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Theoretical models of attrition have failed to address the interwoven factors from the perspective of undergraduate students that influence their decision to drop out. The purpose of this paper is to unravel these complexities using a qualitative phenomenological approach to gain systematic descriptions of the experience of non-completion.

Tinto’s (2004) and Bean and Metzner’s (1985) models serve as the theoretical construct for the study’s design and analysis. In-depth interviews were conducted with 41 students who discontinued studies at universities in the United Arab Emirates, to understand the situations that led them to drop out of university and how they experienced this event in their lives.

Several issues were identified as contributing factors for dropping out that are consistent with those found in the international literature. Additional issues were more gender or culture specific and, to some extent, represented the differences that signal a social development that is in a transitional stage. The findings revealed that institutional factors, poor pre-college preparation, environmental factors (work-education conflict), early marriage responsibilities, well-paid job opportunities and financial concerns were most influential.

Despite the limitations of relying on a small sample to generalize findings, the rich detail of this inductive study has added to the understanding of the dropout phenomenon in a new context.

The paper recommends both remedial and early intervention strategies to be undertaken by the Ministry of Education and universities. Remedial strategies include re-examining the desired standard of English as a condition for admission and adjusting the grading system. Early intervention measures that accommodate the needs of at-risk students are also proposed. At local, regional and international levels, higher education should be freed from commodification and inflated fees.

The paper presents a significant departure from the largely North American and European literature on the university dropout, by offering a broader knowledge of this phenomenon in another regional and national context.

Factors considered important for predicing attrition were extracted from the research done on university dropouts for the past twenty‐five years and integrated into a conceptual model. Stepwise discriminant analysis coupled with logit regression analysis of freshman data from Brandon University yielded six variables: student status, residence, financial sources, distance of hometown from the university, goal fulfilment, and satisfaction with overall university atmosphere, which were useful in prediction. Several recommendations are made for minimizing the withdrawal phenomenon.

This paper aims to address the issue of why students want to drop out from a course and suggests appropriate strategies to enhance student retention.

A sample of 260 hospitality management students were surveyed based on both Tinto's model of student–institution integration and a theory of planned behavior on student departure. The research applies data mining and decision tree using the classification and regression trees (CART) method as an analytic tool to identify a group, discover relationships between groups and predict future events for segmentation.

The results regarding the demographics indicate that the most critical factors of dropout included residency status, financial situation, quality of class and occupation.

This is a limited US sample, based on student perceptions only and not lecturer or institution perceptions.

The paper provides empirical evidence of student perspective along with institutional and learning environment factors. It includes data from students who are currently enrolled (which previous literature has not covered) by testing student–institution integration and planned behavior on student departure.

Using data from the Children of Immigrants Longitudinal Study, this study examines the structural relationships between negative school social relationships, school safety, educational expectation, and academic achievement of Latino immigrant students. Results from multilevel structural equation modeling show that discrimination, unhelpful school social relationships, and experiences of unsafe school environments influence Latino immigrant adolescents’ academic achievement indirectly and directly through their educational expectations. Specifically, this study explores how noncognitive and contextual factors embedded in different structural layers of school organization influence Latino immigrant adolescents’ academic achievement. It draws attention to the impact of negative school factors such as discriminatory and unsupportive school social relationships, and negative and unsafe school structures that undermine school life. Based on our findings, we argue that as Latino immigrant students internalize negative experiences from their school experiences during the critical period of adolescence, such accumulated negative internalization may reinforce negative self-perceptions and inaccurate stereotypes. Not only discrimination but also other negative school features such as the absence of academic supporters, nonacademically oriented friends, and unsafe learning environments inhibit them from navigating positive school opportunities and ultimately, successful school achievement. Implications for the social organization of U.S. public secondary schools with a focus on Latino immigrant adolescents’ academic achievement are discussed.

A common perception about immigrant assimilation is that association with natives necessarily speeds the process by which immigrants become indistinguishable from natives. Using 2000 Census data, this paper casts doubt on this presumption by examining the effect of an immigrant's marriage to a native, a measure of social integration, on dropout rates of children from these marriages. Although second-generation immigrants with one native parent generally have lower dropout rates than those with two foreign-born parents, the relationship reverses when steps are taken to control for observable and unobservable background characteristics. That is, immigrants that marry natives have children that are more likely to drop out of high school than immigrants that marry other immigrants. Moreover, gender differences in the effect of marriage to a native disappear in specifications which control for the endogeneity of the marriage decision.

On the theoretical level, this chapter examines the mechanisms through which cultural and financial capital affects educational outcomes in different institutional contexts. On the methodological level, the central question in this chapter is how to resolve concerns in comparative analyses of educational attainment, such as variations in enrolment rates and study program duration across institutional settings. On the empirical level, the chapter asks whether family background predicts educational attainment in similar ways in two diametrically opposed welfare states: the United States and Norway. Differences in dropout from higher education were compared using nationally representative longitudinal data from the United States and Norway and event history and multilevel modelling techniques. The chapter also makes use of the standardized sheaf coefficient to summarize central background variables for more direct comparison of effect sizes. The findings show that whereas parents’ education level has strikingly similar effects on students’ dropout probabilities in the two countries, the effect of parents’ income varies substantially according to the institutional context. The chapter concludes that in comparative analyses of inequality in education the value of different types of family resources must be understood in light of the concrete, practical constraints of the national institutional contexts.

This study investigates why contributors to online volunteer organizations reduce activity or discontinue volunteering. First, this analysis, based on a survey of over a 100 English Wikipedia’s volunteers with the highest edit count, identifies a gap in the research on volunteers burnout/dropout, namely the importance of interpersonal conflict as an understudied yet highly significant factor. Second, this analysis has practical implications for the sustainability of the Wikipedia project. Third, this analysis should outline an underrepresented issue that if generalizable, may help other volunteer organizations identify a key area related to their volunteer burnout/dropout.

This paper aims to provide a parsimonious but rigorous model to assist decision-makers to determine critical factors which can lead to higher graduation rates amongst higher education institution (HEI) participants. It predicts the odds of dropout amongst university students, using HEI data from a developing country. This is used as a basis for a Student Retention Predictive (SRP) Model to inform HEI administrators about predicted risks of attrition amongst cohorts.

A classification tool, the Logistic Regression Model, is fitted to the data set for a particular HEI in a developing country. The model is used to predict significant factors for student dropout and to create a base model for predicted risks by various student demographic variables.

To reduce dropout and to ensure higher graduation rates, the model suggests that variables such as age group, faculty, academic standing and cumulative GPA are significant. These indicative results can drive intervention strategies to improve student retention in HEIs and lessen the gap between graduates and non-graduates, with the goal of reducing socio-economic inequalities in society.

This research employs risk bands (low, medium and high) to classify students at risk of attrition or drop out. This provides invaluable insights to HEI administrators in the development of intervention strategies to reduce dropout and increase graduation rates to impact the wider public policy issue of socio-economic inequities.

User-generated content (UGC) refers to semantic and behavioral traces created by users on various social media platforms. While several waves of platforms have come and gone, the long-term sustainability of UGC activities has become a critical question that bears significance for theoretical understanding and social media practices.

Based on a large and lengthy dataset of both blogging and microblogging activities of the same set of users, a multistate survival analysis was applied to explore the patterns of users' staying, switching and multiplatforming behaviors, as well as the underlying driving factors.

UGC activities are generally unsustainable in the long run, and natural attrition is the primary reason, rather than competitive switching to new platforms. The availability of leisure time, expected gratification and previous experiences drive users' sustainability.

The authors adopted actual behavioral data from two generations of platforms instead of survey data on users' switching intentions. Four types of users are defined: loyal, switcher, multiplatformer and dropout. As measured by the transitions among the four states, the different sustainability behaviors are thereby studied via an integrated framework. These two originalities bridge gaps in the literature and offer new insights into exploring user sustainability in social media.

The purpose of this paper is to assess how wages of US native workers with various educational backgrounds are affected by immigration.

This paper estimates the responses of these workers’ wages to the concentration of immigrants with various educational backgrounds in their local labour markets, using 1980‐2000 US Census data and instrumental variables approach.

Wages of native high school dropouts fall slightly in the presence of immigrant high school dropouts and high school graduates; wages of native high school graduates fall slightly in the presence of immigrant high school graduates, but rise in the presence of immigrants with higher levels of education; wages of native workers with some college education fall slightly with larger concentrations of immigrant high school graduates but rise slightly with larger concentrations of immigrant college graduates; and there is no evidence that wages of native college graduates are affected by immigration.

No previous studies have considered these possibilities when assessing the impact of immigration on native workers’ wages.