Search results

The 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.

The 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.

The 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.

While 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.

This study aimed to use enrollment information including demographic, family background and financial status, which can be gathered before the first semester starts, to construct early prediction models (EPMs) and extract crucial factors associated with first-year student dropout probability.

The real-world samples comprised the enrolled records of 2,412 first-year students of a private university (UNI) in Taiwan. This work utilized decision trees (DT), multilayer perceptron (MLP) and logistic regression (LR) algorithms for constructing EPMs; under-sampling, random oversampling and synthetic minority over sampling technique (SMOTE) methods for solving data imbalance problems; accuracy, precision, recall, F1-score, receiver operator characteristic (ROC) curve and area under ROC curve (AUC) for evaluating constructed EPMs.

DT outperformed MLP and LR with accuracy (97.59%), precision (98%), recall (97%), F1_score (97%), and ROC-AUC (98%). The top-ranking factors comprised “student loan,” “dad occupations,” “mom educational level,” “department,” “mom occupations,” “admission type,” “school fee waiver” and “main sources of living.”

This work only used enrollment information to identify dropout students and crucial factors associated with dropout probability as soon as students enter universities. The extracted rules could be utilized to enhance student retention.

Although first-year student dropouts have gained non-stop attention from researchers in educational practices and theories worldwide, diverse previous studies utilized while-and/or post-semester factors, and/or questionnaires for predicting. These methods failed to offer universities early warning systems (EWS) and/or assist them in providing in-time assistance to dropouts, who face economic difficulties. This work provided universities with an EWS and extracted rules for early dropout prevention and intervention.

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.

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.

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 study aims at developing an instrument to measure the latent trait propensity to drop out in face-to-face higher education.

Based on Tinto's student integration theory, a 27-item scale was created to measure student propensity to drop out of undergraduate programs. Item response theory was used to evaluate the psychometric analysis of the items. Furthermore, different methodologies were used to evaluate and provide evidence for content validity, response process validity, internal structure validity and criterion-related validity.

With the support of specialists in the construct, the interpretation of the scores for the use of the scale was defined in four levels of propensity: high, moderate, low and very low.

The latent trait propensity to drop out in face-to-face higher education allows the inclusion of new items and aspects in the instrument. Thus, it can be adapted to distance education.

The students' propensity to drop out score can be useful for researchers and administration units in colleges and universities in the planning of permanent institutional actions and programs to take preventive measures.

Minimize dropout in order to raise the educational level of the population and make better use of the resources invested in education.

This study points out when, why and how propensity to drop out can be measured and how scores can be interpreted in the context of the problem.

The purpose of this paper is to reveal how support services for open and distance students are designed, developed and implemented to ensure successful learning to take place, with specific references to the Open University of Sri Lanka (OUSL) and Universitas Terbuka (UT) Indonesia. Success in distance learning is one major challenge for open universities to respond to expectations of students and stakeholders. This study focuses on the strategies of student support services in OUSL and UT, investigating related factors including instructional design and development, learning engagement and motivation, policy and strategy in reducing dropouts, use of OER/MOOCs, and quality assurance.

A qualitative study was employed involving analyses of documents; interviews and focus group discussion with senior administrators, academic staff, students; and on-site observation in locations of teaching and learning.

This research is exploratory in nature. Findings of the study are expected to improve our understanding of student support in distance learning, in which analysis is based on good practices, challenges and rooms for improvement of both OUSL and UT.

Findings of this study reveal practices and lessons learnt that may be useful as reference to open universities, taking into considerations the fact that each open university has been established to address specific challenges in its own unique circumstances.

This research may be adopted as baseline framework for analysis of student support for open universities. Further in-depth study is needed to understand how various aspects of student support contribute to success in open and distance learning.

Scholarship on women in engineering education mainly focuses on the question of how to attract more women to this subject. The topic concerning women in engineering education is here guided by the question of why women leave engineering studies. The paper aims to examine the main conflicts women encounter in engineering education and to derive implications for interventions suited for strengthening institutional bonding forces.

The question is approached through case analyses of 40 interviews with women and men (as the control group) who have left their studies. In addition, repertory grids were carried out with all interviewees and analysed. On the basis of these analyses, five types of dropout could be defined. Two case studies with women are presented in detail in this article. These cases are especially representative of two types of dropout that are characterised by high quotas of women.

The central conflicts of women in engineering education are often either suffering from poor grades or that women being afflicted by a subjective feeling of not gaining a deep understanding of technical phenomena. These two conflicts represent the two pillars of identity formation in engineering education that are necessary to bind students to their studies: passing the exams with good grades and feeling self‐efficacious in the handling of technology.

Up‐to‐date subject‐specific studies on dropout in engineering education – especially with a focus on women – are marginal in Europe, and particularly so in Germany.

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.

Graduation rates are commonly used to assess the quality of higher educational institutions. While universities strive to produce as many graduates as possible, maintaining the right balance between the number of new students enrolled and the number who graduate each year has become a challenge in the past few decades. Timely graduation is often disregarded because a large majority of the students do not graduate within the stipulated time. The purpose of this paper is to analyze the factors associated with timely degree attainment.

The data for this study were obtained from records maintained by Registrar Office, Prince of Songkla University, Pattani Campus, Thailand. The final sample comprised 1,330 undergraduate students enrolled at four major faculties in 2009. A multivariate logistic regression model was applied to explain the effects of independent variables on timely graduation.

About 81.0 percent had completed their degree program within the stipulated time. The results indicated that faculty, first-semester grade point average, gender and place of residence were significantly associated with timely graduation.

Findings from this study may serve as a guide to higher educational institutions in identifying the underlying factors, and accordingly develop programs to enhance on time degree completion rates.