Student Attrition Research Articles

A scale for measuring member commitment and integration in fitness services

This study assesses the reliability and validity of an instrument adapted from the domain of student attrition in higher-education research, for implementation in the field of fitness services management. The study was conducted at a commercial fitness facility based in Dubai, UAE, and comprised 184 subjects. A questionnaire was created by adapting a model with extensive research support in the field of student attrition studies; modifications were based on Delphi technique and subject interviews. Items were measured on a 5-point Likert scale, and the data set was subjected to exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). Four factors emerged: goal commitment; institutional commitment; social integration; institutional integration. CFA fit indices indicated good model fit, and all factors had strong Cronbach alpha coefficients. The instrument displayed robust psychometric properties/factor-loading invariance, and can be used to measure commitment and integration constructs in commercial fitness-club settings.

Academic Suicide: Scenarios of Doctoral Student Attrition in Russia

Doctoral student attrition is one of the most debated problems in higher education. Related studies are few in Russia, mostly being of applied type and offering no theoretical approaches to research on departure from doctoral study. Tinto’s model of student departure based on Durkheim’s theory of suicide is the most widespread theoretical framework among U.S. and European researchers. However, Tinto’s model only considers egoistic suicide. The present study offers an integrated approach to Durkheim’s theory, demonstrating the potential of applying the entire theoretical typology of suicide to analyze scenarios of doctoral student attrition. Interviews with doctoral students who did not finish their thesis were used to identify the major challenges faced by doctoral candidates and to provide recommendations for overcoming the problem of non-completion in Russian doctoral education.

A scale for measuring member commitment and integration in fitness services

This study assesses the reliability and validity of an instrument adapted from the domain of student attrition in higher-education research, for implementation in the field of fitness services management. The study was conducted at a commercial fitness facility based in Dubai, UAE, and comprised 184 subjects. A questionnaire was created by adapting a model with extensive research support in the field of student attrition studies; modifications were based on Delphi technique and subject interviews. Items were measured on a 5-point Likert scale, and the data set was subjected to exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). Four factors emerged: goal commitment; institutional commitment; social integration; institutional integration. CFA fit indices indicated good model fit, and all factors had strong Cronbach alpha coefficients. The instrument displayed robust psychometric properties/factor-loading invariance, and can be used to measure commitment and integration constructs in commercial fitness-club settings.

Exploring the Causes of Student Attrition in South African TVET Colleges: A Case of One KwaZulu-Natal Technical and Vocational Education and Training College

The Technical and Vocational Education and Training (TVET) Colleges are the cornerstone in addressing unemployment, poverty and building the economy of the Republic of South Africa by producing well-equipped artisans. TVET Colleges are expected to enrol 2.5 million students by 2030 (Branson et al. in S Afr Child Gauge 1:1–8, 2015). To achieve this, the TVET Colleges should have a sound throughput at the end of each academic cycle. However, the main challenge faced by the TVET Colleges and the Department of Higher Education and Training at large is high levels of student attrition which impede the TVET Colleges from achieving their goals. This study sought to ascertain the nature of and the reasons behind this high attrition rate. The acquisition of this knowledge should be an essential step in addressing the problem. Drawing on a mixed-methods approach, this study conducted interviews (N = 20) and questionnaire surveys (N = 100) with purposively selected staff and students at one TVET College in KwaZulu-Natal Province. The findings show that attrition is high and uniform across the programmes and campuses. Factors behind the high attrition rate at the TVET Colleges include dissatisfaction with the programs offered, inadequate student induction and inadequate student work placement. This study concluded that the causes of student attrition are multidimensional and multi-sourced. A multi-pronged strategy implemented by responsible stakeholders is required to solve this problem.

A predictive analytics framework as a countermeasure for attrition of students

ABSTRACTAttrition is one of the main concerns in distance learning due to the impact on the incomes and institutions reputation. Timely identification of students at risk has high practical value in effective students’ retention services. Big Data mining and machine learning methods are applied to manipulate, analyze, and predict students’ failure, supporting self-directed learning. Despite the extensive application of data mining to education, the imbalance problem in minority classes of students’ attrition is often overlooked in conventional models. This document proposes a large data frame using the Hadoop ecosystem and the application of machine learning techniques to different datasets of an academic year at the Hellenic Open University. Datasets were divided into 35 weeks; 32 classifiers were created, compared and statistically analyzed to address the minority classes’ imbalance of student’s failure. The algorithms MetaCost-SMO and C4.5 provide the most accurate performance for each target class. Early predictions of timeframes determine a remarkable performance, while the importance of written assignments and specific quizzes is noticeable. The models’ performance in any week is exploited by developing a prediction tool for student attrition, contributing to timely and personalized intervention.

Enabling Success in Nursing School: Description of an Innovative Student-Led Program.

Nursing student attrition rates are high in BSN programs. Peer support programs can address challenges associated with attrition. This article describes a student-led program created to address the needs of first- and second-year nursing students. The program combined mentorship with quarterly academic workshops that focused on common challenges among nursing students. Following the program, students reported increased academic confidence, enhanced preparedness for nursing courses, improved sense of community, and decreased self-reported anxiety related to nursing school. Student-led programs are feasible means to creating prepared, resourceful, confident, and successful nursing students.

Analysis of social media forums to elicit narratives of graduate engineering student attrition

AbstractBackgroundGraduate engineering student attrition is prevalent, but most literature that studies graduate attrition is accomplished in disciplines outside of STEM or engineering, yielding an incomplete understanding of either attrition or persistence.Purpose/HypothesisThe purpose of this article is to investigate the relationships between motivators of attrition for engineering graduate students.Design/MethodData were collected using an online Web‐scraping “bot” that mines data from the online forum Reddit. The anonymous textual forum threads collected were qualitatively analyzed through open‐coding methods.ResultsThe emergent themes reveal the interconnectedness between the roles of the advisor, student perception of cost, their support network, goals, their perceptions of how others perceive them, and quality of life and work. Our model is flexible in that it illuminates underlying combinations of factors that can influence student attrition.ConclusionThis study provides a framework by which various stakeholders can approach the support and education of graduate students, including mentoring students both toward or away from graduate school per the student's goals.

Admission Assessment: Linking a Standardized Admission Exam to Nursing Program Outcomes

This article reports the results of an academic program evaluation in which standardized admission test scores are compared to intermediate and final program outcomes. We used two intermediate program measures of progress-first semester nursing grades and performance on a standardized exit exam prior to graduation. Program final outcomes compared are student attrition and graduate nurses’ performance on the NCLEX-RN®. The analysis resulted in identifying statistically significant relationships between entrance exam scores and first semester grades. Statistically significant relationships were seen between entrance exam scores and performance on a pre-graduation exit exam. There was a statistically significant relationship between entrance exam scores and NCLEX-RN® pass rates. These results indicate that admission testing is a viable option for use as part of an admission process for baccalaureate nursing programs.

Advisor Selection, Advisor-Advisee Relationship, and Perceived Stress among Korean and US Doctoral Students

In recent decades a prolific amount of research has been conducted into the topic of students’ relationships with supervising professors as key to doctoral experiences and success. Across different education systems, positive relationships between doctoral students and their advisors have been strongly associated with socialization into their departments and disciplines, as well as overall satisfaction with doctoral programs. While faculty-student relationship has been widely studied as one of the most important factors affecting student satisfaction and attrition, little is known about how the choice of advisor and how advisor-student relationships are related to stress. Data was collected by administrating a survey of students enrolled in doctoral programs from a public, research-intensive university in the Midwest of the United States and a public, research-oriented institution in South Korea. The findings indicate that US students were generally more positive about the advisor-advisee relationship than Korean students and both Korean and US doctoral students’ concerns were largely related to post-graduation options.

Assessment on Factors Causing Female Students Attrition at Haramaya University, Ethiopia

Assessment on Factors Causing Female Students Attrition at Haramaya University, Ethiopia

A predictive analytics framework as a countermeasure for attrition of students

ABSTRACT Attrition is one of the main concerns in distance learning due to the impact on the incomes and institutions reputation. Timely identification of students at risk has high practical value in effective students’ retention services. Big Data mining and machine learning methods are applied to manipulate, analyze and predict students’ failure, supporting self-directed learning. Despite the extensive application of data mining to education, the imbalance problem in minority classes of students’ attrition is often overlooked in conventional models. This document proposes a large data frame using the Hadoop ecosystem and the application of machine learning techniques to different datasets of an academic year at the Hellenic Open University. Datasets were divided into thirty-five weeks. Thirty-two classifiers were created, compared and statistical analyzed to address the minority classes’ imbalance of student’s failure. The algorithms metacost-SMO, and C4.5 provide the most accurate performance for each target class. Early predictions of timeframes determine a remarkable performance, while the importance of written assignments and specific quizzes is noticeable. The models’ performance in any week is exploited by developing a prediction tool for student attrition, contributing to timely and personalized intervention.

Effect of Virtual Reality on Learning Motivation and Academic Performance: What Value May VR Have for Library Instruction?

The research on whether Virtual Reality (VR) has a positive effect on student learning and engagement is limited. This study aims to examine what impact VR has on student learning motivation and performance. The study conducted by Wang (2017) revealed that VR had a marginally positive impact on student scores and a strong impact on students’ learning engagement. It indicates that VR provides a small improvement in academic performance and a large improvement in student engagement. The application of VR in libraries focuses on providing the VR tools to learn subjects in STEM and history fields. For one-off instructional settings, the boost of learning motivation may increase interest in further investigation and retention. For semester-long courses, increased learning motivation may decrease student attrition or “failure” in the information literacy course.

Strengths and satisfaction in first year undergraduate students: A longitudinal study

ABSTRACT Half of college student attrition occurs in the first year of college, so identifying factors that contribute to student satisfaction is an important target for research. Knowledge and use of one’s strengths are two such variables associated with academic and life satisfaction, but studies establishing these relations have been largely cross-sectional. Therefore, the goal of this study was to examine longitudinal relations from strengths knowledge to strengths use and from strengths use to academic and life satisfaction. While strengths knowledge consistently predicted strengths use over time and strengths use consistently predicted academic satisfaction over time, strengths use did not predict life satisfaction over time. These results have implications for strengths research broadly and for higher education personnel working with first year college students.

Role of Personal and Organizational Factors on Student Attrition From Graduate Education: A Mixed-Model Research

Students in graduate education have a desire to hold a degree because of contributions of graduate education such as opportunity to become faculty member, professional development, and promotion. Despite these benefits of graduate education, there are students who do not persist on gaining a graduate degree. This study aims to develop and test a model to determine the role of personal and organizational factors on student attrition from graduate education and to investigate graduate student attrition from the lenses of students and faculty. The design of the study was mixed-model research. Through a three-staged clustered random sampling and purposeful sampling, respectively, 653 and 36 participants were selected. Results of the correlational analysis indicated that intention to leave graduate education was predicted by personal factors, while the phenomenological part of the study pointed out that personal factors were more visible in student attrition than organizational factors.

Are we losing the battle with nursing student attrition?

Are we losing the battle with nursing student attrition?

Desgranamiento y dificultades de integración a la vida universitaria en Ciencias de la Educación de la Universidad Nacional de La Plata

Este artículo indaga en los problemas de desgranamiento de la matrícula estudiantil y las dificultades encontradas en el proceso de integración a la vida universitaria de estudiantes del primer año de las carreras de Ciencias de la Educación, de la Facultad de Humanidades y Ciencias de la Educación de la Universidad Nacional de la Plata. Específicamente se aborda el caso de lxs estudiantes en situación de desgranamiento de la cohorte 2016. En términos generales, el objeto de esta investigación emerge de la preocupación por los procesos de desgranamiento de la matrícula universitaria durante el tramo inicial de las carreras y el problema del sostenimiento de las trayectorias estudiantiles en el sistema universitario. Los resultados muestran la incidencia significativa en los procesos de desgranamiento de la desigualdad social y de los imaginarios de lxs estudiantes en torno al derecho a la educación.

A Review on Student Attrition in Higher Education Using Big Data Analytics and Data Mining Techniques

A Review on Student Attrition in Higher Education Using Big Data Analytics and Data Mining Techniques

Variables affecting first-year student commitment during the transition to college in Ireland.

Third-level student attrition rates internationally are a cause for concern. Thus, student retention and academic success are top priorities for colleges, and students alike. In addition to this, student well-being is a growing public health concern. This study explores the need to incorporate well-being as a predictor in traditionally academically focused models of student persistence during the transition to college. A cross-sectional web-based survey was conducted with 574 first-year students aged 17-22 years attending a university in Ireland to examine the effect of student persistence and well-being variables on student commitment during the transition to college. This study highlights the connection between student academic, social and well-being variables during the transition to college within the fitted models that emerged from the data. Student well-being plays a key role ensuring student persistence during the transition to college. The results support our hypothesis that many student variables have the potential to substantially impact student commitment during the first-year transition to college. These variables include student depression, self-rated health, academic environment, peer connections and perceiving the academic programme to be an appropriate personal choice. It is therefore important for education institutions to acknowledge and address student persistence and student well-being in an integrative way and for traditionally academically focused student retention models to orientate to incorporate student well-being.

Study of the Scale and the Reasons of Student Dropout from Technical University

The article addresses the problem of student dropout from technical university due to their academic failure. The modern technical universities face a decline in youth’s interest to technical and natural sciences and engineering specialties. In enrolling new students on these specialties the universities have to set lower standards and requirements for the admission. So, the students are less motivated, and the number of expelled students increases.The article presents the results of data analysis for the two leading areas of training at Moscow Automobile and Road State Technical University (MADI) – “Construction of unique buildings and structures” and “Land transport and technological means” carried out respectively at the Road-Building faculty (DSF) and the faculty of Automobile transport (ATF). The article adduces the total number of students in MADI, as well as the number of the enrolled students on the specified training directions, and the number of expelled students of all courses for the period from 1935 to 2018. The results in physics exams showed by undergraduate students were compared with the Unified State Exam scores in physics. There is a clear parallel between the Unified State Exam scores, an entrance testing and “residual knowledge” tests.The authors have also analyzed the results of an anonymous questioning among the same groups of students, which make it possible to understand their point of view on the problems of learning difficulties. The main reasons for student attrition are both the low scores of the applicants’ results of the Unified State Exam, and insufficient actions and ineffective strategies undertaken by the university to involve undergraduate students in its educational environment.

Strategies to Assist Distance Doctoral Students in Completing Their Dissertations

Completing doctoral dissertations is difficult work and may be harder for distance students physically separated from institutional and collegial supports. Inability to complete independent research contributes to doctoral student attrition. Factors impacting completion include institutional factors, student characteristics, and supervisory arrangements (Manathunga, 2005). This paper shares proactive strategies used by a Midwestern university in the United States to support distance doctoral students. Strategies and technology tools are described that (a) cultivate a shared culture of responsibility and commitment, (b) increase effective communication between researchers, and (c) grow departmental and institutional services and technologies for faculty and students. This paper suggests the use of a specific framework to help students develop a shared culture of responsibility. This framework encourages students to discuss their social network, as well as teaches students how to manage their split life by using a tool which evaluates a student’s readiness for the dissertation process and maps out where dissertation skills and knowledge are developed throughout the program. Strategies for effective communication include availability, effective feedback, trust, and humor. Services and technologies provided to build capacity include the use of online and library resources, campus-wide use of research software, writing and research services, and department supports and processes to promote student research. These mechanisms for accountability, mentoring, training, and trust increase the likelihood of success.