Public school district drop out rates for SY 2015 by race and gender

EDFacts Graduates and Dropouts, 2014-15 (EDFacts GD:2014-15) is one of 17 “topics" identified in the EDFacts documentation (in this database, each “topic" is entered as a separate study). EDFacts GD:2014-15 (ed.gov/about/inits/ed/edfacts) annually collects cross-sectional data from states about student who graduate or receive a certificate of completion from secondary education or students who dropped out of secondary education at the school, LEA, and state levels. EDFacts GD:2014-15 data were collected using the EDFacts Submission System (ESS), a centralized portal and their submission by states is mandatory and required for benefits. Not submitting the required reports by a state constitutes a failure to comply with law and may have consequences for federal funding to the state. Key statistics produced from EDFacts GD:2014-15 are from 6 data groups with information on Regulatory Cohort Graduation Rate (Four, Five, and Six Year)-Graduation Rate; Regulatory Cohort Graduation Rate (Four, Five, and Six Year)-Student Counts; Graduation Rate; Graduates/Completers; Regulatory Cohort Graduation Rate-Flex; and Regulatory Cohort Graduation Rate Student Counts-Flex. For the purposes of this system, data groups are referred to as 'variables', as a result of the structure and format of EDFacts' data.

The percentage of 9th through 12th graders who withdrew from public school out of all high school students in a school year. Withdraw codes are used as a proxy for dropping out of school based upon the expectation that withdrawn students are no longer receiving educational services. A dropout is defined as a student who, for any reason other than death, leaves school before graduation or the completion of a Maryland-approved education program and is not known to enroll in another school or State-approved program during a current school year. Source: Baltimore City Public School SystemYears Available: 2009-2010, 2010-2011, 2011-2012, 2012-2013, 2013-2014, 2014-2015, 2015-2016, 2016-2017, 2018-2019, 2019-2020, 2020-2021, 2021-2022, 2022-2023

Historical Dataset of Lakeview Dropout Prevention is provided by PublicSchoolReview and contain statistics on metrics:Total Students Trends Over Years (1999-2023),Total Classroom Teachers Trends Over Years (2000-2014),Distribution of Students By Grade Trends,Student-Teacher Ratio Comparison Over Years (2000-2014),Asian Student Percentage Comparison Over Years (2001-2016),Hispanic Student Percentage Comparison Over Years (1998-2018),Black Student Percentage Comparison Over Years (1999-2023),White Student Percentage Comparison Over Years (1999-2023),Two or More Races Student Percentage Comparison Over Years (2011-2023),Diversity Score Comparison Over Years (1999-2023),Free Lunch Eligibility Comparison Over Years (2002-2023),Reduced-Price Lunch Eligibility Comparison Over Years (2005-2014),Graduation Rate Comparison Over Years (2011-2019)

In 2023, the number of children out of school in Tanzania increased by ***** thousand children (+***** percent) compared to 2022. In total, the number of children out of school amounted to * million children in 2023. Out-of-school children are the number of school-age children enrolled in primary or secondary school minus the total population of the official primary school-age children.

The percentage of 9th through 12th graders who withdrew from public school out of all high school students in a school year. Withdraw codes are used as a proxy for dropping out of school based upon the expectation that withdrawn students are no longer receiving educational services. A dropout is defined as a student who, for any reason other than death, leaves school before graduation or the completion of a Maryland-approved education program and is not known to enroll in another school or State-approved program during a current school year. Source: Baltimore City Public School System Years Available: 2009-2010, 2010-2011, 2011-2012, 2012-2013, 2013-2014, 2014-2015, 2015-2016, 2016-2017, 2018-2019, 2019-2020, 2020-2021

This dataset tracks annual reduced-price lunch eligibility from 2005 to 2014 for Lakeview Dropout Prevention vs. Florida and Escambia School District

Communities In Schools (CIS) works to provide and connect students with integrated support services to keep them on a path to graduation. The intent of the CIS model is to reduce dropout rates by integrating community and school-based support services within schools through the provision of "Level 1" and "Level 2" services. Level 1 services are broadly available to all students or to groups of students and are usually short-term, low intensity activities or services. CIS Coordinators spend much of their time focused on more intensive Level 2 "case-managed" services, which they provide to a subset of students displaying one or more significant risk factors, such as poor academic performance, a high absentee rate, or behavioral problems. This study was a two-year randomized controlled trial of Level-2 CIS case management, which examined service provision, student experiences and student outcomes. This trial was half of a two-pronged national evaluation, the other half was a quasi-experimental study of the whole-school model. The study evaluated 24 mostly urban, low-income secondary schools in North Carolina and Texas during the 2012-2013 and 2013-2014 school years; baseline data was also collected during the 2011-2012 school year. Data was collected through student surveys, school records, and CIS management information systems (MIS) data. The data in this collection is student-level, including all information collected about students in the study sample with 613 variables and 4459 cases. The dataset includes three school years of data: baseline period (2011-2012), first year of implementation (2012-2013) and second year of implementation (2013-2014). Demographic variables in this collection include: free lunch status, special education status, employment, race, language, ethnicity, gender, household members, number of siblings, parents' education level, and grade level.

Abstract The undergraduate dropout rate is a management concern and can generate many academic studies. In Brazil, the Ministry of Education annually conducts the Census of Higher Education. The different methodologies for calculating and analyzing indicators of school dropout rate are often considered imprecise and inconsistent, weakening their importance in public policies and strategies for control and improvement of educational services within higher education institutions. This exploratory study uses a quantitative technique and presents systematization for the school dropout rate analysis, using the Census as a data source. Looking for Census from 2009 to 2014, organizational knowledge can be systematically extracted. The proposed methodology contributes to the alignment between information technology and knowledge management. It is possible to develop solutions that facilitate and organize the sharing of ideas, good practices and data that can be transformed from the implicit to the explicit state, contributing to the managers and course coordinators to control evasion.

These data are calculated based on the year of cohort, that is, the academic year in which a group of students began university studies. In each COHORTE COURSE all data (including graduation data) are referenced to the year in which studies were initiated in order to track students who started studies at the same time. Graduate students collect the number of students from a new entry cohort who have completed all curriculum credits, regardless of the year they finished. Time Graduate Students is the number of students in a new entry cohort who graduate on schedule or one more year. Dropout rate is the percentage of students in a new-income cohort who had to earn the degree in the intended academic year, according to the duration of the plan, and who have not enrolled in either that academic year or the next. Initial Abandonment Rate is the percentage of students in a new-income cohort who, without obtaining the degree, do not enroll in the study either of the two academic years following the entry Rate of Graduation Percentage of students who complete teaching in the expected time or in one more year relative to their incoming cohort. The fees exclude students from grade adaptation courses, students who have recognised (or adapted or validated) more than 15 % of the credits of the curriculum and students enrolled in the part-time modality in any of the years studied.

Historical Dataset of Gates Open Doors Program High School is provided by PublicSchoolReview and contain statistics on metrics:Graduation Rate Comparison Over Years (2014-2015)

As of 2018, the drop-out rate in middle schools in Nigeria was slightly higher among male students. In the second class of lower secondary school, some ** percent of males dropped-out, while the share of female students reached ** percent.

The official junior secondary education age in Nigeria goes from 12 to 14 years old.

Baseline characteristics of study population, 2011–2014.

This section presents statistical information on the educational variables that are collected in the Labour Force Survey of the National Institute of Statistics, as well as in the Community Labour Force Survey (Eurostat). The indicators of the strategic framework for European cooperation in education and training (2021-2030) that derive from these sources are highlighted. The information is presented disaggregated by autonomous community and by country of the European Union, according to the source used, and with temporary developments since 2002.Line break The results are obtained as annual averages of quarterly data, so the information is updated annually, as the four quarters of the EPA are available, as well as the results derived from the Community survey of Eurostat. From the 2014 results of the EPA, the new National Classification of Education, CNED-2014, based on the International Standard Classification of Education, ISCED-2011, applied in the LFS, is applied; and from 2016, the update of the sectors/fields of study of both classifications (CNED-F and ISCED-F) is applied. These changes in the rankings represent a series break for some of the tables, as indicated in the accompanying notes.

The LA Promise Zone is a collective impact project involving leaders from government, local institutions, non-profits and community organizations that targets resources to create jobs, boost public safety, improve public education and stimulate better housing opportunities for our residents and neighborhoods.The Promise Zone is located within Central Los Angeles and includes the neighborhoods of Hollywood, East Hollywood, Koreatown, Pico Union and Westlake. The Zone is home to approximately 165,000 residents, of whom 35% live in poverty. Nearly one-quarter of Promise Zone households earn less than $15,000 each year, and educational attainment for adults is weak with 35% of the population 25 years of age and older having obtained less than a high school diploma. The Promise Zone also has alarming high school dropout rates, high unemployment, and a shortage of affordable housing. Large shares of recent immigrant populations hailing from Latin America, Asia and Eastern Europe live there.

Multivariate analysis of nursing school attrition and nursing school completion in more than four years among students admitted to nursing school at the School of Health Sciences (ESCS), Brasília, Federal District, Brazil, between 2009 and 2014.

Univariate analysis comparing students admitted to nursing school at the School of Health Sciences (ESCS), Brasília, Federal District, Brazil, from the regular path and social quota systems between 2009 and 2014 (n = 448).

Korea Primary Completion Rate: Male: % of Relevant Age Group data was reported at 98.371 % in 2015. This records an increase from the previous number of 94.148 % for 2014. Korea Primary Completion Rate: Male: % of Relevant Age Group data is updated yearly, averaging 101.470 % from Dec 1971 (Median) to 2015, with 44 observations. The data reached an all-time high of 109.669 % in 2012 and a record low of 93.806 % in 2002. Korea Primary Completion Rate: Male: % of Relevant Age Group data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Korea – Table KR.World Bank: Education Statistics. Primary completion rate, or gross intake ratio to the last grade of primary education, is the number of new entrants (enrollments minus repeaters) in the last grade of primary education, regardless of age, divided by the population at the entrance age for the last grade of primary education. Data limitations preclude adjusting for students who drop out during the final year of primary education.; ; UNESCO Institute for Statistics; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

Bahamas BS: Primary Completion Rate: Female: % of Relevant Age Group data was reported at 77.330 % in 2014. This records an increase from the previous number of 76.044 % for 2013. Bahamas BS: Primary Completion Rate: Female: % of Relevant Age Group data is updated yearly, averaging 85.782 % from Dec 1999 (Median) to 2014, with 11 observations. The data reached an all-time high of 92.927 % in 2005 and a record low of 76.044 % in 2013. Bahamas BS: Primary Completion Rate: Female: % of Relevant Age Group data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Bahamas – Table BS.World Bank.WDI: Social: Education Statistics. Primary completion rate, or gross intake ratio to the last grade of primary education, is the number of new entrants (enrollments minus repeaters) in the last grade of primary education, regardless of age, divided by the population at the entrance age for the last grade of primary education. Data limitations preclude adjusting for students who drop out during the final year of primary education.;UNESCO Institute for Statistics (UIS). UIS.Stat Bulk Data Download Service. Accessed April 5, 2025. https://apiportal.uis.unesco.org/bdds.;Weighted average;

Introduction and Background. Minorities are less likely to report rapes. The Post Coital DNA Recovery (PCDR) study (2009-14) subjects were white (93%) where expanded collection times were not generalizable to minority populations. Evidence reports health and medical differences between races necessitating duplication of previous research in minority populations. Aims. (1) What is the time period in which it is possible to collect post-coital DNA in minority women using Y-STR laboratory methods? and (2) when compared to the former study sample of minority and non-minority, what are the physiological conditions, factors, or activities in minority couples that influence post-coital DNA recovery? Design. The design includes mixed methods duplication perfected in the first study, embracing descriptive and inferential techniques. Qualitative research used semi-structured interviews. Aim 1 analysis used PCDR-M data only. Aim 2 combined data from both PCDR and PCDR-M studies. Combined, DNA recovery, a binary outcome accounting for repeated methods in population regression analysis, used Generalized Estimating Equation (GEE) methods. Fidelity. The strict criteria for adherence included considerable outreach and support of study personnel. PCDR and PCDR-M data combined and compared the two samples, which had specific homogeneity, including same inclusion and elimination criteria in both studies; fidelity to the validated protocol; laboratory method and interpretation for inclusion; duplicate statistical analysis; and interpretation of data. Any variation in key variables met elimination criteria. Assumptions and Limitations. Assumptions included (1) motivation is altruistic; (2) motivation is incentives and coercion for some; (3) negotiating coitus is difficult and stressful; and (4) similar fidelity and dropout rates. The limitations included (1) a lack of representation for the diverse experiences of rape victims; (2) sample size; (3) self-selection bias; (4) protocol adherence; and (4) advances in laboratory science and DNA kits. Demographics. Demographic variables included gender, race, and age. Major categories in the dataset included participants' reproductive history, data on female participants' reproductive organs, and childhood abuse.