. Unfortunately, at this transition age from childhood into adulthood, they experience many challenges such as malnutrition, poverty, school dropout rates, gender inequality, drug and substance abuse, mental ill-health, and menstrual hygiene and health challenges. Risky behaviors related to SRHR include unplanned pregnancies, gender and sexual orientation issues, gender-based violence, sexually transmitted infections, harmful cultural practices, and reproductive cancers.
 Methods: VSO PITCH Data for the youth accountability project addressed social accountability by service providers for youth-friendly information and services. The data tool used was the intersectional community scorecard collected through focused group discussion entries made at county health facilities by youth, service providers, and interface synthesis of satisfaction scores. These were uploaded onto a digital platform showing the number of FGDs, core indicators, satisfaction scores, reasons, recommendations, and action plans. This project was conducted in Kilifi County and two other counties. 
 Results: FGDs comprised 50% youth, 25% adults, 25% of mixed age range, and two persons with disability. All core indicators were unsatisfactory, <50%, and did not meet the global standard for quality healthcare services. The satisfaction score for the number of staff providers was grossly underserved at 10%, with the youth demanding that they serve their own. A satisfaction score of 30% was reported due to a lack of disability services, privacy, youth space, inadequate quality of care including test kits for HIV, and discriminated and stigmatized LGBTQ+ with back-biting after delivery of services. 
 Conclusion: Youth-led social accountability ensures service providers are responsive to the needs of adolescents and youth. The propulsion is by youth for youth who should be health literate on social accountability. More attention among service providers includes the provision of adequate competent staff, VCAT, compassionate and respectful care, and good interpersonal communication, meaningful engagement and reverse mentorship with adolescents and youth, and a focus on rights-based and intersectionality for better SRHR outcomes and youth development.

School-Based Intervention for Adolescents With ADHD: Predictors of Effects on Academic, Behavioral, and Social Functioning

Adolescents with attention-deficit/hyperactivity disorder (ADHD) experience significant academic, behavioral, and social skill difficulties including underachievement, risk for school dropout, poor peer relations, and emotion dysregulation. Although stimulant medication reduces ADHD symptoms, psychosocial and educational interventions are necessary to address functional impairments. We examined the nature and predictors of academic, behavioral, and social skills trajectories in response to multicomponent organizational and interpersonal skills training in 92 high school students with ADHD. Latent trajectory class analyses revealed positive treatment response ranging from 61.5% (report card grades) to 100% (inattention symptoms, organizational skills, social skills). Organizational skill and academic grade treatment response trajectories were predicted by assigned sex, pretreatment anxiety, and treatment dosage, while improvement in behavioral and social functioning was associated with better emotion regulation and family relations prior to treatment along with stronger working alliance with treatment coach at midtreatment. Multicomponent organizational and interpersonal skills training appears effective for most high school students with ADHD and the degree treatment-induced change is associated with multiple malleable factors can be leveraged to enhance intervention response.

The National Student Assistance Plan (PNAES) in the context of a university campus in the Amazon Region

The study carried out sought to analyze whether a campus of a federal public university in the Amazon Region, through its Student Assistance Program, has managed to combat dropout rates from its courses, as stated in one of the main objectives of the National Student Assistance Program – PNAES, set out in Decree n º 7.234 of July 19, 2010. Microsoft Office Excel software was used to carry out the study, in order to identify the profile of the beneficiary students and their course completion rates, based on two documents: The Report of students benefiting from student assistance, between the years 2016 to 2020 and the Report of dropout students who entered between the years 2012 to 2018. Furthermore, a Multiple Correspondence Analysis was carried out using the R software. study results indicate that the Student Assistance Program contributes to the reduction of school dropouts in courses on the studied campus, mainly in afternoon courses. It was found that improvements are possible with the adoption of measures aimed at encouraging students to complete the course, especially those in situations of socioeconomic vulnerability, such as expanding and increasing the value of student aid.

Poorer self-reported mental health and general health among first year upper secondary school students do not predict school dropout: a five-year prospective study.

Education is important for socioeconomic, work and health status; thus, dropping out of secondary school is of major concern. In Norway, 1 out of 5 is dropping out from upper secondary education. Academic performance is a known predictor for dropout, but the role of mental and general health status is studied less. By use of student data collected during the first school year we examined the accumulated risk of school dropout over 5 years. Students entering upper secondary school in a North-Norwegian region (Troms County) completed a comprehensive questionnaire during August 2010 (N = 1,676, 69% response rate). The contribution of mental and general health problems in predicting five-year dropout was of primary interest, adjusted for demographics and academic performance. One-third of the students had dropped out after 5 years. A logistic regression analysis showed no significant effect of mental and general health problems on dropout. Among the covariates, higher grades from lower secondary education reduced the chance of dropping out (OR = 0.31; p < 0.001). Subgroup analyses showed that students in the vocational track reported poorer mental and general health, compared to students in the general track, but this difference was not related to dropout. General track students were also less likely to drop out than vocational track students (OR for dropout 0.66; p < 0.05). In conclusion, lower grades from lower secondary education represented a warning flag for school dropout during upper secondary education whereas mental health issues were not.

Quality of Life of Children From Families Affected by Migration: The Role of Educational Policies

The problems of children from Romanian transnational families represent a current issue and one of great interest in the field of public policies that need to be developed in Romania in order to offer solutions that will lead to an increase in the quality of life within these families. This article reflects, based on the results of a survey among parents/grandparents who care for children from transnational families and two focus groups with authorities/organizations with a role in managing the problems of transnational families, the main issues faced by children from these families within education. The results obtained indicate an increased need for intervention in the following areas: support to avoid school dropout; education regarding the negative effects of drug, alcohol and other toxic substance consumption; and supervision in the completion of school assignments. All these problems influence the educational course of children and consequently the quality of life of all family members. This article offers support to decision makers in the field of educational policies to effectively manage the real problems of these families, highlighting the vital role of substantiating public policies based on scientific studies.

Student Engagement—Pre and Post Covid-19 Pandemic

This study contributes to applied and theoretical research for schools and districts by exploring data-based evidence of the relationships between the Covid-19 pandemic and student engagement with school. The paper features trend data on student orientation to school assessed via the multi-dimensional Student Orientation to School Questionnaire (SOS-Q). The SOS-Q was initially developed to better understand the reasons for school dropout and has expanded to explicate a wider range of student-school engagement dynamics. This study demonstrates how student orientation to school may be effected by major extraneous factors and demonstrates the value of integrating valuable non-cognitive or affective measures within comprehensive student information and assessment systems augmenting both individual and cohort psychological supports.

Artificial Intelligence Bringing Improvements to Adaptive Learning in Education: A Case Study

Despite promising outcomes in higher education, the widespread adoption of learning analytics remains elusive in various educational settings, with primary and secondary schools displaying considerable reluctance to embrace these tools. This hesitancy poses a significant obstacle, particularly given the prevalence of educational technology and the abundance of data generated in these environments. In contrast to higher education institutions that readily integrate learning analytics tools into their educational governance, high schools often harbor skepticism regarding the tools’ impact and returns. To overcome these challenges, this work aims to harness learning analytics to address critical areas, such as school dropout rates, the need to foster student collaboration, improving argumentation and writing skills, and the need to enhance computational thinking across all age groups. The goal is to empower teachers and decision makers with learning analytics tools that will equip them to identify learners in vulnerable or exceptional situations, enabling educational authorities to take suitable actions that are aligned with students’ needs; this could potentially involve adapting learning processes and organizational structures to meet the needs of students. This work also seeks to evaluate the impact of such analytics tools on education within a multi-dimensional and scalable domain, ranging from individual learners to teachers and principals, and extending to broader governing bodies. The primary objective is articulated through the development of a user-friendly AI-based dashboard for learning. This prototype aims to provide robust support for teachers and principals who are dedicated to enhancing the education they provide within the intricate and multifaceted social domain of the school.

A Study on Girl Dropout in Community College of Kirtipur Municipality

College dropout is one of the big problems in community college of Kirtipur. So, in this study, the researcher explores the social, financial and academic reasons of girls who quit their study at the college level. As education plays a vital role in holistic development of individual and nation, the issues of droping out of students from educational program are cricual area of research. While social, economic and academic factors may affect the students’ survival in the school, this study explores the particular reasons that cause girls college dropout at the undergraduate level. The research is based on constructive, interpretative qualitative ideas of mobile interview with open-ended questionnaires using purposive sampling methods with in-depth interviews using as tools to take the data. The findings of this study show that, social, economic and academic reasons influence the participants’ college dropout in under graduate level.

Psychosocial factors as risk of dropout in university students of the Early Care and Early Childhood Education Program

The present study analyzed psychosocial risk factors for dropout in students of the Early Care and Early Childhood Education Program. A non-experimental, transversal and descriptive design was carried out. The sample was made up of 102 students, to whom sociodemographic and modified dropout questionnaires were applied. The results showed that the average academic performance in three semesters (57.8%, 56%, 49%); 87.3% of students work, 52.9% full time, affecting their performance; 41.2% understand the contents only sometimes; the family conceives the student poorly (3.9%), very high family expectations (13.7%), they feel valued as bad students (5.9%), affecting their motivation; 70% entered on the advice of others; 5.9% have worse performance than their peers, related to repetition and indirectly dropping out, and more than 78% report deficiencies in previous courses. The students identified the main risk factors for dropping out: economic difficulties (26.5%), family problems (13.7%), possibility of missing the year (11.8%) and job placement (10.8%).

Who is at risk for dropout from a virtual-agent based digital therapy for insomnia?

Who is at risk for dropout from a virtual-agent based digital therapy for insomnia?