University Dropout Research Articles

A place too crowded to study: The impact of student cohort growth on the probability of university dropout

Introduction: This study examines the influence of major fluctuations in the number of students enrolling at university on the probability of dropout or a switch to a different course of study. Findings from the US show that a pronounced increase in student numbers leads to more dropouts. Materials and methods: This article provides an analysis of this relationship for the first time outside the US and for an entire university system. We use administrative data for all the students who started studying at Swiss universities between 1980 and 2001. Results: The results suggest a significant relationship between positive cohort growth and the probability of dropout. A reduction in student numbers, on the other hand, does not increase the probability of persistence. Discussion: Despite the negative influence of a big cohort on the probability of persistence, no statistically significant relationship exists, by contrast, between the change in student numbers and the probability of a student switching to a different course of study.

Analysis of the attrition phenomenon through the lens of university dropouts in the United Arab Emirates

PurposeTheoretical 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.Design/methodology/approachTinto’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.FindingsSeveral 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.Research limitations/implicationsDespite 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.Practical implicationsThe 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.Originality/valueThe 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.

Supplemental Material for Linking Changes in Perceived Academic Control to University Dropout and University Grades: A Longitudinal Approach

Supplemental Material for Linking Changes in Perceived Academic Control to University Dropout and University Grades: A Longitudinal Approach

Beyond university dropout. An approach to university transfer

ABSTRACT Degree transfer is understood as the increasingly common phenomenon among students of changing university degrees or university, especially after the first or second years of the degree. The profile of students who transfer (3,861students, 8.3% of students) is constructed based on microdata from the University Pre-enrolment Register of Catalonia and an explanatory model is validated by means of Multivariate Logistic Regression. Transfer refers to both changing the area of knowledge or the university and occurs most frequently in engineering, experimental sciences and social sciences degrees. The profile of the student who transfers is male, does not balance paid employment with studying, has completed baccalaureate in a private or a state-funded private school, and is upper middle class with both parents with a higher-level education working in higher management positions or liberal occupations. His level of use of social networks and digital communication tools is very high.

Determinants of University Dropout: A Case of Thailand

Student dropout is a growing concern for educational institutions across the world and extensive research on this issue has been done in past few decades. In this study, we analyzed the determinants of student propensity to dropout at Prince of Songkla University, Pattani campus. The data comprised 10,377 students enrolled between the 2007 and 2011 academic years. Variables included in the analysis were admission year, faculty, gender-religion, first semester GPA and admission type. The overall dropout rate over the five-year period was 23.9%, and a decreasing trend in dropout rate was found from second semester and onwards. A logistic regression model was used to determine the effect of explanatory variables on dropout. The findings indicate that admission year, gender-religion, faculty and first semester GPA are strongly associated with student dropout.

Dropout and transfer paths: What are the risky profiles when analyzing university persistence with machine learning techniques?

University dropout is a growing problem with considerable academic, social and economic consequences. Conclusions and limitations of previous studies highlight the difficulty of analyzing the phenomenon from a broad perspective and with bigger data sets. This paper proposes a new, machine-learning based method, able to examine the problem using a holistic approach. Advantages of this method include the lack of strong distribution hypothesis, the capacity for handling bigger data sets and the interpretability of the results. Results are consistent with previous research, showing the influence of personal and contextual variables and the importance of academic performance in the first year, but other factors are also highlighted with this model, such as the importance of dedication (part or full time), and the vulnerability of the students with respect to their age. Additionally, a comprehensive graphic output is included to make it easier to interpret the discovered rules.

Analysis of Correlation between the Characteristics of University Students and Dropout

Analysis of Correlation between the Characteristics of University Students and Dropout

Simulation of the leaky pipeline: Gender diversity in U.S. K-graduate education

ABSTRACT What is the future trend of gender (dis)parity in the U.S. higher education and workforce populations? I take a systems approach to develop a dynamic simulation model of gender diversity in U.S. higher education. The model consists of an education pipeline for males and females and includes several mechanisms that reinforce interest in higher education or affect university admission or dropout rates. I simulated a model and examined its fidelity in replicating the historical data of U.S. higher education from 1970 to 2014. I then simulated the model to forecast future gender composition trends at different levels of education over the next two decades. The model forecasts that women will be the majority of university degree holders in the United States by 2035 (i.e., female to male ratio of 1.7 for advanced degrees) with lower dropout rates. Additionally, a discussion is provided on the study’s findings and subsequent implications.

Educational Practices for Diminishing the Dropout Risk of the First-Year College Students from an Agronomic University in Romania. Preliminary Considerations

Communication drills a strategic direction of the management of the Faculty of Agriculture, within the University of Agricultural Sciences and Veterinary Medicine, to support the first-year students that are exposed to the risk of university dropout, belonging, in particular, to the disadvantaged groups. The target group was formed in the university year 2017-2018 out of a number of 150 students, who met the criteria of the project.Among these, 77 students (48 %) got grades of 7 or below 7 at the Baccalaureate; 77 (51,3 %) belong to monoparental , low income families or with parents who work abroad; 83 (55,3 %) come from the countryside; 10 (6%) are orphans of one parent or both parents; 2 (0,13) have been in foster care, orphanages or similar institutions. Moreover, older research (Stanciu &al, 2011) showed that the main problem the first-year students have to face in their effort to fit into the academic work is the lack of skills of efficient learning (almost 78%).The courses of action for diminishing university dropout were the following: the awareness of the age and individual peculiarities of the students; the emphasis of the teaching-learning-assessment process on the student; the initiation and the running of social-emotional development programmes; the individualized counseling of the students for facing the accommodation problems which may occur during the first years of the bachelor studies; the familiarization with the efficient learning techniques which may break new grounds toward lifelong learning; the learning of efficient communication techniques; the involvement in volunteering actions; the development of a partnership between the family, the university, the community and the economic entities.

University dropout. Causes and solution

The phenomenon of university dropout is met in all universities in the world and its effects are felt both at the economic level, at the level of society and at the personal level of students who abandon the university. Factors leading to university dropout may be of a social nature (student background, income level, so on.), psycho-pedagogical (inadequate academic training, inconsistency between prior training and university studies, lack of counseling services, so on)and personal (poor adaptability to the university, low levels of socio-emotional intelligence, so on). Universities need to cope with this phenomenon and adapt and develop prevention and intervention services so that students' retention rate rises. The paper analyzes this phenomenon in The Bucharest University of Economic Studies and identifies possible solutions for diminishing the phenomenon.

Trajectory of University Dropout: Investigating the Cumulative Effect of Academic Vulnerability and Proximity to Family Support

University dropout is a major policy concern around the world because of its consequences for the individual, institutions and society. In this study, we offer new evidence by examining the cumulative effect of academic vulnerability and family support on trajectory of dropout among cohorts of undergraduate students in Thailand. Data were drawn from administrative records of two cohorts of students (n=1613), and consisted of information on which semester individual’s dropped out of university. Using discrete time survival analysis, we first modelled the trajectory of dropout without predictors followed by a conditional model which examined the effects of predictors on the trajectory of dropout. Cumulative effects of predictors were then examined by plotting the probabilities of their combined effects on dropout in each semester. Our findings show that while the beginning of the second year was a critical period of dropout with almost 20% of students leaving by this time, as much as 10% of students drop out between the second and final year. Students with the lowest entry grades were about 2.17 times more likely to dropout while those who were farther away from family support were 1.32 times more likely to drop out across each semester. The cumulative effect of low entry grades and living away from family support resulted in a 30% probability of dropping out in the second year. The dropout rate among this category of students by the final year was 60% compared to only 14% for students with high entry grades and who live close to their families. Among other things, we recommend that interventions to reduce dropout should encompass both helping students to access family support and develop personal connections at university to compensate for absence of family support, as well as academically focused support for student who do not have a strong entry qualification.

University dropouts vs high school graduates in the school-to-work transition

PurposeThe purpose of this paper is to consider the enrolment at university and the subsequent possible dropout as a piece of the school-to-work transition and ask whether it improves or worsens the labour market outcomes a few years after graduation from the high school.Design/methodology/approachThe analysis exploits data from the upper secondary graduate survey by ISTAT on a cohort of high school graduates and investigates the effect of dropping out four years after graduation. The labour market outcomes of university dropouts are compared to the outcomes of high school graduates who never enrolled at university. A propensity score matching approach is applied. The model is also estimated on the subsamples of males and females.FindingsThe findings show that spending a period at university and leaving it before completion makes the transition to work substantially more difficult. Both the probability of being NEET and getting a bad job increase in the case of dropout, while no relevant effect is found on earnings. Moreover, the impact of university dropout tends to be more harmful the longer the spell from enrolment to dropping out. Separate estimates by gender point out that females appear to be relatively more affected in the case of dropping out without a fallback plan.Originality/valueWhile the existing studies in the literature on the school-to-work transition mostly focus on the determinants of the dropout, this paper investigates whether and how the employment outcomes are affected by dropping out in Italy. Moreover, university dropouts are compared to high school graduates with no university experience, rather than to university graduates. Finally, evidence on the mechanisms driving the effect of dropping out is provided, by considering timing and motivations for dropping out.

Predicting University Dropout trough Data Mining: A systematic Literature

Objectives: To make a systematic review of literature on the prediction of university student dropout through data mining techniques. Methods/Analysis: The study was developed as a systematic review of the literature of empirical research results regarding the prediction of university dropout. In this phase, the review protocol, the selection requirements for potential studies and the method for analyzing the content of the selected studies were provided. The classification presented in section 3 allowed answering the main research question. What are the aspects considered in the prediction of university student desertion through data mining? Findings: University dropout is a problem which affects universities around the world, with consequences such as reduced enrolment, reduced revenue for the university, and financial losses for the State which funds the studies, and also constitutes a social problem for students, their families, and society in general. Hence the importance of predicting university dropout, that is to say identify dropout students in advance, in order to design strategies to tackle this problem. Novelty /Improvement: This is the first work to perform an integral systematic literature review about university dropout prediction through data mining, with studies from 2006–2018. Keywords: Data Mining, Dropout Factors, Dropout Prediction, Machine Learning, University Student Dropout

Delayed Graduation and University Dropout: A Review of Theoretical Approaches

Delayed Graduation and University Dropout: A Review of Theoretical Approaches

Integration of Data Technology for Analyzing University Dropout

Dropout, defined as the abandonment of a career before obtaining the corresponding degree, considering a significant time period to rule out the possibility of return. Higher education students´ dropout generates several issues that affect students and universities. The results obtained from the data provided by the Engineering departments of the University of Mumbai, in India, determine that the variables that best explain a student’s dropout are the socioeconomic factors and the income score provided by the University Admission Test (UAT). According to the decision tree technique, it is concluded that the retention is 78.3%. The quality of the classifiers allows to ensure that their predictions are correct, with statistical levels of ROC curve are 76%, 75%, and 83% successful for Bayesian network classifiers, decision tree, and neural network respectively.

Formação e Vocação: Palestras de Divulgação Científica para a Educação Básica na Amazônia

Apesar da gama de pesquisas realizadas em universidades e instituições brasileiras, nas mais diversas áreas do conhecimento, a carreira científica tem permanecido pouco procurada pelos jovens que planejam ingressar em cursos de nível superior. Além da variedade de fatores socioeconômicos que podem ser abordados na tentativa de explicar esta baixa procura, o pequeno número de iniciativas especializadas em divulgação científica com foco em escolhas profissionais voltadas à ciência e à tecnologia também pode ser evidenciado. Com a possibilidade de aproximar os estudantes da realidade das carreiras científicas e acadêmicas, e estabelecendo o contato dos jovens com pesquisadores e suas pesquisas, pode-se contribuir para a escolha profissional, reduzindo índices de evasão universitária ocasionados pela falta de conhecimento acerca do curso pretendido. Neste artigo, relatamos a promoção de palestras de divulgação científica, desde a década de 1960, na Amazônia brasileira, a evolução destas ações educativas com o passar dos anos na comunidade amazônica, além de outras atividades congêneres realizadas atualmente por iniciativas de divulgação científica da Universidade Federal do Pará.

Indicadores academicos de deserción en Estudiantes de pregrado de la universidad libre - Seccional socorro

El presente proyecto tiene como objetivo diagnosticar los factores académicos intervinientes en la deserción de estudiantes de pregrado de los tres primeros niveles de formación de la Universidad Libre - Seccional Socorro, con un tipo de investigación correlacional con carácter transversal. Puesto que se va comprobar, si la presencia de ciertos factores o variables inciden en el comportamiento de otros. Lo anterior a través de pruebas estadísticas objetivas en donde la recolección de la información y análisis dela misma, se efectuará en un periodo de tiempo específico, en este caso II semestre 2016. Como resultados preliminares se encontró: Las problemáticas más comunes que presentan los estudiantes a nivel del desempeño académico, así como la caracterización de los hábitos de estudio empleados por los estudiantes, las actividades desarrolladas para mejorar el desempeño académico y la identificación de algunas estrategias empleadas por los docentes para contrarrestar esta problemática y el rol que desempeña el docente en estos casos.

A Multinomial and Predictive Analysis of Factors Associated with University Dropout

The phenomenon of dropout, by its complexity and educational and social impact, has been extensively studied to understand the specific causes. In this line of research, the purpose of this study was to analyze explanatory and predictive models of student dropout from university studies at the Instituto Tecnológico de Costa Rica (TEC), based on many variables recorded in the institutional system indicators. The first stage of the analysis considered multinomial regression models to identify the influence of these variables on the dropout. In the second analysis, six machine learning algorithms were evaluated in order to find a model that would predict student dropout. Data analysis showed that the probability of dropping out is related to sociodemographic variables, study program, academic history, scholarship and other benefits, and performance after first semester. In addition, the best predictor of dropout algorithm was the “random forest”, a probability of 0.83 to predict the dropout correctly and to capture 34% of the actual student dropout. These results are the first step toward building a more robust predictive model of dropout, which will contribute to preventive decision making in this university.

Sustainable Education: Analyzing the Determinants of University Student Dropout by Nonlinear Panel Data Models

University dropout is a serious problem. It affects not only the individual who drops out but also the university and society. However, most previous studies have focused only on the subjective/individual level. University dropout is a very important issue in South Korea, but it has not received much research attention so far. This study examined the possible causes of university dropout in South Korea at the aggregate level, focusing on four fundamental categories: students, resources, faculty, and university characteristics. Three-year balanced panel data from 2013 to 2015 were constructed and estimated by using nonlinear panel data models. The findings show that cost and burden for students, financial resources, qualitative and quantitative features of faculty, and type/size of the university have significant effects on university dropout.

The Effect of Grants on University Drop-Out Rates: Evidence on the Italian Case

In this paper we evaluate the impact of need-based grants on university drop-out rates in the first year of enrollment, using student-level administrative data from all Italian universities in the period 2003-2013. We exploit the fact that not all eligible students receive financial aid due to limited resources to generate a treatment and a control group. Using this partition, we estimate the average treatment effect, i.e. the average effect on low income students, controlling for a set of observable characteristics by running regressions on blocks defined on the propensity score. Results point towards a sizeable effect of grants in reducing dropping out from higher education: around one third of these students would have left university in the first year in absence of the grants. This evidence is robust to a variety of specifications and sample selection criteria.