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1
Wolman, Clara, Robert Bruininks, and Martha L. Thurlow. "Dropouts and Dropout Programs." Remedial and Special Education 10, no. 5 (September 1989): 6–20. http://dx.doi.org/10.1177/074193258901000504.
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Burton, Damon, and Rainer Martens. "Pinned by Their Own Goals: An Exploratory Investigation into Why Kids Drop out of Wrestling." Journal of Sport Psychology 8, no. 3 (September 1986): 183–97. http://dx.doi.org/10.1123/jsp.8.3.183.
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Previous research concludes that athletes drop out of sport because of conflicts of interest, but these findings cannot clarify whether dropouts find other activities more appealing or turn to new activities because sport fails to meet their achievement needs. This investigation assessed dropout motives by testing explanations derived from Nicholls' (1984) motivational model and comparing them with traditional dropout questionnaire responses. Wrestling coaches, participants, participants' parents, dropouts, and dropouts' parents completed a 23-item dropout inventory; and participants and dropouts responded to questionnaire items testing Nicholls' task choice predictions. Dropout inventory responses confirmed previous conflict-of-interest findings. In data testing Nicholls' model, participants demonstrated significantly higher perceived ability, better won-loss records, more functional attributions, and more positive expectancies, and valued wrestling success more than dropouts did. These findings supported predictions that wrestlers change activities when continued participation threatens their perceived ability. Disagreement between the conclusions concerning why young athletes drop out of wrestling drawn from the conflict-of-interest explanation and from Nicholls' perceived ability model are discussed, and suggestions for reducing dropout rates are offered.
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Löbig, Anna, Peter Ehnold, and Torsten Schlesinger. "„Da hatte ich einfach kein Interesse mehr daran.“ Analyse der Verläufe von Vereinsmitgliedschaftskarrieren jugendlicher Fußballer unter besonderer Berücksichtigung des Dropouts." Sport und Gesellschaft 17, no. 1 (April 28, 2020): 35–68. http://dx.doi.org/10.1515/sug-2020-0003.
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ZusammenfassungAusgehend von erhöhten Dropout-Quoten, welche mit negativen Konsequenzen für Verbände, Vereine oder Mitglieder einhergehen können, steht die Analyse typischer Vereinskarrieren jugendlicher Fußballer unter besonderer Berücksichtigung des Dropouts im Fokus des Beitrags. Ergänzend zu bisherigen, meist querschnittlich angelegten Studien wird dabei eine lebenslaufbezogene Perspektive eingenommen. Jugendliche Fußballer (n=15) aus verschiedenen Vereinen (n=4) wurden mit Hilfe des biografischen Mappings befragt. Dabei zeigen sich typische Verläufe in Abhängigkeit von der subjektiven Relevanz des Vereinswechsels (Vereins-Dropout) sowie des Fußball-Dropouts: „Vereins-Dropouts mit stabiler Fußballmitgliedschaft“ (Typ 1), „Plötzliche Fußball-Dropouts mit oder ohne vorherige Vereinswechsel“ (Typ 2), „Temporäre Fußball-Dropouts mit anschließendem Vereinswechsel“ (Typ 3) und „Instabile Fußballmitgliedschaftskarrieren“ (Typ 4). Diese Verlaufstypologien erweitern die bis-herige Befundlage um eine prozessuale/verlaufsbezogene Perspektive und eröffnen dadurch alternative Steuerungsoptionen im Umgang mit Dropouts.
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Andrea King-Dominguez, Andrea, Luis Amestica-Rivas, Victor Ramirez Gonzalez, and Francisco Ganga Contreras. "Student dropout, the economic cost for Chilean universities." Universidad Ciencia y Tecnología 27, no. 118 (February 27, 2023): 17–28. http://dx.doi.org/10.47460/uct.v27i118.683.
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Student dropout continues to be a significant challenge in higher education. Studies have shown that it has economic impacts on institutions. However, the cost associated with student dropout needs to be better understood. This research focuses on first-year dropouts in 51 Chilean universities, intending to analyze the costs generated by student dropouts in all their careers, allowing to project in an average horizon the resources that would no longer be received as a result of dropouts. It is descriptive research with a documentary analysis technique. Among the most outstanding results, it is shown that the institutions would lose around USD 1,169,853,410 and that private universities are the ones that register a higher cost associated with first-year university dropouts. On the other hand, it is statistically proven that for those universities that register a higher number of enrollments, the cost associated with dropout will be higher.
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Putri, Mailian, Jasmienti Jasmienti, Iswantir Iswantir, and Fauzan Fauzan. "Faktor-Faktor Yang Mempengaruhi Akhlak Anak Putus Sekolah di Jorong Balai Cubadak Nagari Taram Kecamatan Harau Kabupaten Lima Puluh Kota." Indonesian Research Journal On Education 3, no. 2 (March 8, 2023): 935–46. http://dx.doi.org/10.31004/irje.v3i2.7.
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This research is motivated by the morals of school dropouts in various forms. The morals of these school dropouts are commendable and some have despicable characters, not all school dropouts have despicable morals, but there are also commendable ones. Out-of-school children certainly do not get a full education so dropouts have despicable morals such as: being dishonest, likes to lie, talk rudely, and are also easily influenced by the outside environment which makes dropout children like to steal otherpeople's things. The purpose of this study was to determine the factors that influence the morals of school dropouts in Jorong Balai Cubadak Nagari Taram, Harau District, Lima Puluh Kota Regency so that the morals of dropouts have noble character. This type of research is descriptive qualitative research. In collecting data, the writer uses observation, interview, and documentation techniques. Meanwhile, to analyze it, the researcher took several steps, namely data reduction, presenting data, and drawingconclusions. Based on the results of the research that has been carried out, it can be concluded that the factors that influence the morals of school dropouts in Jorong Balai Cubadak are instinct, innate or inherited, environment, habits, will, and education. A bad environment will affect the morals of school dropouts to behave despicably and if the innate or inherited parents have good morals, the morals of dropout children will have noble character.
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Blais, Régis. "Assessing Patient Satisfaction with Health Care: Did You Drop Somebody?" Canadian Journal of Program Evaluation 5, no. 2 (September 1990): 1–13. http://dx.doi.org/10.3138/cjpe.5.001.
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Abstract: This study has three objectives: (a) to compare socio-demographic characteristics of dropouts and completers of a health promotion program, (b) to assess each group's satisfaction with specific aspects of the program, and (c) to investigate the reasons for dropout. Data were collected by means of individual structured interviews with 19 dropouts and 20 completers randomly selected. Results show that the two groups do not differ on socio-demographic variables. Completers were significantly more satisfied than dropouts with only a few aspects of care. Investigating dropouts' motives added key information. We conclude that useful measurement of patient satisfaction should focus on specific aspects of care and on survey dropouts as well as completers, and should assess dropouts' motives.
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Janosz, Michel, Marc LeBlanc, and Bernard Boulerice. "Consommation de psychotropes et délinquance : de bons prédicteurs de l’abandon scolaire ?" Criminologie 31, no. 1 (September 1, 2005): 87–107. http://dx.doi.org/10.7202/017413ar.
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Although empirical links between deviant behavior and school dropout have been extensively demonstrated, the specific influence of drug use and delinquency on school dropout is still not clear and varies across studies. One reason for this lack of consistency may rests upon the way samples of dropouts have been analysed. Recently, Janosz, Le Blanc, Boulerice and Tremblay (1996) constructed and validated a typology of school dropout highlithing the social and psychological diversity of this population. Using a longitudinal sample of adolescents (N=791), we analyzed the predictive relationships of family rebelliousness, drug use and delinquency on school dropout. The results showed an important variability in the predictive relationships according to the type of dropouts. The necessity of considering the psychosocial heterogeneity of dropouts when conducting such studies is discussed.
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Kim, Sangyun, Euteum Choi, Yong-Kee Jun, and Seongjin Lee. "Student Dropout Prediction for University with High Precision and Recall." Applied Sciences 13, no. 10 (May 20, 2023): 6275. http://dx.doi.org/10.3390/app13106275.
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Since a high dropout rate for university students is a significant risk to local communities and countries, a dropout prediction model using machine learning is an active research domain to prevent students from dropping out. However, it is challenging to fulfill the needs of consulting institutes and the office of academic affairs. To the consulting institute, the accuracy in the prediction is of the utmost importance; to the offices of academic affairs and other offices, the reason for dropping out is essential. This paper proposes a Student Dropout Prediction (SDP) system, a hybrid model to predict the students who are about to drop out of the university. The model tries to increase the dropout precision and the dropout recall rate in predicting the dropouts. We then analyzed the reason for dropping out by compressing the feature set with PCA and applying K-means clustering to the compressed feature set. The SDP system showed a precision value of 0.963, which is 0.093 higher than the highest-precision model of the existing works. The dropout recall and F1 scores, 0.766 and 0.808, respectively, were also better than those of gradient boosting by 0.117 and 0.011, making them the highest among the existing works; Then, we classified the reasons for dropping out into four categories: “Employed”, “Did Not Register”, “Personal Issue”, and “Admitted to Other University.” The dropout precision of “Admitted to Other University” was the highest, at 0.672. In post-verification, the SDP system increased counseling efficiency by accurately predicting dropouts with high dropout precision in the “High-Risk” group while including more dropouts in total dropouts. In addition, by predicting the reasons for dropouts and presenting guidelines to each department, the students could receive personalized counseling.
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Hammack, Floyd Morgan. "Large School Systems' Dropout Reports: An Analysis of Definitions, Procedures, and Findings." Teachers College Record: The Voice of Scholarship in Education 87, no. 3 (March 1986): 324–41. http://dx.doi.org/10.1177/016146818608700303.
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One basic problem for both researchers and policymakers is obtaining accurate information about dropouts. In this article, Floyd Hammack examines school district reports on the dropout problem in Boston, Los Angeles, Miami, New York City, San Diego, and Chicago. Citing the great diversity in the processes for the classification of students as dropouts, he raises important concerns about the comparability of dropout rates between districts.
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Wayman, Jeffrey C. "Factors Influencing Dropouts' GED & Diploma Attainment." education policy analysis archives 9 (February 8, 2001): 4. http://dx.doi.org/10.14507/epaa.v9n4.2001.
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This study examined correlates of degree attainment in high school dropouts. Participants were high school dropouts of Mexican American or non-Latino white descent who had no degree, a high school degree, or a GED certificate. This study was unique in that it accounted for sample bias of missing data through the use of multiple imputation, it considered students who had dropped out as early as 7th grade, and it was able to include variables found significant in previous research on returning dropouts. Logistic regression analyses identified a parsimonious set of factors which distinguished dropouts who held degrees (diploma or GED) from those who did not. Similar analyses were performed to distinguish participants who had attained diplomas from those who had attained GEDs. It was estimated that 59.2% of dropouts return to obtain high school credentials. School capability, age at dropout, and socio-economic status significantly predicted degree attainment. Presence of children, higher school capability and socio-economic status were associated with GED attainment, while later grade at dropout was associated with diploma attainment. These relationships did not vary by ethnicity, although degree attainment was less likely for Mexican American dropouts. The study concludes that dropping out is not the end of a student's education, and more research should be directed toward returning dropouts. Further, the focus of such research should be expanded to include a more positive and broader range of correlates.
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Song, Zihan, Sang-Ha Sung, Do-Myung Park, and Byung-Kwon Park. "All-Year Dropout Prediction Modeling and Analysis for University Students." Applied Sciences 13, no. 2 (January 14, 2023): 1143. http://dx.doi.org/10.3390/app13021143.
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The core of dropout prediction lies in the selection of predictive models and feature tables. Machine learning models have been shown to predict student dropouts accurately. Because students may drop out of school in any semester, the student history data recorded in the academic management system would have a different length. The different length of student history data poses a challenge for generating feature tables. Most current studies predict student dropouts in the first academic year and therefore avoid discussing this issue. The central assumption of these studies is that more than 50% of dropouts will leave school in the first academic year. However, in our study, we found the distribution of dropouts is evenly distributed in all academic years based on the dataset from a Korean university. This result suggests that Korean students’ data characteristics included in our dataset may differ from those of other developed countries. More specifically, the result that dropouts are evenly distributed throughout the academic years indicates the importance of a dropout prediction for the students in any academic year. Based on this, we explore the universal feature tables applicable to dropout prediction for university students in any academic year. We design several feature tables and compare the performance of six machine learning models on these feature tables. We find that the mean value-based feature table exhibits better generalization, and the model based on the gradient boosting technique performs better than other models. This result reveals the importance of students’ historical information in predicting dropout.
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Augustine, L. Maningba, and M. Jeyaseelan. "Aftermath of School Dropout: Sociological Analysis with Reference to Maram Naga Tribe, Manipur." Shanlax International Journal of Arts, Science and Humanities 10, no. 3 (January 1, 2023): 75–82. http://dx.doi.org/10.34293/sijash.v10i3.5883.
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School dropout is a serious problem faced by individual and society for which focus has been a great concern for the policymakers and researchers to deal with. The present study was to examine the consequences of school dropouts in the Maram Naga Tribe, Manipur. School dropout is not a new phenomenon but the current study will contribute to the awareness of the effects and suggest the remedies in order to curb the problems. The aims of the study were to explore the research questions such as what problems do dropouts encounter after leaving school. The researcher followed simple random sampling methodto select 260 respondents from the universe. The interview method has been used to collect data to understand the phenomena of the consequences of school dropouts. The key findings are unemployment, regret, family chaos and taking intoxicate like alcoholism, drug addiction and so on. The significance of the findings shows that dropouts have different experiences in economic, social and political outcomes in society.
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Yufrinalis, Marianus, and Stefanus Igolois Grenga Uran. "Social Attitudes, Environmental Factors, and Laws-Institutions Impacts on School Dropouts: Case Studies in Sumba Island." Utamax : Journal of Ultimate Research and Trends in Education 5, no. 1 (March 17, 2023): 45–61. http://dx.doi.org/10.31849/utamax.v5i1.11818.
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This research is based on the fact that most children in West Sumba and Central Sumba are forced to drop out of school for various very crucial reasons. The purpose of this study refers to efforts to identify various factors that influence the high dropout rate. The collected data shows that the number of primary school dropouts in West Sumba was 151 students (0.76%) from 18,772 primary school students in the regency. The highest number was in the Lamboya and Tanarighu districts, making up 2.02% and 1.06%, respectively. The percentage is even lower for secondary school dropouts, which is 0.006% of the total of 13,368 junior high school students in West Sumba. The percentage of school dropouts at the primary schools in the Central Sumba Regency is 0.72%. From the collected data, the highest dropout rates are in the districts of Mamboro (1.28%). The percentage of secondary school dropouts in Central Sumba is 2.14%. The highest numbers were in the districts of Umbu Ratu Nggay Barat (3.61%), Katikutana Selatan (2.42%), Katikutana (2.04%), Mamboro (1.70%), and Umbu Ratu Nggay (1.21%). From the information above, the highest dropout rates for primary and secondary schools are in Umbu Ratu Nggay Barat and Katikutana Selatan districts. The main factors causing the high dropout rate in these two districts are Social Attitudes, Environmental Factors, and Laws and Institutions
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Buzulukova, Natalia, Jerry Goldstein, Mei-Ching Fok, Alex Glocer, Phil Valek, David McComas, Haje Korth, and Brian Anderson. "Magnetosphere dynamics during the 14 November 2012 storm inferred from TWINS, AMPERE, Van Allen Probes, and BATS-R-US–CRCM." Annales Geophysicae 36, no. 1 (January 25, 2018): 107–24. http://dx.doi.org/10.5194/angeo-36-107-2018.
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Abstract. During the 14 November 2012 geomagnetic storm, the Van Allen Probes spacecraft observed a number of sharp decreases (“dropouts”) in particle fluxes for ions and electrons of different energies. In this paper, we investigate the global magnetosphere dynamics and magnetosphere–ionosphere (M–I) coupling during the dropout events using multipoint measurements by Van Allen Probes, TWINS, and AMPERE together with the output of the two-way coupled global BATS-R-US–CRCM model. We find different behavior for two pairs of dropouts. For one pair, the same pattern was repeated: (1) weak nightside Region 1 and 2 Birkeland currents before and during the dropout; (2) intensification of Region 2 currents after the dropout; and (3) a particle injection detected by TWINS after the dropout. The model predicted similar behavior of Birkeland currents. TWINS low-altitude emissions demonstrated high variability during these intervals, indicating high geomagnetic activity in the near-Earth tail region. For the second pair of dropouts, the structure of both Birkeland currents and ENA emissions was relatively stable. The model also showed quasi-stationary behavior of Birkeland currents and simulated ENA emissions with gradual ring current buildup. We confirm that the first pair of dropouts was caused by large-scale motions of the OCB (open–closed boundary) during substorm activity. We show the new result that this OCB motion was associated with global changes in Birkeland (M–I coupling) currents and strong modulation of low-altitude ion precipitation. The second pair of dropouts is the result of smaller OCB disturbances not related to magnetospheric substorms. The local observations of the first pair of dropouts result from a global magnetospheric reconfiguration, which is manifested by ion injections and enhanced ion precipitation detected by TWINS and changes in the structure of Birkeland currents detected by AMPERE. This study demonstrates that multipoint measurements along with the global model results enable the reconstruction of a more complete system-level picture of the dropout events and provides insight into M–I coupling aspects that have not previously been investigated. Keywords. Magnetospheric physics (magnetosphere–ionosphere interactions; magnetospheric configuration and dynamics); space plasma physics (numerical simulation studies)
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Kyei, Kwabena A. "Dropout in High Schools students–Modeling a Case Study in the Vhembe District, Limpopo Province, South Africa." Journal of Education and Vocational Research 5, no. 2 (June 30, 2014): 65–72. http://dx.doi.org/10.22610/jevr.v5i2.154.
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South Africa experiences a significant amount of dropouts of high school learners every year. Only about 45% of learners who start primary school in a given year write matriculation examinations after 10 years of schooling. A high dropout rate deprives the country of well-informed and competent future leaders. This study looks at the factors that underlie dropout in high schools in the Vhembe district. A random sample of 5 villages was selected from 25 villages which have high schools. A census of high school dropouts in these 5 villages was conducted. About 660 dropouts were obtained and interviewed. Applying regression modeling, this study shows that poor performance, attitude, punishment and pregnancy are the factors affecting dropout in Vhembe, and recommends that educators encourage learners to develop positive attitude to school work and also give extra assistance to under-performing learners, and sex education be given with seriousness to reduce unwanted pregnancies.
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Lam, Wing-Shun, Parvez N. Guzdar, and Rajarshi Roy. "Effect of Spontaneous Emission Noise and Modulation on Semiconductor Lasers Near Threshold with Optical Feedback." International Journal of Modern Physics B 17, no. 22n24 (September 30, 2003): 4123–38. http://dx.doi.org/10.1142/s021797920302209x.
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The dynamical behavior of power dropouts in a semiconductor laser with optical feedback, pumped near threshold current, is strongly influenced by quantum noise. This is clearly demonstrated by experiments with modulations on the pumping current or the feedback strength. For the cases without modulation and with only current modulation, the dropouts occur randomly. However the feedback strength modulation locks the dropout events periodically. By numerically modeling these three cases using the Lang–Kobayashi equations with a stochastic term to take into account spontaneous emission noise, it is shown that the observed behavior of the dropouts can be readily reproduced for all three cases. Noise plays a signifcant role in explaining the observed dropout events. A simple explanation of the observed dropout phenomenon is presented, based on the adiabatic motion of the ellipse formed by the steady state solutions of the rate equations due to slow time modulations of the injection current or the feedback strength.
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Huang, Li-xun, and Yong Fang. "Convergence Analysis of Wireless Remote Iterative Learning Control Systems with Dropout Compensation." Mathematical Problems in Engineering 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/609284.
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The wireless remote iterative learning control (ILC) system with random data dropouts is considered. The data dropout is viewed as a binary switching sequence which obeys the Bernoulli distribution. In order to eliminate the effect of data dropouts on the convergence property of output error, the signal at the same time with the lost one but in the last iteration is used to compensate the data dropout at the actuator. With the dropout compensation, the convergence property of output error is analyzed by studying the element values of system transition matrix. Finally, some simulation results are given to illustrate the validity of the proposed method.
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Parreño, Samuel John. "School dropouts in the Philippines: causes, changes and statistics." Sapienza: International Journal of Interdisciplinary Studies 4, no. 1 (January 17, 2022): e23002. http://dx.doi.org/10.51798/sijis.v4i1.552.
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School dropout is a major problem as it has negative impacts that result in high social costs. A learner can be called a dropout when the learner fails to enroll in school despite having reached the mandatory school age. This paper aims to identify the root causes of school dropouts in the Philippines, specifically in all regions for the years 2008 and 2013. The secondary data on the proportion of population 6 to 24 years old who are not attending school from the website of the Philippine Statistics Authority were used. The data were analyzed using R version 4.2.1. This paper employed descriptive statistics, namely frequency and percentage to identify the root causes of dropping out in the Philippines when grouped according to region and year. Percentage change (increase and decrease) were explored to track changes in the causes of school dropouts. The findings indicated that the high cost of education, and student employment or when the student is seeking employment were the root causes of dropouts in the Philippines for the years 2008 and 2013, respectively. Based on the findings, it is recommended that the Philippine government, through the Department of Education, should prioritize programs that will address the root causes of the school dropouts with the goal of decreasing the dropout rate in general.
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Svec, Henry. "Overestimation of Academic Competence by High School Dropouts." Psychological Reports 59, no. 2 (October 1986): 669–70. http://dx.doi.org/10.2466/pr0.1986.59.2.669.
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To estimate the frequency of academic overestimation by high school dropouts, the achievement and self-concept scores of 40 normal, and 40 dropout male adolescents, were evaluated. For this sample dropouts were not over-represented in the high self-concept, low-achievement group. This suggests that students may not leave school to “save face” and that other factors may contribute to this phenomenon.
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Qi, Jing, Yang Zhou, Zicen Zhao, and Shuilin Jin. "SDImpute: A statistical block imputation method based on cell-level and gene-level information for dropouts in single-cell RNA-seq data." PLOS Computational Biology 17, no. 6 (June 17, 2021): e1009118. http://dx.doi.org/10.1371/journal.pcbi.1009118.
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The single-cell RNA sequencing (scRNA-seq) technologies obtain gene expression at single-cell resolution and provide a tool for exploring cell heterogeneity and cell types. As the low amount of extracted mRNA copies per cell, scRNA-seq data exhibit a large number of dropouts, which hinders the downstream analysis of the scRNA-seq data. We propose a statistical method, SDImpute (Single-cell RNA-seq Dropout Imputation), to implement block imputation for dropout events in scRNA-seq data. SDImpute automatically identifies the dropout events based on the gene expression levels and the variations of gene expression across similar cells and similar genes, and it implements block imputation for dropouts by utilizing gene expression unaffected by dropouts from similar cells. In the experiments, the results of the simulated datasets and real datasets suggest that SDImpute is an effective tool to recover the data and preserve the heterogeneity of gene expression across cells. Compared with the state-of-the-art imputation methods, SDImpute improves the accuracy of the downstream analysis including clustering, visualization, and differential expression analysis.
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Kim, Mi Kyoung. "Perceived Carrer Barriers and Suicidal Ideation among Adolescent School Dropouts." Research Institute for Life and Culture Sogang University 64, no. 1 (May 31, 2022): 187–206. http://dx.doi.org/10.17924/solc.2022.64.187.
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This study aimed to identify the temporal changes in perceived career barriers and suicidal ideation and examine the impact of career barriers on suicidal ideation to establish practical guidelines for career development and psychological support required for adolescents’ development following their academic dropout. We used the data of 250 adolescents, who participated in the Adolescent School Dropouts Panel Survey, between 2014 and 2017. Data were analyzed using SPSS 25.0 and Amos 23.0 for computing descriptive statistics and a potential growth model for career barriers and suicidal ideation, respectively, among adolescent school dropouts. The analysis demonstrated a change in adolescent school dropouts’ perceptions of career barriers and suicidal ideation. Furthermore, adolescent school dropouts’ career barriers had a significant effect on suicidal ideation. These findings emphasize the need for an integrated approach to implement career support interventions for exploration and experience, alongside preventive measures to reduce the risk of suicide among adolescent school dropouts. Thus, the current study results prompt a discussion on the need to establish a social support system for adolescent school dropouts and their healthy integration into the society and provide future research recommendations.
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Patzina, Alexander, and Gabriele Wydra-Somaggio. "Early Careers of Dropouts from Vocational Training: Signals, Human Capital Formation, and Training Firms." European Sociological Review 36, no. 5 (June 25, 2020): 741–59. http://dx.doi.org/10.1093/esr/jcaa011.
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Abstract Dropping out of post-secondary education has negative consequences for career progression. However, as human capital theory predicts and as previous studies have shown, having some training still pays off. For a large part of the European workforce who has attended vocational training, however, the theoretical predictions are less clear and empirical studies are scarce. In occupational labour markets, signalling and credentialism theories predict negative effects of dropping out. Furthermore, apprenticeship dropouts learn at different training firms, which differ in their influence on human capital development and the provision of job opportunities. Relying on a unique panel data set from Germany and estimating normalized fixed effects growth curve estimators, our study reveals the following results. First, the timing of dropping out structures career progression, as late dropouts have the highest employment rates and highest wages within the dropout population. However, in an occupational labour market setting, credentials and signals are still highly important for career progression, as the wage advantage of late dropouts within the dropout population is rather small, and late dropouts suffer a wage penalty when we compare their wage profiles to those of graduates. Second, our study emphasizes the importance of training firms, which influence the human capital development of individuals during the course of training and provide dropouts with connections to their first jobs. Thus, in occupational labour markets, the consequences of dropping out depend mainly on different mechanisms, as in other settings.
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Rõõm, Marili, Marina Lepp, and Piret Luik. "Dropout Time and Learners’ Performance in Computer Programming MOOCs." Education Sciences 11, no. 10 (October 14, 2021): 643. http://dx.doi.org/10.3390/educsci11100643.
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One of the problems regarding MOOCs (Massive Open Online Courses) is the high dropout rate. Although dropout periods have been studied, there is still a lack of understanding of how dropout differs for MOOCs with different levels of difficulty. A quantitative study was conducted to determine the periods with the highest dropouts in computer programming MOOCs and the performance of the dropouts on the course before dropping out. Four occurrences of three MOOCs, with different durations, difficulty of the topic, and the degree of supportive methods, were included. The results showed that dropout was highest at the beginning of all studied courses. Learners also dropped out before the project. In the easier and shorter courses, most dropouts were successful until they quit the course. In longer and more difficult courses, learners mainly dropped out in the week they started due to experiencing problems with the course activities. It is suggested to recommend that learners take courses at a level that suits them if their current course is too easy or difficult and encourage learners to use course resources for help. It would be a good idea to provide learners with example topics to assist them in starting with a project.
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Neupane, Binod. "Causes of Dropout in Higher Education: An Analysis of Student Dropouts in Bachelor of Education from Marsyangdi Multiple Campus." Marsyangdi Journal 4, no. 1 (July 16, 2024): 1–14. http://dx.doi.org/10.3126/mj.v4i1.67750.
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Student dropout in higher education institutions (HEIs) is a serious problem in many developed and developing countries including Nepal. According to the University Grants Commission (UGC) report, many campuses are at risk and have a few number of students due to the high dropout rate. This paper aims to analyse student dropout in B.Ed. programme at Marsyangdi Multiple Campus (MMC) and explores the main causes of high dropouts with some measuring strategies to mitigate the problem. Following a quantitative survey through telephone interviews with 30 dropout students, I collected information and analysed it thematically in a narrative way. The findings of the study revealed that 65.47% of students left the campus before completing their degree. The study explored the major causes of high dropouts related to four indicators such as student, institutional, family, and community. Most of the students left their studies due to financial constraints, socioeconomic factors, institutional insufficiency, employment opportunities, study abroad, and early marriage and early pregnancy. The findings of the study apply to reducing the increasing number of dropouts from the university and other similar campuses. In addition to this, it implies formulating higher education policy and reforming the HEIs as per the demands of the time.
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Mohammad Faisal, Nurfarah Najwa, Puteri Rohani Megat Abdul Rahim, Nor Faizah Kaeni Mokh Hatta, and Addiennur Hamizah Abu Bakar. "Understanding School Dropouts Phenomenon among Youths through Behavioural Trends." Environment-Behaviour Proceedings Journal 8, no. 23 (March 23, 2023): 3–11. http://dx.doi.org/10.21834/ebpj.v8i23.4474.
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Dropout among school students is seen as problematic and needs to be addressed, to protect the growth of the nation, particularly in the economic aspect. This phenomenon can be addressed by understanding the behavioural trends of school dropouts. This study aims to explore behavioural dropout trends through a systematic literature review. The process entails five primary methodological steps which were systematic searching strategies based on identification, screening, and eligibility on several reputable databases, data extraction, and analysis. The findings showed a considerable number of behavioural trends could be used as an early signal by the school to address dropout issues. Keywords: Dropouts; Youths; School Dropouts; Behavioural Trends eISSN: 2398-4287 © 2023. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians/Africans/Arabians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia. DOI: https://doi.org/10.21834/ebpj.v8i23.4474
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Zhang, Hua Jing, Xue Feng Zhang, and Yan Xia Shen. "H∞ Filtering for a Class of Networked Control Systems with Packet Dropouts." Applied Mechanics and Materials 321-324 (June 2013): 2326–30. http://dx.doi.org/10.4028/www.scientific.net/amm.321-324.2326.
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The problem of H∞ filtering for networked control system with packet dropouts is discussed. By analyzing packet dropout dynamics and presenting a switching filter, the new filtering error system corresponding to the dynamic information of the packet dropouts is structured. A sufficient condition in terms of LMIs for the system to be stable with a prescribed H performance is obtained. The result is less conservative. A numerical example illustrates the effectiveness of the presented method.
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Wilcox, Ralph C. "Dropouts." Journal of Physical Education, Recreation & Dance 58, no. 6 (August 1987): 21–25. http://dx.doi.org/10.1080/07303084.1987.10609564.
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Roy, Ram Rekha, and Bishnu Prasad Sharma. "Economic Cost of Absentee and Dropout Students in Public Schools of Nepal." Economic Journal of Nepal 42, no. 3-4 (December 31, 2019): 1–11. http://dx.doi.org/10.3126/ejon.v42i3-4.36029.
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High absenteeism and dropout rates in school are considered one of the major stumbling blocks in achieving educational goals in developing countries. Absentees and dropouts impose a large resource cost on the educational system and the society. The study examines the economic cost of absentee and dropout students in public schools of Nepal. Using data from public schools in a rural municipality in Nepal, the study estimates the unit cost of absentee and dropout students by level. Cost of human resource, stationery, utility and fixed costs of building and furniture were the components for estimating unit costs. The findings reveal that the unit cost of students was equivalent to U.S. $295, 130 and 143 for primary, lower-secondary, and secondary levels respectively, and an average of U.S. $189 overall. The resource loss due to dropout was around 28, 12, and 11 percent of the total resource spent for primary, lower secondary and secondary levels respectively with an average of around 16 percent. The combined resource loss from dropouts and absentees were found to be 39, 23 and 20 percent for the different levels. On average, 26 percent of the public-school resource was lost due to dropouts and absentees. The main causes of dropout and absenteeism were the lack of interest, motivation of parents and the children to attend the school. The study suggests the need for more comprehensive and in depth study for effective policy formulation to address this problem.
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Khan, Aiyaz Ahmad, and Abdul Samad. "A Study of Factors Affecting Boys’ Dropout." RESEARCH REVIEW International Journal of Multidisciplinary 7, no. 8 (August 17, 2022): 27–35. http://dx.doi.org/10.31305/rrijm.2022.v07.i08.005.
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School dropout is a major hindrance in attaining the goals of education in India. From time to time several policy pronouncements have been made, but it’s not yielding the desired outcome. Over a decade, the dropout rates for both boys and girls are reflecting a decreasing trend. Several reports reveal that more boys are now dropping out of schools, mainly at the primary level. As per a Unified District Information System for Education Plus (UDISE+) report, the rate of dropout for boys in primary classes was 1.7 percent and that of girls was 1.2 percent. Similarly, the rate of dropout for boys in secondary classes was 18.3 percent which is higher than that of girls with 16.3 percent (TOI, Jul 2, 2021). In this context, attempts have been made to study the patterns of boys’ dropouts and to explore the nature of relationships among different familial and institutional factors with dropouts. This paper is based on the empirical study carried out in one of the most backward districts of West Bengal. A questionnaire on the school dropout factors having 24 items was designed and administered among 93 respondents. The items of the questionnaire were identified through a review of the extant literature. Frequency distribution and ordinal logistic regression were used to analyse the data. Results indicate that key determinants of dropouts are expiry of breadwinner, household works, personal health problems, lack of interest and failure in examinations in studies.
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Kim, Jangsaeng, and Miyang Jun. "Money, a Drain of Educational Opportunity: A Microregional Study of School Dropouts in Mpigi, Uganda." Sustainability 14, no. 10 (May 12, 2022): 5875. http://dx.doi.org/10.3390/su14105875.
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This paper sheds light on the causes of school dropouts, a major challenge facing UPE attainment in public primary schools of Uganda. We offer microregional analysis of school dropout patterns in the Mpigi district, and show a number of distinct patterns of school dropouts in Mpigi that can be differentiated from studies based on national data. While the Universal Primary Education program covered tuition fees, additional costs for education, such as meals, school transport, and uniforms, function as hurdles for longer school years. This is an obstacle regardless of parental awareness about education’s importance and how wealthy the parents think they are. Such findings directly conflict with existing knowledge that higher household income results in longer school years. The previous understanding of girl dropouts in Sub-Saharan Africa and its patriarchal context offer little explanations on the dropout pattern of Mpigi, as it is more related to the economic cost of education and the high demand for male agricultural labor. For a multicultural society such as Uganda, we highlight the importance of microlevel regional study in educational research.
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Azevedo, Ana Paula da Silva, Clara Nóbrega, Alberto Carlos Amadio, and Júlio Cerca Serrão. "ADHERENCE TO SIX MONTHS OF INSTRUCTED MINIMALIST AND BAREFOOT RUNNING TRAINING." Revista Brasileira de Medicina do Esporte 22, no. 3 (June 2016): 182–85. http://dx.doi.org/10.1590/1517-869220162203152987.
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ABSTRACT Introduction: The interest in minimalist and barefoot running is growing continuously. However, there is no data on how many runners drop out during this process. Objective: To describe the adhesion and dropout rates of a six-month instructed training program based on barefoot and minimalist footwear running. Methods: Thirty-four recreational runners participated in the study: 20 runners started the race training barefoot, while 14 runners were involved in training with minimalist footwear. Adhesion to intervention programs was evaluated through training spreadsheets and recording attendance at training sessions, while dropouts were evaluated at the end of training. A questionnaire was sent to participants who dropped out of the training, to obtain information related on why they had abandoned it. Results: Considering all participants (n=34), 41.2% of the runners completed six months with reduced plantar protection; 70% of all dropouts occurred in barefoot training; the main reasons for leaving the training were injury/pain (40%) and lack of time/suitable place for training (40%); and the majority of dropouts (50%) occurred in the first month of training. Barefoot training (n=20) showed 70% dropouts, 57.1% of them due to lack of time/suitable place for training; and 71.4% of the dropouts occurred in the first month of the intervention. The training with minimalist footwear (n=14) had fewer dropouts (42.9%) than the barefoot training, all of them due to injury/pain; 50% of them occurred in the third month of intervention. Conclusion: Dropouts usually occur at the beginning of training. Training involving barefoot running has more dropouts than training with minimalist footwear. Intervention programs lasting six months based on minimalist footwear/barefoot seems to have similar adhesion to other supervised exercise programs. The main reasons for dropping out are injury/pain and lack of time/suitable place to run.
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Liu, Chunping, Rong Xiong, Jianxin Xu, and Jun Wu. "On Iterative Learning Control for Remote Control Systems with Packet Losses." Journal of Applied Mathematics 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/245372.
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The problem of iterative learning control (ILC) is considered for a class of time-varying systems with random packet dropouts. It is assumed that an ILC scheme is implemented via a remote control system and that packet dropout occurs during the packet transmission between the ILC controller and the actuator of remote plant. The packet dropout is viewed as a binary switching sequence which is subject to the Bernoulli distribution. In order to eliminate the effect of packet dropouts on the convergence property of output error, the hold-input scheme is adopted to compensate the packet dropout at the actuator. It is shown that the hold-input scheme with average ILC can achieve asymptotical convergence along the iteration axis for discrete time-varying linear system. Numerical examples are provided to show the effectiveness of the proposed method.
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Radovanovic, Sandro, Boris Delibasic, and Milija Suknovic. "Predicting dropout in online learning environments." Computer Science and Information Systems, no. 00 (2020): 53. http://dx.doi.org/10.2298/csis200920053r.
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Online learning environments became popular in recent years. Due to high attrition rates, the problem of student dropouts became of immense importance for course designers, and course makers. In this paper, we utilized lasso and ridge logistic regression to create a prediction model for dropout on the Open University database. We investigated how early dropout can be predicted, and why dropouts occur. To answer the first question, we created models for eight different time frames, ranging from the beginning of the course to the mid-term. There are two results based on two definitions of dropout. Results show that at the beginning AUC of the prediction model is 0.549 and 0.661 and rises to 0.681 and 0.869 at mid-term. By analyzing logistic regression coefficients, we showed that at the beginning of the course demographic features of the student and course description features are the most important variables for dropout prediction, while later student activity gains more importance.
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Yan, Haojing, Seth H. Cohen, Rogier A. Windhorst, Rolf A. Jansen, Zhiyuan Ma, John F. Beacom, Chenxiaoji Ling, et al. "JWST's PEARLS: Bright 1.5–2.0 μm Dropouts in the Spitzer/IRAC Dark Field." Astrophysical Journal Letters 942, no. 1 (December 28, 2022): L8. http://dx.doi.org/10.3847/2041-8213/aca974.
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Abstract Using the first epoch of four-band NIRCam observations obtained by the James Webb Space Telescope (JWST) Prime Extragalactic Areas for Reionization and Lensing Science Program in the Spitzer IRAC Dark Field, we search for F150W and F200W dropouts. In 14.2 arcmin2, we have found eight F150W dropouts and eight F200W dropouts, all brighter than 27.5 mag (the brightest being ∼24 mag) in the band to the red side of the break. As they are detected in multiple bands, these must be real objects. Their nature, however, is unclear, and characterizing their properties is important for realizing the full potential of JWST. If the observed color decrements are due to the Lyman break, these objects should be at z ≳ 11.7 and z ≳ 15.4, respectively. The color diagnostics show that at least four F150W dropouts are far away from the usual contaminators encountered in dropout searches (red galaxies at much lower redshifts or brown dwarf stars). While the diagnostics of the F200W dropouts are less certain due to the limited number of passbands, at least one of them is likely not a known type of contaminant, and the rest are consistent with either high-redshift galaxies with evolved stellar populations or old galaxies at z ≈ 3–8. If a significant fraction of our dropouts are indeed at z ≳ 12, we have to face the severe problem of explaining their high luminosities and number densities. Spectroscopic identifications of such objects are urgently needed.
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Anderson, Jordan A., Shaelyn M. Harris, Erica L. Nelson, Ingrid Teuber, and Andrew Futterman. "DIMINISHED COMPLEXITY OF RELIGIOUS BELIEF AMONG DROPOUTS FROM A LONGITUDINAL STUDY OF COPING." Innovation in Aging 3, Supplement_1 (November 2019): S458. http://dx.doi.org/10.1093/geroni/igz038.1714.
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Abstract Selective attrition is a common problem in longitudinal studies of older adults. Dropout is due to many factors, but frequently health concerns figure prominently as a reason for attrition. In light of previous work that suggests health problems reduce complexity of religious and other social involvements, the current study examines complexity of religiousness among dropouts and continuers in a longitudinal study of religion and health in later life. A random sample of 287 older adults living in Worcester, MA was assessed at two times of measurement 12 months apart using interview-based measures of religious orientation (Batson, Schoenrade, and Ventis, 1993) and health (OARS). Of the 287 who began the study, 72 dropped out and were not available to be assessed at 12 month assessment. Using Mplus, a three-factor model of Ends, Means, and Quest orientations demonstrated a good fit to the data in both dropout and continuer subsamples (e.g., CFI’s equaled .959 and .966, respectively). Diminished correlations between Ends, Means, and Quest orientations in the dropout vs. continuer subsample suggests diminished complexity of religious orientation among dropouts. Dropouts were more seriously ill, had higher levels of functional impairment, and demonstrated lower SES, suggesting increased vulnerability and fewer resources may have been the reason for dropping from the study as well as one possible cause of their diminished religious complexity.
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Rasca, Anthony P., William M. Farrell, Phyllis L. Whittlesey, Robert J. MacDowall, Stuart D. Bale, and Justin C. Kasper. "Magnetic Field Dropouts and Associated Plasma Wave Emission near the Electron Plasma Frequency at Switchback Boundaries as Observed by the Parker Solar Probe." Astrophysical Journal 935, no. 2 (August 1, 2022): 81. http://dx.doi.org/10.3847/1538-4357/ac80c3.
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Abstract The first solar encounters by the Parker Solar Probe revealed the magnetic field to be dominated by short field reversals in the radial direction, referred to as “switchbacks.” While radial velocity and proton temperature were shown to increase inside the switchbacks, ∣B∣ exhibits very brief dropouts only at the switchback boundaries. Brief intensifications in spectral density measurements near the electron plasma frequency, f pe, were also observed at these boundaries, indicating the presence of plasma waves triggered by current systems in the form of electron beams. We perform a correlative study using observations from the Parker FIELDS Radio Frequency Spectrometer and Fluxgate Magnetometer to compare occurrences of spectral density intensifications at the electron plasma frequency (f pe emissions) and ∣B∣ dropouts at switchback boundaries during Parker’s first and second solar encounters. We find that only a small fraction of minor ∣B∣ dropouts are associated with f pe emissions. This fraction increases with ∣B∣ dropout size until all dropouts are associated with f pe emissions. Brief spikes in the differential electron flux measured by the SWEAP Solar Probe Analyzer for Electron sensors also occur in conjunction with nearly all f pe emissions. This suggests that in the presence of strong ∣B∣ dropouts, electron currents that create the perturbation in ∣B∣ along the boundaries are also stimulating plasma waves such as Langmuir waves.
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Gruenhagen, Katheen A. "Appalachian Special Education Students Dropping Out of School: Looking at the Whos and Whys." Rural Special Education Quarterly 12, no. 2 (June 1993): 14–20. http://dx.doi.org/10.1177/875687059301200204.
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Although the literature suggests there is a high rate of dropping out of school even among students receiving special education, there is a paucity of research dealing with circumstances surrounding the special education student who leaves school prematurely. This study investigated the characteristics, reasons, and unmet school needs of students with disabilities who have dropped out of school in seventeen southern Appalachian counties. Data were collected on 135 student dropouts by polling those teachers who reported having dropouts. Results indicated that the average dropout was a 16 year old white male who was entering the ninth grade and who had not previously been employed. Future dropout prevention programs for this population therefore should begin before high school, be geared toward white males, and include instruction in the world of work.
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Hernández-Rodríguez, Juan-Carlos, Cristina García-Muñoz, Juan Ortiz-Álvarez, Francesc Saigí-Rubió, Julián Conejo-Mir, and Jose-Juan Pereyra-Rodriguez. "Dropout Rate in Digital Health Interventions for the Prevention of Skin Cancer: Systematic Review, Meta-analysis, and Metaregression." Journal of Medical Internet Research 24, no. 12 (December 9, 2022): e42397. http://dx.doi.org/10.2196/42397.
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Background Digital strategies are innovative approaches to the prevention of skin cancer, but the attrition following this kind of intervention needs to be analyzed. Objective The aim of this paper is to assess the dropouts from studies focused on digital strategies for the prevention of skin cancer. Methods We conducted this systematic review with meta-analyses and metaregression according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statements. Search terms for skin cancer, digital strategies, and prevention were combined to search PubMed, Scopus, Web of Science, CINAHL, and Cochrane Library from inception until July 2022. Randomized clinical trials that reported dropouts of participants and compared digital strategies with other interventions to prevent skin cancer in healthy or disease-free participants were included. Two independent reviewers extracted data for analysis. The Revised Cochrane Collaboration Bias tool was employed. We calculated the pooled dropout rate of participants through a meta-analysis of proportions and examined whether dropout was more or less frequent in digital interventions against comparators via an odds ratio (OR) meta-analysis. Data were pooled using a random-effects model. Subgroup meta-analyses were conducted in a meta-analysis of proportions and OR meta-analysis to assess the dropout events when data were sorted by digital interventions or control comparator. A univariate metaregression based on a random-effects model assessed possible moderators of dropout. Participants’ dropout rates as pooled proportions were calculated for all groups combined, and the digital and comparator groups separately. OR>1 indicated higher dropouts for digital-based interventions. Metaregressions were performed for age, sex, length of intervention, and sample size. Results A total of 17 studies were included. The overall pooled dropout rate was 9.5% (95% CI 5.0-17.5). The subgroup meta-analysis of proportions revealed a dropout rate of 11.6% for digital strategies (95% CI 6.8-19.0) and 10.0% for comparators (95% CI 5.5-17.7). A trend of higher dropout rates for digital strategies was observed in the overall (OR 1.16, 95% CI 0.98-1.36) and subgroup OR meta-analysis, but no significant differences were found between the groups. None of the covariates moderated the effect size in the univariate metaregression. Conclusions Digital strategies had a higher dropout rate compared to other prevention interventions, but the difference was not significant. Standardization is needed regarding reporting the number of and reasons for dropouts. Trial Registration International Prospective Register of Systematic Reviews (PROSPERO) CRD42022329669; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=329669
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Sarnquist, Clea, Jake Sinclair, Benjamin Omondi Mboya, Nickson Langat, Lee Paiva, Bonnie Halpern-Felsher, Neville H. Golden, Yvonne A. Maldonado, and Michael T. Baiocchi. "Evidence That Classroom-Based Behavioral Interventions Reduce Pregnancy-Related School Dropout Among Nairobi Adolescents." Health Education & Behavior 44, no. 2 (July 11, 2016): 297–303. http://dx.doi.org/10.1177/1090198116657777.
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Purpose. To evaluate the effect of behavioral, empowerment-focused interventions on the incidence of pregnancy-related school dropout among girls in Nairobi’s informal settlements. Method. Retrospective data on pregnancy-related school dropout from two cohorts were analyzed using a matched-pairs quasi-experimental design. The primary outcome was the change in the number of school dropouts due to pregnancy from 1 year before to 1 year after the interventions. Results. Annual incidence of school dropout due to pregnancy decreased by 46% in the intervention schools (from 3.9% at baseline to 2.1% at follow-up), whereas the comparison schools remained essentially unchanged ( p < .029). Sensitivity analysis shows that the findings are robust to small levels of unobserved bias. Conclusions. Results suggest that these behavioral interventions significantly reduced the number of school dropouts due to pregnancy. As there are limited promising studies on behavioral interventions that decrease adolescent pregnancy in low-income settings, this intervention may be an important addition to this toolkit.
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Morrow, George. "Standardizing Practice in the Analysis of School Dropouts." Teachers College Record: The Voice of Scholarship in Education 87, no. 3 (March 1986): 342–55. http://dx.doi.org/10.1177/016146818608700306.
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After demonstrating the types of problems that arise from using different methods to calculate school dropout rates, Morrow suggests a set of procedures to standardize the process and improve the validity and reliability of data on dropouts.
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Boylan, Rebecca L., and Linda Renzulli. "Routes and Reasons Out, Paths Back." Youth & Society 49, no. 1 (August 2, 2016): 46–71. http://dx.doi.org/10.1177/0044118x14522078.
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Dropout is a major issue facing our country’s schools; however, many students who drop out of school later go on to finish their degree either by returning to high school or by earning a General Education Development (GED) credential. Despite this, there has been relatively little research on these students who “stopout” of high school. Drawing on a sample of high school dropouts, we build on research conceptualizing dropouts as having been “pushed” or “pulled” out of school by examining how routes out of school influence the process of return. Our analysis reveals that being either pushed or pulled has little differential impact on the reengagement process. But, particular reasons within the categories have strong effects on keeping students out of school and on the pathways that they take if they return. Implications are suggested for both school practice and for how researchers should best conceptualize dropouts.
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Nurmalitasari, Zalizah Awang Long, and Mohammad Faizuddin Mohd Noor. "Factors Influencing Dropout Students in Higher Education." Education Research International 2023 (February 8, 2023): 1–13. http://dx.doi.org/10.1155/2023/7704142.
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Dropout students are a severe problem in higher education (HE) in many countries. Student dropout has a tremendous negative impact not only on individuals but also on universities and socioeconomic. Consequently, preventing educational dropouts is a considerable challenge for HE’s institutions. Therefore, knowing the factors influencing student dropout is an essential first step in preventing students from dropping out. This study uses a mix of qualitative and quantitative approaches. To determine what variables affect student dropout, we use a qualitative approach, after which the variables found will be validated by the public and stakeholders using a quantitative approach. Then, the next step is to classify variables using a quantitative approach. This study observes dropout students at private universities in Central Java, Indonesia. The findings reveal that personal economic factors, academic satisfaction, academic performance, and family economics are the most influential. The results of this paper are significant for universities in Indonesia, especially Central Java, to overcome the problem of student dropouts, so that they are more precise in making decisions. In addition, the results of this study are also helpful for further research as a basis for predicting students dropping out of university.
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Gupta, Priyanka. "EFFORTS TO REINTEGRATE DROPOUTS IN LIGHT OF DRAFT OF NATIONAL EDUCATION POLICY 2019." Researchers' Guild 2, no. 1 (October 9, 2020): 95–101. http://dx.doi.org/10.15503/rg2019.10.
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Dropouts are the children who are not in the educational field because of various reasons. All those children who could not either get enrolled in the school or dropout from the school before completing the education. There have many efforts to bring all children in school. Right to Education was one such effort to achieve 100% enrolment for children upto 14 years. Draft of National Education Policy has also suggested various measures to ensure that all the students could be streamlined in the educational field. This paper critically analyzes the suggestions made in the Draft of National Education Policy to reintegrate the dropouts.
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Toha, Muhammad. "ANALISIS KETERAMPILAN DRIBBLING PERMAINAN FUTSAL PADA REMAJA PUTUS SEKOLAH DI DESA SUKA MAJU BENGKULU UTARA." Educative Sportive 1, no. 01 (June 15, 2020): 6–12. http://dx.doi.org/10.33258/edusport.v1i01.1062.
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Based on the researcher's observations on the implementation of school dropout soccer game activities in Suka Maju Village, North Bengkulu Regency, that the researcher wants to analyze the football skill level of School Dropout Youth in Suka Maju Village, North Bengkulu Regency. This research method is quantitative descriptive. The population of this study was all 20 school dropouts in Suka Maju Village, North Bengkulu Regency. The place for the research was carried out in the futsal field in Suka Maju Village, North Bengkulu Regency, while the research time was April 2018. Data on dribbling skills were taken using the physical freshness center theory dribbling test. The data analysis technique of this research uses techniques with quantitative data analysis. The results of the data analysis show that: The basic skills of futsal dribbling for school dropouts in rural villages like Bengkulu Utara. With 9 people in the good category with a relative frequency magnitude of 45%, 9 people in the medium category with a relative frequency magnitude of 45%, 1 person in the less category with a frequency magnitude of 5% and 1 person in the very poor category with a frequency magnitude of 5%. Meanwhile, the average skills of rural school dropouts like to advance are in the medium category with a score of 49.5.
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Itzhaki, Yael. "The Different Role of Mentor Support Along the High-School Dropout Process." Youth & Society 51, no. 7 (September 26, 2018): 981–1008. http://dx.doi.org/10.1177/0044118x18803260.
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This study examined the contribution of mentor support to the following aspects of high-school dropouts’ lives: the personal (self-esteem, and the process of becoming less religious [BLR]), social (societal conditional positive and negative regard) and psychological (well-being and loneliness). The study, conducted among Ultraorthodox Jewish males, included 261 participants, aged 14 years to 21 years ( M = 17, SD = 1.17), who were at different stages in the dropout process. Findings indicated a significant difference in the contribution of mentor support. Among youths still in their yeshiva high schools, mentor support made only a minor contribution to the process of BLR; for youths in a program for dropouts, mentor support made a positive contribution to most aspects of their lives. However, among dropouts, mentor support contributed negatively to all aspects that were examined in the current study. Findings highlight the importance of further illuminating the role of mentor support and adapting it to youths’ needs.
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Feng, Wenzheng, Jie Tang, and Tracy Xiao Liu. "Understanding Dropouts in MOOCs." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 517–24. http://dx.doi.org/10.1609/aaai.v33i01.3301517.
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Massive open online courses (MOOCs) have developed rapidly in recent years, and have attracted millions of online users. However, a central challenge is the extremely high dropout rate — recent reports show that the completion rate in MOOCs is below 5% (Onah, Sinclair, and Boyatt 2014; Kizilcec, Piech, and Schneider 2013; Seaton et al. 2014).What are the major factors that cause the users to drop out?What are the major motivations for the users to study in MOOCs? In this paper, employing a dataset from XuetangX1, one of the largest MOOCs in China, we conduct a systematical study for the dropout problem in MOOCs. We found that the users’ learning behavior can be clustered into several distinct categories. Our statistics also reveal high correlation between dropouts of different courses and strong influence between friends’ dropout behaviors. Based on the gained insights, we propose a Context-aware Feature Interaction Network (CFIN) to model and to predict users’ dropout behavior. CFIN utilizes context-smoothing technique to smooth feature values with different context, and use attention mechanism to combine user and course information into the modeling framework. Experiments on two large datasets show that the proposed method achieves better performance than several state-of-the-art methods. The proposed method model has been deployed on a real system to help improve user retention.
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Klein, Edward B., Walter N. Stone, Mitchell W. Hicks, and Ian L. Pritchard. "Understanding Dropouts." Journal of Mental Health Counseling 25, no. 2 (April 1, 2003): 89–100. http://dx.doi.org/10.17744/mehc.25.2.xhyreggxdcd0q4ny.
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This study examined differences between clients who did or did not notify mental health providers of intent to discontinue treatment. Clients who did not notify were more likely to be women, attend less than four sessions, and rate their overall functioning lower. Both groups showed significant improvement, and self-reports were found to be a better indicator of progress than counselor estimates. Findings suggested that the adoption of mutual goals and empathetic counselor attitudes toward client treatment expectations might increase staff awareness of satisfied dropouts who have made therapeutic gains. Implications include benefits to staff morale and the larger Community Mental Health Center system in which almost half of all clients discontinue treatment without informing staff.
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Gottheil, Edward, Robert C. Sterling, and Stephen P. Weinstein. "Pretreatment Dropouts." Journal of Addictive Diseases 16, no. 2 (February 27, 1997): 1–14. http://dx.doi.org/10.1300/j069v16n02_01.
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Fernandez, Ricardo R., and Gangjian Shu. "School Dropouts." Education and Urban Society 20, no. 4 (August 1988): 363–86. http://dx.doi.org/10.1177/0013124588020004005.
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Holroyd, Ed, and R. Monastersky. "Soluble Dropouts." Science News 142, no. 17 (October 24, 1992): 275. http://dx.doi.org/10.2307/4017974.
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