Academic dropout remains a significant challenge for education systems, necessitating rigorous analysis and targeted interventions. This study employs machine learning techniques, specifically random forest (RF) and feature tokenizer transformer (FTT), to predict academic attrition. Utilizing a comprehensive dataset of over 40 000 students from an…

While student attrition constitutes a major institutional concern at the undergraduate level, this topic is overlooked at the master's level. Dropout rates have been documented, but no solid predictive models are to be found. Likewise, little is known about students' decision to terminate their studies. With growing enrolment numbers in…

Many of the first-year undergraduate students who enrol in universities, particularly in top-ranked private universities in Bangladesh, struggle with getting good grades. As a result, many students look forward to a bleak future, dropping out midway through their studies. Thus, improving the rates of graduation and reducing the rates of attrition…

Studies found that students from low socioeconomic backgrounds have higher odds of dropping out from higher education. Academic hardships were also identified as predictors. The current study utilizes data on 45,752 students who started their studies at The Hebrew University of Jerusalem (2003-2015). Descriptive statistics reveal that 18% of all…

This year's study is the 35th in a series of annual reports on trends in dropout and attrition rates in Texas public schools. The 2019-20 study builds on a series of studies by the Intercultural Development Research Association (IDRA) that track the number and percent of students in Texas who are lost from public school enrollment prior to…

Attrition from Canadian graduate programs is a point of concern on a societal, institutional, and individual level. To improve retention in graduate school, a better understanding of what leads to withdrawal needs to be reached. This paper uses logistic regression and discrete-time survival analysis with time-varying covariates to analyze data…

This investigation sought to determine when colleges should conduct assessments to identify first-year students at risk of dropping out. Thirty-five variables were used to predict the persistence of 2,024 first-year students from four universities in the southeastern United States. The predictors were subdivided into groups according to when they…

The main aim of this study was to gain a better understanding of why students abandon their studies, or perform less well than expected given their high school grades, and to develop predictive models that can help identify those students most at-risk at the time they enter college. This will allow teachers and those responsible for student…

Family socioeconomic status, ability, high school curriculum, scholarship receipt, age, race, marital status, enrollment status, employment status, and type of college attended were examined. The importance of these factors varied widely with year of college completed. Results demonstrated that these factors cannot be molded into a single equation…

Examined the relationship between selected independent variables and graduation from college five years after students (N=1,943) first matriculated. Results showed that the variables accounted for less than six percent of the variability in the graduate/nongraduate criterion with high school rank being the best individual predictor. (Author/LLL)

Data from the National Longitudinal Study of the High School Class of 1972 indicate that women are more likely to withdraw only in two year colleges and that whites are more likely to withdraw than blacks. High school program, college grades, and educational aspiration are significantly related to withdrawal, but receipt of financial aid is not.…

Multiple linear discriminant function analyses were performed using academic, performance, and personality variables to discriminate among groups of transfers, persisters, and dropouts two years after college matriculation. Analysis of all variables combined added no predictive power beyond that by either subset alone. The results held up on…

The relationship between attrition and a student's personality type was studied, using the Myers-Briggs Type indicator (MBTI), which classifies people according to extraversion/introversion, sensing/intuition, thinking/feeling, and judgment/perception. In a second study, the extent to which a student's congruence with the personality types of…

Of 115 adult literacy students interviewed, 59 were contacted 8 months later to collect data on characteristics, academic and social integration, program and goal commitment, and withdrawal decisions. Factor and discriminant analyses identified 14 variables that accurately predicted the present status of 76 percent of completers, persisters, and…

This survey of a national sample of 451 deaf adolescents found that many factors predicting attrition in general education also apply to deaf education. These include individual ability, local educational values, and demographic traits. Regional differences were also found, with programs in the southeast and southwest losing more students than…