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…

This study examines whether tutors (N?=?15) in a problem-based learning curriculum were able to predict students' success in their first year and their entire bachelor programme. Tutors were asked to rate each student in their tutorial group in terms of the chance that this student would successfully finish their first year and the entire…

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…

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…

A study by Kenney, Kenney, and Dumont (2005) identified a supportive learning environment as one of the five indicators for collegiate student engagement, a concept that extends beyond the classroom to permeate the entire educational environment. A student's level of engagement can be impacted as early as orientation and registration, when he is…

Affecting university rankings, school reputation, and financial well-being, student retention has become one of the most important measures of success for higher education institutions. From the institutional perspective, improving student retention starts with a thorough understanding of the causes behind the attrition. Such an understanding is…

The increasing competition for graduate students among business schools has resulted in a greater emphasis on graduate business student retention. In an effort to address this issue, the current article uses survival analysis, decision trees and TreeNet® to identify factors that can be used to identify students who are at risk of dropping out of a…

Analysis of data on 101 entering proprietary college students found that (1) predictors of initial achievement were entrance exam scores, gender, race, age, grade point average, and expectations; (2) dropout predictors were marital status, work hours, prior achievement, absences, and faculty interaction; and (3) age, gender, race, and children did…

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…

Data from a standardized reading test and student background information were correlated to determine relationships. Self-assessed reading scores and other data may be used for predicting retention, academic performance, and reading ability. Differences were found between persisters and dropouts on these variables. (Author)

Stepwise discriminant analysis coupled with logit regression analysis of freshmen data from Brandon University (Manitoba) indicated that six tested variables drawn from research on university dropouts were useful in predicting attrition: student status, residence, financial sources, distance from home town, goal fulfillment, and satisfaction with…

A causal model to explain student attrition was tested at a major midwestern land-grant university with a sample of 1,513 full-time, unmarried freshmen who were 21 years old or younger. The causal model was reduced from 23 to 10 variables: an intent variable, three attitudinal variables, and two each of organizational, personal, and environmental…

A model of student attrition was synthesized from psychological, sociological, and educational sources, and contains six sets of variables: background, organizational, personal, environmental, attitudinal, and intent to leave. The model was tested with 1,909 full-time and unmarried university freshmen at a major midwestern university. The sample…

Research on student withdrawals has largely ignored the issue of stop-outs, those students who withdraw from a college or university but subsequently reenroll. As a result, student withdrawals have been seen as an attrition issue. However, this study suggests they should be viewed as a retention possibility rather than an attrition issue. This…