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This work examines the returns to education for workers who pursue additional education after time out of the labor force. It compares those who remain in the labor force during additional education with those who drop out of the labor force during additional education. It compares two cohorts of the National Longitudinal Survey of Youth (NLSY).

This work utilizes a difference equation to estimate the returns to education for workers who pursue additional education after time spent out of school and in the labor force.

The results indicate a sheepskin return of approximately 14% for those who remain in the labor force and a return of approximately 9% to years of additional education for those who drop out of the labor force. This contrasting pattern of returns is robust to sample selection correction and a variety of checks.

This work does not fully account for all threats to causation. Further research could pursue these and make use of data from more clearly defined periods of education.

This work finds key differences between the internal labor market faced by those remaining in the labor force and the external labor market faced by those dropping out of the labor force. A policy focused on re-training workers should account for these differences.

This is the first work to compare workers who pursue additional education while remaining in the labor force to workers who pursue additional education and drop out of the labor force.

Using longitudinal data of children in Nepal, this study examines the relationships between dropouts, grade repetition and the causes of dropout, such as entrance age, to derive concrete recommendations to improve the basic education completion rates in Nepal, one of the targets of Sustainable Development Goal 4 (SDG4).

The data for this study were drawn from school records kept in the target schools, home visit surveys and interviews with principals and teachers. After comparing the repetition experience and the frequency of repetitions between graduates and dropouts, the study analysed the dropout patterns of individual children. The study then examined the effects of repetition and entrance age on children’s schooling.

The results identified a large group of children who dropped out of school without any repetition, with only 15.9% of the children repeating a grade immediately before dropping out. The findings indicated that harsh family environments, being overage and low educational expectations were factors in sudden dropout.

Collecting longitudinal data is difficult in developing countries, and few studies use such data. The question of access to education has been re-ignited by the COVID-19 pandemic; this study used longitudinal data to thoroughly analyse children’s dropout patterns and provide specific recommendations that will contribute to the achievement of SDG4.

Adolescents with harmful sexual behaviors (AHSB) who drop out of treatment are more likely to continue offending than are those who complete treatment; therefore, it is important to identify factors that heighten the risk of dropout, so they can be detected early. The purpose of this paper is to present the predictors of treatment dropout derived from a community sample of AHSB in New Zealand.

Pretreatment data on 100 males (aged 12–16) in community-based treatment for harmful sexual behavior were analyzed. Data on 50 adolescents who dropped out were matched by age and ethnicity to 50 adolescents who completed treatment. Pretreatment variables were identified using the Estimate of Risk of Adolescent Sexual Offence Recidivism. The degree to which these variables influenced treatment dropout was tested using logistic regression.

Compared to those who completed treatment, adolescents who dropped out were more likely to have a prior history of personal victimization, to deny or minimize their behavior, to have been mandated to attend treatment and to have engaged in noncontact offences.

Screening for a prior history of personal victimization, denial or minimization, mandated treatment and noncontact offences may facilitate the prediction of dropout risk more confidently. Addressing these pretreatment risk variables has the potential to improve treatment completion rates.

To the best of the authors’ knowledge, this paper is the first to highlight treatment dropout predictors in a New Zealand community sample.

This paper aims to measure the prevalence of deviant behaviour among children who have dropped out of school and their subsequent arrests by the criminal justice system. The paper further analyses the relationship between the factors attributed to deviant behaviour and the subsequent arrests by the criminal justice system.

Using a semi-structured interview schedule, data was collected from 330 children who had already dropped out of school, remained on the streets or worked. The interviews took place in the presence of either of the children’s parents, with their consent.

The research identified 12 significant factors contributing to children dropping out of school. It also found six factors responsible for deviant behaviour. Furthermore, the study revealed that about 70% of the respondents were involved in one or more deviant behaviours. Among them, 51% had been detained by the Police in the past two years. Additionally, the linear regression model results positively predict the nexus among the six factors responsible for deviant behaviour.

The study is limited to male children who had dropped out of school, as female children were excluded. In connection with measuring deviant behaviour, it was challenging to discern whether it occurred before students left school, after or both.

The study suggests several measures, including policies such as early intervention programmes, providing quality education, mentoring and counselling for students and parents, vocational education opportunities, creating drug-free environments, career guidance, peer mentoring, community engagement, substance abuse prevention and rehabilitation programmes, to prevent school dropout and subsequent deviant behaviour.

To the best of the authors’ knowledge, this study is unique to India. The moderation regression model represents an exceptional finding. This study constitutes another addition to the field of child welfare while also indicating scope for future research.

This study examined the psychometric properties of intention to drop out and study satisfaction measures for first-year South African students. The factorial validity, item bias, measurement invariance and reliability were tested.

A cross-sectional design was used. For the study on intention to drop out, 1,820 first-year students participated, whilst 780 first-year students participated in the study on satisfaction with studies. Confirmatory factor analysis (CFA), differential item functioning (DIF), measurement invariance and internal consistency were used to test the scales.

A one-factor structure was confirmed for both scales. For the intention to drop out scale, Items 3 and 4 were identified with statistically significant item bias; however, these differences had no practical impact. Except for scalar invariance for language, sufficient measurement invariance was established. No problematic items were identified for the study satisfaction scale.

In essence, this study provides evidence of two short measures that are culturally sensitive that could be used as short and valid measures across contextual boundaries as practically valuable tools to measure intention to drop out and study satisfaction in diverse and multicultural contexts.

This study contributes to limited research on bias and invariance analyses for scales that can be used in interventions to identify students at risk of leaving the university and utilising psychometric analyses to ensure the applicability of these two scales in diverse and multicultural settings.

This study analyzed the impact on the persistence of Chilean university students who had received a government-guaranteed loan (CAE).

Using academic and administrative data from 2016 to 2019, provided by 11 Chilean universities, a discrete-time survival model was constructed. The model was based on data of 5,276 students in the 2016 cohort and included sociodemographic variables, academic background prior to entering university and academic performance once in university. As a robustness check of our results to observable confounding, the analysis was repeated using a control group constructed using propensity score matching (PSM).

The results reveal that students who receive a bank loan (CAE) were more likely to remain in undergraduate studies for at least the first two years of university, as opposed to their peers who did not receive financial aid. In addition, they show the importance of academic performance in retention.

The article advances in the identification of the impact of bank loans on permanence. Although previous research has evaluated the impact of the CAE, it has been conducted on small samples of students. These studies also lacked student records associated with their academic performance at the university. The present research overcomes both weaknesses, allowing us to estimate the impact of the CAE on a larger population of students that is representative of the system.

The purpose of this paper is to consider one test of a well-functioning housing system – its impact on wellbeing. Exploring one indicator of this, this study aims to track changes in mental and general health across a mix of tenure transitions and financial transactions in three jurisdictions: Australia, the UK and the USA.

Using matched variables from three national panel surveys (Household, Income and Labour Dynamics in Australia, British Household Panel Survey/Understanding Society and Panel Study of Income Dynamics) over 17 years (2000–2017) to capture the sweep of the most recent housing cycle, this study adopts a difference-in-difference random-effects model specification to estimate the mental and general health effects of tenure change and borrowing behaviours.

There is an enduring health premium associated with unmortgaged owner-occupation. Mortgage debt detracts from this, as does the prospect of dropping out of ownership and into renting. A previously observed post-exit recovery in mental health – a debt-relief effect – is not present in the longer run. In fact, in some circumstances, both mental and general health deficits are amplified, even among those who eventually regain homeownership. Though there are cross-country differences, the similarities across these financialised housing systems are more striking.

The well-being premium traditionally associated with owner occupation is under threat at the edges of the sector in all three jurisdictions. In this, there is cross-national convergence. There may therefore be scope to introduce policies to better support households at the edges of ownership that work across the board for debt-funded ownership-centred housing systems.

This paper extends the duration of a previous analysis of the impact of tenure transitions and financial transactions on well-being at the edges of ownership in the UK and Australia. The authors now track households over nearly two decades from the start of the millennium into a lengthy (post-global financial crisis) era of declining housing affordability. This study adds to the reach of the earlier study by adding a general health variable and a third jurisdiction, the USA.

The main purpose of this study is to evaluate the extent of dropout students and identify the relationship between risk factors of dropout and the survival time of students.

The Kaplan–Meier estimator (KM), also known as the product-limit technique, is a nonparametric model function that is commonly used in estimating survival function events (Kaplan and Meier, 1958). The survival function's Kaplan–Meier estimators are used to estimate and graph survival probabilities as a function of time, as well as explanatory data analysis (EDA) for the survival data, including the median survival time, and compare for two or more of the survival events. In addition, Cox proportional hazards model is employed for modelling purpose.

Results of the Kaplan–Meier curves show that male students have lower survival rates than female, researchers have found that there is a difference between the survival times of the student's school types, results show students from English-based schools are higher than Arabic-based schools as suggested by the survival curve. Similarly, there is a difference between the survival times of students aging equal or greater than 25 and students aging less than 25 and survival function estimates of dropout according to high school grade marks has huge difference. These results were confirmed using log rank test as age, school type and marks were statistically significantly different while gender is not statistically significant.

There is no study of this kind from the Somalia context about the student's dropout. Subsequent to the outbreak of civil war in 1988 and the collapse of the central government in 1991, all public social services in Somalia including education centers were severely disrupted.

The statistical methods discussed in the previous section will be applied on a real dataset obtained from different offices of the university; most of the data were extracted from faculty of economics office and admission and record office. The data set comprised of 70 students from SIMAD university, consists of full-time faculty of economics students who enrolled at the university in the academic year of 2017–2018 until two years of diploma, students either complete 24 months of diploma or leave the university and that is the event of interest.

This paper provides novel evidence on the role of gender in the performance of university students, which is particularly relevant to the debate on the performance of female students in science, technology, engineering and mathematics (STEM) subjects.

Our approach relies on the metafrontier approach proposed by Huang et al. (2014), which measures students' efficiency within a given faculty and the impact of the faculty’s technology on students’ efficiency. We use a sample of 53,159 first-year students in 8 faculties from a large university in southern Italy from 2002–2003 to 2010–2011.

Students’ efficiency is relatively low, reflecting an essential role of unobserved heterogeneity. The different technologies of somewhat similar faculties have minimal impact on efficiency. There is a performance gap against women in five faculties, which on average is strongest for the faculties in the pure and applied science area. This gap increases with the proportion of female students and decreases with female lecturers.

The metafrontier has the benefit of providing relevant policy information on the drivers of student success by relying on data that universities routinely generate and preserve.

The stochastic metafrontier approach allows us to separate the group-specific frontiers from the metafrontier, yielding a decomposition of the efficiency scores of various faculties into technical efficiency scores and technological gaps.

First-generation students (FGS) experience numerous challenges during their studies because of their background attributes and lack of social capital required to navigate institutions of higher learning. The purpose of this study was to investigate the influence of perceived social support and a sense of belonging on academic persistence among FGS at a distance e-learning institution in South Africa.

A cross-sectional quantitative research approach was employed. The sample comprised 240 undergraduate students. While multiple linear regression analysis was used to assess the influence of perceived social support and sense of belonging on academic persistence, mediation analysis was used to test for the mediating effect of sense of belonging on the relationship between perceived social support and academic persistence.

The results revealed that while perceived family support, perceived friendship support and perceived support from others did not significantly predict academic persistence, a sense of belonging significantly predicted academic persistence. The results also demonstrated that a sense of belonging significantly mediated the relationship between perceived family support and academic persistence. Further, the sense of belonging significantly mediated the relationship between perceived support from others and academic persistence.

The results of the study imply that distance learning institutions should strengthen student support mechanisms and institute steps to create learning environments that engender belongingness to enable students to persist academically and reach their academic goals.

This study outlines practical strategies that distance learning institutions could use to enhance support and bolster belongingness among students to help them complete their studies.