Dropout Research Research Articles

Exploring the interplay between vocational competence and dropout intention: insights and perspectives

High drop-out rates from Vocational Education and Training (VET) remain a severe problem in VET systems globally. Despite decades of drop-out research revealing numerous influencing factors, the role of trainees’ vocational competence in their drop-out behavior has been neglected. This study aims to define the structure of vocational competence and analyze its effects on drop-out intention. Using longitudinal data from 458 commercial trainees in Germany, vocational competence is measured at three time points using a validated competence test, subdivided into domain-linked and domain-specific dimensions (Gelman and Greeno, 1989). Four different directions of drop-out intentions are considered, enabling a detailed effect inspection of the prevailing research gap. Additionally, factors identified in previous studies, such as educational level, age, language, and the degree of having chosen one’s desired occupation, are controlled for. We conducted 12 rounds of ordinal logistic regression to test three lagged temporal combinations of the effect relationship between vocational competence and dropout intention over different time spans (T0- > T1, T1- > T2, T0- > T2). We find that lower domain-specific competence increases the intention to drop out from VET without qualification over different time spans. Initial lower domain-specific competence also affects trainees’ intention to change their occupation in the final year of training. Furthermore, higher levels of domain-linked competence at the beginning increase the intention to leave VET to pursue higher qualifications in the midterm of training.

Structuring the complexity of drop-out from VET: a theoretical framework guiding empirical research perspectives

After more than 50 years of research on drop-out from Vocational Education and Training (VET), databases provide vast amounts of drop-out studies from around the globe that entail hundreds of potential drop-out factors. However, many scholars tend to explore the topic without detailed and theoretically grounded foundation. Several diverging research foci exist within the research field of drop-out from VET: Studies differ with regard to the analysed phase of drop-out (development, decision-making, paths after dropping out), the applied sample perspective (learners, educators, further stakeholders), and the overall research perspective that is applied based on a specific theoretical approach. Given the range of drop-out factors, stakeholders, and possible theoretical approaches within studies, this article aims at organising the research on the multi-facetted phenomenon for future endeavours by presenting a framework model that comprises a three-step recommendation: First, the model illustrates different phases (Development-, Decision-, Adjustment-Phase) of drop-out research that should be differentiated. Second, it is argued that the chosen sample perspective is highly relevant for drop-out research and must be chosen carefully. Third, the overarching disciplinary research perspectives on drop-out from VET, which scholars may adopt within their research, entail particular relevant variables and focal points and should therefore be discussed. Four examples of research perspectives (economical, psychological, sociological, pedagogical) are briefly presented, structured on a micro-, meso- and macro-level, to exemplify different theoretical accesses to drop-out research. Throughout the article, the novel organisation framework is explained and exemplified by illustrating relevant aspects of each research area and exemplary literature. The presented framework will help organising the research field and enable scholars to delimit their work more precisely, leading to a more traceable structure of further research efforts and more significant contributions to the state of knowledge.

Charting the Course of School Dropout Research: A Bibliometric Exploration

Charting the Course of School Dropout Research: A Bibliometric Exploration

Dropout prediction and decision feedback supported by multi temporal sequences of learning behavior in MOOCs

The temporal sequence of learning behavior is multidimensional and continuous in MOOCs. On the one hand, it supports personalized learning methods, achieves flexible time and space. On the other hand, it also makes MOOCs produce a large number of dropouts and incomplete learning behaviors. Dropout prediction and decision feedback have become an important issue of MOOCs. This study carries out sufficient method design and decision analysis on the dropout trend. Based on a large number of learning behavior instances, we construct a multi behavior type association framework, design dropout prediction model to analyze the temporal sequence of learning behavior, then discuss the corresponding intervention measures, in order to provide adaptive monitoring mechanism for long-term tracking and short-term learning method selection, and enable adaptive decision feedback. the full experiment shows that the designed model might improve the performance of the dropout prediction, which achieves the reliability and feasibility. The whole research can provide key technical solution and decision, which has important theoretical and practical value for dropout research of MOOCs.

Open Educational Resource-Enabled Pedagogy to Improve Student Outcomes in Nutrition Course

Online learning is a critical component of higher education. In 2017, the US Department of Education National Center for Education Statistics reported that one-third of all college and university students were enrolled in at least 1 online course. 1 Ginder SA Kelly-Reid JE Mann FB Enrollment and Employees in Postsecondary Institutions, Fall 2017; and Financial Statistics and Academic Libraries, Fiscal Year 2017: First Look (Provisional Data). NCES 2019-021rev. National Center for Education Statistics, US Department of Education, 2019https://nces.ed.gov/pubs2019/2019021REV.pdfDate accessed: February 19, 2021 Google Scholar In response to the coronavirus disease 2019 outbreak, online course delivery has flourished, 2 Adedoyin OB, Soykan E. Covid-19 pandemic and online learning: the challenges and opportunities [published online ahead of print September 2, 2020]. Interact Learn Environ.https://doi.org/10.1080/10494820.2020.1813180. Google Scholar but there are still unique challenges in online instruction: feelings of isolation, 3 Gillet-Swan J The challenges of online learning: supporting and engaging the isolated learner. J Learn Des. 2017; 10: 20-30 Google Scholar perceived lack of rigor/effectiveness, 1 Ginder SA Kelly-Reid JE Mann FB Enrollment and Employees in Postsecondary Institutions, Fall 2017; and Financial Statistics and Academic Libraries, Fiscal Year 2017: First Look (Provisional Data). NCES 2019-021rev. National Center for Education Statistics, US Department of Education, 2019https://nces.ed.gov/pubs2019/2019021REV.pdfDate accessed: February 19, 2021 Google Scholar lack of student engagement, 4 Stott P The perils of a lack of student engagement: reflections of a “lonely, brave, and rather exposed” online instructor. Br J Educ Technol. 2014; 47: 51-64 Crossref Scopus (14) Google Scholar greater student attrition, 5 Lee Y Choi J A review of online course dropout research: implications for practice and future research. Educ Technol Res Dev. 2011; 59: 593-618 Crossref Scopus (260) Google Scholar and participation barriers for under-represented students. 6 Baum S McPherson M The human factor: the promise & limits of online education. Daedalus. 2019; 149: 235-254 Crossref Google Scholar Although blended and flipped classroom formats offer promising approaches to overcome these obstacles, 7 Evans L Vanden Bosch ML Harrington S Schoofs N Coviak C Flipping the classroom in health care higher education: a systematic review. Nurse Educ. 2019; 44: 74-78 Crossref PubMed Scopus (20) Google Scholar , 8 Hew KF Lo CK Flipped classroom improves student learning in health professions education: a meta-analysis. BMC Med Educ. 2018; 18: 38 Crossref PubMed Scopus (202) Google Scholar , 9 Liu Q Peng W Zhang F Hu R Li Y Yan W The effectiveness of blended learning in health professions: systematic review and meta-analysis. J Med Internet Res. 2016; 18: e2 Crossref PubMed Scopus (207) Google Scholar courses that are taught entirely asynchronously online face many challenges.

Predicting Math Student Success in the Initial Phase of College With Sparse Information Using Approaches From Statistical Learning

In math teacher education, dropout research relies mostly on frameworks which carry out extensive variable collections leading to a lack of practical applicability. We investigate the completion of a first semester course as a dropout indicator and thereby provide not only good predictions, but also generate interpretable and practicable results together with easy-to-understand recommendations. As proof-of-concept, a sparse feature space together with machine learning methods is used for prediction of dropout, wherein the most predictive features have to be identified. Interpretability can be reached by introducing risk groups for the students. Implications for interventions are discussed.

Dropout in online higher education. A scoping review from 2014 to 2018

Online higher education continues to grow, yet its high dropout rates remain a pressing and complex problem. This article presents a scoping review of the recent literature on the theme, focusing on dropout definitions, concepts, and models, study domains and themes, methodological approaches, and findings. A search of relevant databases yielded 138 articles and dissertations. Findings reveal a complex yet disorganized field, lacking standard definitions and models. The bulk of current research is focused on risk factors; the most important ones were course and program factors (student support), student factors (motivation, time management skills, and satisfaction), and environmental factors (time- and financial-related issues). Future research should strive to achieve greater consistency in terminology, methods, and measurement, develop new intervention strategies and produce reliable effectiveness information. Further implications of these findings for future dropout research and the limitations of the study are discussed.

Dropout in online higher education: A scoping review from 2014 to 2018

Online higher education continues to grow, yet its high dropout rates remain a pressing and complex problem. This article presents a scoping review of the recent literature on the theme, focusing on dropout definitions, concepts, and models, study domains and themes, methodological approaches, and findings. A search of relevant databases yielded 138 articles and dissertations. Findings reveal a complex yet disorganized field, lacking standard definitions and models. The bulk of current research is focused on risk factors; the most important ones were course and program factors (student support), student factors (motivation, time management skills, and satisfaction), and environmental factors (time- and financial-related issues). Future research should strive to achieve greater consistency in terminology, methods, and measurement, develop new intervention strategies and produce reliable effectiveness information. Further implications of these findings for future dropout research and the limitations of the study are discussed.

The different patterns of the dropout according to the level and the field of education

Background and aims Our research is a part of a complex dropout research, whose main aim is to examine the time changes, social and regional inequalities, and constitutional differentiation of student dropout, appearing on a large scale and causing individual and institutional loss. As a part of this, the aim of our research on one hand is to identify the training fields and training levels with high dropout risk, furthermore to draw the patterns of dropout based on the available countrywide data. Methods We analyzed the database of the Hungarian Higher Education Informational System for our research, especially considering the students starting their training, based on final exam. We examined the most important features of advancements in studies, furthermore the occurring recoils. Considering our data, the measure of dropout remarkable differs based on the training fields and schedule, training, finances and some demographically background variable as well, taking the measure of dropout and its reasons into account. During our analysis, we separated three main types of the dropout’s reasons: financial reasons, study inefficiency, and dropout caused by other reasons. Results In this study, we examine these types and their characteristics in three different training levels: Bachelor degree programs, undivided, long-cycle Master courses, and short-cycle higher education vocational training. Discussion Almost one third of the students end up joining the group of dropout in all kind of training type, especially critical period is from the second to the fifth semester. The most endangered are males, correspondent students, fee-paying students, participants of higher education vocational training, furthermore the students of science and students of IT fields.

Rethinking Research on Prediction and Prevention of Psychotherapy Dropout: A Mechanism-Oriented Approach.

Dropout is a ubiquitous psychotherapy outcome in clinical practice and treatment research alike, yet it remains a poorly understood problem. Contemporary dropout research is dominated by models of prediction that lack a strong theoretical foundation, often drawing on data from clinical trials that report on dropout in an inconsistent and incomplete fashion. In this article, we assert that dropout is a critical treatment outcome that is worthy of investigation as a mechanistic process. After briefly describing the scope of the dropout problem, we discuss the many factors that limit the field's present understanding of dropout. We then articulate and illustrate a transdiagnostic conceptual framework for examining psychotherapy dropout in contemporary research, concluding with recommendations for future research. With a more comprehensive understanding of the factors affecting retention, research efforts can shift toward investigating key processes underlying treatment dropout, thus, boosting prediction and informing strategies to mitigate dropout in clinical practice.

Great Optically Luminous Dropout Research Using Subaru HSC (GOLDRUSH). I. UV luminosity functions at z ∼ 4–7 derived with the half-million dropouts on the 100 deg2 sky

Abstract We study the UV luminosity functions (LFs) at z ∼ 4, 5, 6, and 7 based on the deep large-area optical images taken by the Hyper Suprime-Cam (HSC) Subaru Strategic Program (SSP). On the 100 deg2 sky of the HSC SSP data available to date, we take enormous samples consisting of a total of 579565 dropout candidates at z ∼ 4–7 by the standard color selection technique, 358 out of which are spectroscopically confirmed by our follow-up spectroscopy and other studies. We obtain UV LFs at z ∼ 4–7 that span a very wide UV luminosity range of ∼0.002–100$\, L_{\rm UV}^\ast$ (−26 < MUV < −14 mag) by combining LFs from our program and the ultra-deep Hubble Space Telescope legacy surveys. We derive three parameters of the best-fit Schechter function, ϕ*, $M_{\rm UV}^{\,\ast}$, and α, of the UV LFs in the magnitude range where the active galactic nucleus (AGN) contribution is negligible, and find that α and ϕ* decrease from z ∼ 4 to 7 with no significant evolution of $M_{\rm UV}^{\,\ast}$. Because our HSC SSP data bridge the LFs of galaxies and AGNs with great statistical accuracy, we carefully investigate the bright end of the galaxy UV LFs that are estimated by the subtraction of the AGN contribution either aided by spectroscopy or the best-fit AGN UV LFs. We find that the bright end of the galaxy UV LFs cannot be explained by the Schechter function fits at >2 σ significance, and require either double power-law functions or modified Schechter functions that consider a magnification bias due to gravitational lensing.

Academic Fatalism: Applying Durkheim\u2019s Fatalistic Suicide Typology to Student Drop-Out and the Climate of Higher Education

Student drop-out remains a critical issue facing educational professionals. For higher education, the vast research in the past 40 years has been influenced by the work of Tinto and his model of student persistence. In this model are several elements that have proven to sharpen the focus of student drop-out research such as the concept of integration. The philosophical foundation for these concepts stems from Durkheim’s work on suicide. Specifically, Tinto’s employs Durkheim’s “egotistical” suicide type as an analogy for student departure while attributing students’ departure as a decision to separate themselves from the academic community. However; assigning causation of student departure to students’ decisions stands in stark contrast to the theoretical underpinnings of Durkheim’s work. Durkheim believed that certain social tendencies cause suicides. If student drop-out is to be typified by a certain Durkheimian suicide “type,” then specific social facts must exist in those societies. In this article, student departure in higher education will be examined using Durkheim’s theory of suicide complemented with Bourdieu’s theory of symbolic violence. Egotistical suicide will then be re-examined as an analogy for student departure and the Durkheimian suicide “fatalistic” will be presented as suitable analogy for student departure.

Dropping out and a crisis of trust

This article focuses on the high dropout rate in the Danish vocational education system. The article seeks to analyse the dropout problem using the concept of trust. By taking this perspective on the dropout problem, the article seeks to replace the hitherto-dominant deficit of understanding within the Danish dropout research, which has focused on the so-called crisis of motivation in which students are regarded as lacking sufficient motivation to complete a vocational education. It is asserted that the strong focus on students' lack of motivation contributes to individualizing and psychologizing the dropout problem. On the basis of the concept of trust forwarded by thinkers such as Luhmann, the article seeks to redefine the dropout problem as a problem of trust, thereby aiming to introduce a more comprehensive and relational understanding of student dropouts. The assertion that trust and distrust are key dimensions of the dropout problem is supported by results from an interview study in which 108 Danish school students were interviewed on completion and dropping out and in light of a tangible account of the shift from a motivational to a trust-based perspective. Three conditions are set forth as central themes relative to the student dropout process. These are (1) the primary school's lack of relevance for a group of students, (2) the numerous free riders in vocational education and (3) a lack of work placement spaces.

Predicting Psychotherapy Dropouts: A Multilevel Approach.

The role of therapeutic processes in predicting premature termination of psychotherapy has been a particular focus of recent research. The purpose of this study was to contrast outpatients who completed therapy and those who dropped out with respect to their self-reported in-session experiences of self-esteem, mastery, clarification and the therapeutic alliance. The 296 patients with mixed disorders were treated with an integrative form of cognitive-behavioural therapy without pre-determined time limit (M = 20.2 sessions). Multilevel analyses indicated that patients who did not completetreatment reported, on average, lower levels of self-esteem, mastery and clarification and lower ratings of their therapeutic alliance in treatment in contrast to patients who completed therapy. Patient-reported change in self-esteem experiences over the course of treatment turned out to be the strongest predictor of dropout from psychotherapy or successful completion. When dropout occurred before the average treatment length was reached, patients reported fewer clarifying experiences as early as the first session and their ratings of the therapeutic alliance were characterized by an absence of positive development. Both of these aspects seem to be involved in patients' decisions to leave treatment early. The findings underscore the importance of the therapeutic process in understanding the mechanisms behind treatment dropout. Analyses data from 296 patients at a private outpatient clinic in a routine practice setting (CBT). Completer/dropout definition: presence or absence of measurement battery at post-assessment. Focuses on change in therapy processes by investigating post-session reports. Finds that positive changes in self-esteem experiences is the most robust predictor of dropout, followed by ratings of clarification experiences and the global alliance. In line with recent dropout research, these process indicators might help to detect therapeutic situations that are connected with psychotherapy dropouts.

Understanding Why Students Drop Out of High School, According to Their Own Reports

Research on school dropout extends from early 20th-century pioneers until now, marking trends of causes and prevention. However, specific dropout causes reported by students from several nationally representative studies have never been examined together, which, if done, could lead to a better understanding of the dropout problem. Push, pull, and falling out factors provide a framework for understanding dropouts. Push factors include school-consequence on attendance or discipline. Pull factors include out-of-school enticements like jobs and family. Finally, falling out factors refer to disengagement in students not caused by school or outside pulling factors. Since 1966, most nationally representative studies depicted pull factors as ranking the highest. Also, administrators in one study corroborated pull out factors for younger dropouts, not older ones, while most recent research cites push factors as highest overall. One rationale for this change is a response to rising standards from No Child Left Behind (NCLB), which can be ultimately tested only by future dropout research.

Dropout in secondary education: an application of a multilevel discrete-time hazard model accounting for school changes

For several decades, researchers have focused on dropout in search for an explanation and prevention of this phenomenon. However, past research is characterized by methodological shortcomings. Most of this research was conducted without considering the hierarchical structure of educational data and ignored the longitudinal path towards dropout. Moreover, research that did take into account these shortcomings, did not correct for student mobility between schools, despite the strong correlation with dropout (South et al. 2007). In this study, we attempt to address these shortcoming by implementing a multilevel discrete-time hazard model and exploring the effect of different school classifications on the school effects. Partially analogous to Grady and Beretvas (2010) we compare models with estimated school effects based on the first and on the last school attended and compare these models with multiple membership models and cross-classified models. The results of this comparison indicate that ignoring student mobility can have strong implications on the predictors of dropout. Not only do models which take into account this mobility yield better model fits, models ignoring this mobility tend to miss the effect of school level variables. With respect to the conclusions on dropout research, our models provide evidence for the often cited student characteristics predicting dropout and indicate stronger school effects than generally assumed.

A review of online course dropout research: implications for practice and future research

Although online learning is expanding in availability and popularity, the high dropout rates remain a challenging problem. In this paper, we reviewed the existing empirical studies on online course dropouts in post-secondary education that were published during the last 10 years. We identified 69 factors that influence students’ decisions to dropout and classified them into three main categories: (a) Student factors, (b) Course/Program factors, and (c) Environmental factors. We then examined the strategies proposed to overcome these dropout factors: (a) understanding each student’s challenges and potential, (b) providing quality course activities and well-structured supports, and (c) handling environmental issues and emotional challenges. Finally, we discussed issues regarding dropout factors and strategies for addressing these factors and offered recommendations for future research.

Predictors of Early Termination in a University Counseling Training Clinic

Despite the existence of counseling dropout research, there are limited predictive data for counseling in training clinics. Potential predictor variables were investigated in this archival study of 380 client files in a university counseling training clinic. Multinomial logistic regression, predictive discriminant analysis, and classification and regression trees converged on the use of a 4‐predictor model (client age, income, perceived difficulty, and functional impairment) for classifying counseling dropouts. Implications for research and practice are discussed.

Dropout-Prevention Programs

The factors that contribute to student dropouts have been the focus of extensive deliberation during the last decade. Despite expanded attention, the number of dropouts remains unacceptably high. Drawing on the authors’ 17-year history of dropout research in Texas, Arizona, and across the country, this article describes the alarming dropout rates, especially among Hispanic students; assesses efforts that have been undertaken to address the dropout issue, including proven dropout prevention programs; and provides a new paradigm for preventing dropouts.

Winning the battle and losing the war: Examining the relation between grade retention and dropping out of high school

AbstractThe aim of this investigation is to provide a comprehensive review of dropout research that examines grade retention within both associative and predictive models. A systematic review of seventeen studies examining dropping out of high school prior to graduation demonstrates that grade retention is one of the most powerful predictors of dropout status. The discussion addresses the discrepancies among the perspectives of many educational professionals regarding the effectiveness of grade retention and deleterious long‐term correlates. The transactional model of development is presented, which emphasizes developmental trajectories over time, in order to facilitate the interpretation of the association between grade retention and school withdrawal. Educational professionals, teachers, researchers, parents, and policymakers considering the efficacy of grade retention are encouraged to consider the implications of these findings. © 2002 Wiley Periodicals, Inc.