7 datasets found
  1. Student retention rates at NSW government schools (2014-2023)

    • data.nsw.gov.au
    • researchdata.edu.au
    csv, pdf
    Updated Mar 3, 2025
    + more versions
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    NSW Department of Education (2025). Student retention rates at NSW government schools (2014-2023) [Dataset]. https://data.nsw.gov.au/data/dataset/nsw-education-student-retention-rates-nsw-gov-schools
    Explore at:
    pdf(151686), csv(395), pdf(129474), csv(1021), pdf(173748), pdf(286524), csv(949), pdf(193811), csv(956), csv(230)Available download formats
    Dataset updated
    Mar 3, 2025
    Dataset provided by
    NSW Department of Educationhttps://education.nsw.gov.au/
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Government of New South Wales, New South Wales
    Description

    The full-time apparent retention rate (ARR) measures the proportion of a cohort of full-time students that moves from one grade to the next, based on an expected rate of progression of one grade per year. It does not track individual students through their final years of secondary schooling.

    Data Notes:

    • The ARR is the ratio of the total number of full-time school students in a designated year (e.g. Year 12 in 2020) divided by the total number of full-time students in a previous year (e.g. Year 7 in 2015). This would be the Year 7 to 12 apparent retention rate in 2020.

    • From 2020, students in mainstream support classes (previously excluded from this data) are reported by their underlying grade of enrolment. As a result, data from 2020 onwards is not directly comparable to previous years. A separate column in the CSV files has been provided to show the 2020 retention rates with both previous and revised counting rules. 2021 retention rates use the revised counting rules.

    • Support students at Schools for specific purposes (SSPs) do not have a designated grade and therefore are not counted in the calculation of ARRs. Support students in mainstream schools have been included in the calculations from 2020 (see above).

    • Reporting on ARRs based on small numbers of students can lead to unreliable ARR estimates. The tables combine ABS SA4 areas to ensure the underlying number of students is sufficiently large to generate reliable estimates.

    • Only full-time students are counted in the calculation of full-time apparent retention. Part-time students are excluded.

    • Students enrolled in distance education classes are included with their appropriate grade levels. Sydney-Inner includes enrolments from Sydney Distance Education High School.

    • ARRs can exceed 100 per cent due to factors including student migration from interstate and overseas and between school sectors.

    • Norfolk Island Central School is not included in the Apparent Retention Rate factsheet, but from 2018 to 2021 was included under NSW Government data in the ABS Schools Australia publication. This can lead to a slight difference in reported figures between Schools Australia and this dataset.

    • Aboriginal and/or Torres Strait Islander students are identified based on responses to the school enrolment form. This information may change throughout an individual’s schooling.

    • Reporting by non-binary gender is not possible due to system limitations.

    Data Source:

  2. r

    Schools Apparent Retention Rates, Victoria

    • researchdata.edu.au
    Updated Dec 20, 2021
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    data.vic.gov.au (2021). Schools Apparent Retention Rates, Victoria [Dataset]. https://researchdata.edu.au/schools-apparent-retention-rates-victoria/1877883
    Explore at:
    Dataset updated
    Dec 20, 2021
    Dataset provided by
    data.vic.gov.au
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    A dataset of schools apparent retention rates or ARR, all school sector in Victoria, from census year 2012 to 2023.\r This dataset is prepared and based on data collected from schools as part of the February School Census conducted on the last school day of February each year. It presents information for all government and non-government schools and student enrolments in Victoria, in particular secondary school years. The majority of the statistical data in this publication is drawn from school administration systems. The dataset includes analysis by school sector and sex, Koorie status, as well as on government schools by region.\r Apparent retention rates (ARR) are calculated based on aggregate enrolment data and provide an indicative measurement of student engagement in secondary education. The Department of Education and Training (DET) computes and publishes ARR data at a state-wide and DET region level only.\r \r The term "apparent" retention rate reflects that retention rates are influenced by factors not taken into account by this measure such as: Student repeating year levels, Interstate and overseas migration, Transfer of students between education sectors or schools, Student who have left school previously, returning to continue their school education.\r The ARR for year 7 to 12 (ARR 7-12) refers to the Year 12 enrolment expressed as a proportion of the Year 7 enrolment five years earlier. The ARR for year 10 to 12 (ARR 10-12) refers to the Year 12 enrolment expressed as a proportion of the Year 10 enrolment two years earlier.\r \r Please note that the ABS calculates apparent retention using the number of full-time school students only whereas at the DET we use the number of full-time equivalent school enrolments. Data reported in the ABS Schools, Australia collection is based on enrolment data collected in August by all jurisdictions.\r \r The Department has found that computing ARR at geographical areas smaller than DET regions (e.g. LGA, Postcode) can produce erratic and misleading results that are difficult to interpret or make use of. In small populations, relatively small changes in student numbers can create large movements in apparent retention rates. These populations might include smaller jurisdictions, Aboriginal and Torres Strait Islander students, and subcategories of the non-government affiliation. There are a number of reasons why apparent rates may generate results that differ from actual rates. \r Apparent retention rates provide an indicative measure of the number of full-time school students who have stayed in school, as at a designated year and grade of education. It is expressed as a percentage of the respective cohort group that those students would be expected to have come from, assuming an expected rate of progression of one grade per year.\r \r Provided ARR is a result of calculation of the whole census and is NOT to be re-calculated by average or sum.

  3. A

    Australia AU: Secondary Education: Duration

    • ceicdata.com
    Updated Mar 8, 2018
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    CEICdata.com (2018). Australia AU: Secondary Education: Duration [Dataset]. https://www.ceicdata.com/en/australia/social-education-statistics
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    Dataset updated
    Mar 8, 2018
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2012 - Dec 1, 2023
    Area covered
    Australia
    Variables measured
    Education Statistics
    Description

    AU: Secondary Education: Duration data was reported at 6.000 Year in 2023. This stayed constant from the previous number of 6.000 Year for 2022. AU: Secondary Education: Duration data is updated yearly, averaging 6.000 Year from Dec 1970 (Median) to 2023, with 54 observations. The data reached an all-time high of 6.000 Year in 2023 and a record low of 6.000 Year in 2023. AU: Secondary Education: Duration data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Australia – Table AU.World Bank.WDI: Social: Education Statistics. Secondary duration refers to the number of grades (years) in secondary school.;UNESCO Institute for Statistics (UIS). UIS.Stat Bulk Data Download Service. Accessed April 5, 2025. https://apiportal.uis.unesco.org/bdds.;Median;

  4. i

    Trends in International Mathematics and Science Study 2007 - Armenia,...

    • datacatalog.ihsn.org
    • catalog.ihsn.org
    • +1more
    Updated Jun 14, 2022
    + more versions
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    TIMSS International Study Center (2022). Trends in International Mathematics and Science Study 2007 - Armenia, Australia, Austria...and 55 more [Dataset]. https://datacatalog.ihsn.org/catalog/2376
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    Dataset updated
    Jun 14, 2022
    Dataset authored and provided by
    TIMSS International Study Center
    Time period covered
    2007
    Area covered
    Armenia, Australia
    Description

    Abstract

    TIMSS measures trends in mathematics and science achievement at the fourth and eighth grades in participating countries around the world, as well as monitoring curricular implementation and identifying promising instructional practices. Conducted on a regular 4-year cycle, TIMSS has assessed mathematics and science in 1995, 1999, 2003, and 2007, with planning underway for 2011. TIMSS collects a rich array of background information to provide comparative perspectives on trends in achievement in the context of different educational systems, school organizational approaches, and instructional practices. To support and promote secondary analyses aimed at improving mathematics and science education at the fourth and eighth grades, the TIMSS 2007 international database makes available to researchers, analysts, and other users the data collected and processed by the TIMSS project. This database comprises student achievement data as well as student, teacher, school, and curricular background data for 59 countries and 8 benchmarking participants. Across both grades, the database includes data from 433,785 students, 46,770 teachers, 14,753 school principals, and the National Research Coordinators of each country. All participating countries gave the IEA permission to release their national data.

    Geographic coverage

    The survey had national coverage

    Analysis unit

    Units of analysis in the study include documents, schools and individuals

    Universe

    The TIMSS target populations are all fourth and eighth graders in each participating country. The teachers in the TIMSS 2007 international database do not constitute representative samples of teachers in the participating countries. Rather, they are the teachers of nationally representative samples of students. Therefore, analyses with teacher data should be made with students as the units of analysis and reported in terms of students who are taught by teachers with a particular attribute. Teacher data are analyzed by linking the students to their teachers. The student-teacher linkage data files are used for this purpose.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    The TIMSS target populations are all fourth and eighth graders in each participating country. To obtain accurate and representative samples, TIMSS used a two-stage sampling procedure whereby a random sample of schools is selected at the first stage and one or two intact fourth or eighth grade classes are sampled at the second stage. This is a very effective and efficient sampling approach, but the resulting student sample has a complex structure that must be taken into consideration when analyzing the data. In particular, sampling weights need to be applied and a re-sampling technique such as the jackknife employed to estimate sampling variances correctly.

    In addition, TIMSS 2007 uses Item Response Theory (IRT) scaling to summarize student achievement on the assessment and to provide accurate measures of trends from previous assessments. The TIMSS IRT scaling approach used multiple imputation-or "plausible values"-methodology to obtain proficiency scores in mathematics and science for all students. Each student record in the TIMSS 2007 international database contains imputed scores in mathematics and science overall, as well as for each of the content domain subscales and cognitive domain subscales. Because each imputed score is a prediction based on limited information, it almost certainly includes some small amount of error. To allow analysts to incorporate this error into analyses of the TIMSS achievement data, the TIMSS database provides five separate imputed scores for each scale. Each analysis should be replicated five times, using a different plausible value each time, and the results combined into a single result that includes information on standard errors that incorporate both sampling and imputation error.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    The study used the following questionnaires: Fourth Grade Student Questionnaire, Fourth Grade Teacher Questionnaire, Fourth Grade School Questionnaire, Eighth Grade Student Questionnaire, Eighth Grade Mathematics Teacher Questionnaire, Eighth Grade Science Teacher Questionnaire, and Eighth Grade School Questionnaire. Information on the variables obtained or derived from questions in the survey is available in the TIMSS 2007 user guide for the international database: Data Supplement3: Variables derived from the Student, Teacher, and School Questionnaire data.

  5. f

    Vickers-Chan-7thGraders_Multiplex_Social .zip

    • figshare.com
    zip
    Updated Oct 7, 2022
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    Dan Wang (2022). Vickers-Chan-7thGraders_Multiplex_Social .zip [Dataset]. http://doi.org/10.6084/m9.figshare.21294870.v1
    Explore at:
    zipAvailable download formats
    Dataset updated
    Oct 7, 2022
    Dataset provided by
    figshare
    Authors
    Dan Wang
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The dataset representing the multiplex social network in a school in Victoria, Australia. If you use this dataset in your work either for analysis or for visualization, you should acknowledge/cite the following papers:

    Representing Classroom Social Structure. Melbourne: Victoria Institute of Secondary Education 
    M. Vickers and S. Chan, (1981)
    

    The data were collected by Vickers from 29 seventh grade students in a school in Victoria, Australia. Students were asked to nominate their classmates on a number of relations including the following three (layers):

    1. Who do you get on with in the class?
    2. Who are your best friends in the class?
    3. Who would you prefer to work with?

    Students 1 through 12 are boys and 13 through 29 are girls.

    There are 29 nodes in total, labelled with integer ID between 1 and 29, with 740 connections. The multiplex is directed and unweighted, stored as edges list in the file

    Vickers-Chan-7thGraders_multiplex.edges
    

    with format

    layerID nodeID nodeID weight
    

    (Note: all weights are set to 1)

    The IDs of all layers are stored in

    Vickers-Chan-7thGraders_layers.txt
    
  6. Australia AU: Lower Secondary School Starting Age

    • ceicdata.com
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    CEICdata.com, Australia AU: Lower Secondary School Starting Age [Dataset]. https://www.ceicdata.com/en/australia/social-education-statistics/au-lower-secondary-school-starting-age
    Explore at:
    Dataset provided by
    CEIC Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2012 - Dec 1, 2023
    Area covered
    Australia
    Variables measured
    Education Statistics
    Description

    Australia Lower Secondary School Starting Age data was reported at 12.000 Year in 2023. This stayed constant from the previous number of 12.000 Year for 2022. Australia Lower Secondary School Starting Age data is updated yearly, averaging 12.000 Year from Dec 1970 (Median) to 2023, with 54 observations. The data reached an all-time high of 12.000 Year in 2023 and a record low of 12.000 Year in 2023. Australia Lower Secondary School Starting Age data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Australia – Table AU.World Bank.WDI: Social: Education Statistics. Lower secondary school starting age is the age at which students would enter lower secondary education, assuming they had started at the official entrance age for the lowest level of education, had studied full-time throughout and had progressed through the system without repeating or skipping a grade.;UNESCO Institute for Statistics (UIS). UIS.Stat Bulk Data Download Service. Accessed April 5, 2025. https://apiportal.uis.unesco.org/bdds.;;

  7. i

    Trends in International Mathematics and Science Study 2003 - Argentina,...

    • catalog.ihsn.org
    • dev.ihsn.org
    Updated Aug 26, 2021
    + more versions
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    TIMSS International Study Center (2021). Trends in International Mathematics and Science Study 2003 - Argentina, Armenia, Australia, Belgium, Bulgaria, Bahrain, Botswana, Canada, Chile, Cyprus, Egypt, A [Dataset]. http://catalog.ihsn.org/catalog/2375
    Explore at:
    Dataset updated
    Aug 26, 2021
    Dataset authored and provided by
    TIMSS International Study Center
    Time period covered
    2002 - 2003
    Area covered
    Armenia, Botswana, Egypt, Bahrain, Cyprus, Argentina, Bulgaria, Belgium, Chile, Australia
    Description

    Abstract

    To facilitate secondary analyses aimed at improving mathematics and science education, the TIMSS 2003 International Database makes available to researchers, analysts, and other users the data collected and processed by IEA's TIMSS 2003 project. This database comprises student achievement data in mathematics and science as well as student, teacher, school, and curricular background data for the 48 countries that participated in TIMSS 2003 at the eighth grade and 26 countries that participated in TIMSS 2003 at the fourth grade. The database includes data from over 360,000 students, about 25,000 teachers, about 12,000 school principals, and the National Research Coordinators of each country. All participating countries gave the IEA permission to release their national data.

    IEA, the International Association for the Evaluation of Educational Achievement, has been conducting international comparative studies of student achievement in school subjects for more than 40 years. When it collected data for the first time in 1994-95, TIMSS (known then as the Third International Mathematics and Science Study) was the largest and most complex international study of student achievement ever conducted, including both mathematics and science at third, fourth, seventh and eighth grades, and the final year of secondary school. In 1999, TIMSS (by now renamed the Trends in International Mathematics and Science Study) again assessed eighth-grade students in both mathematics and science to measure trends in student achievement since 1995.

    TIMSS 2003, the third data collection in the TIMSS cycle of studies, was administered at the eighth and fourth grades. For countries that participated in previous assessments, TIMSS 2003 provides three-cycle trends at the eighth grade (1995, 1999, 2003) and data over two points in time at the fourth grade (1995 and 2003). In countries new to the study, the 2003 results can help policy makers and practitioners assess their comparative standing and gauge the rigor and effectiveness of their mathematics and science programs.

    Geographic coverage

    The survey had international coverage

    Analysis unit

    Units of analysis in the study include documents, schools and individuals

    Universe

    The study covered curricula and textbooks, teachers and pupils at selected schools in the country

    Kind of data

    Sample survey data [ssd]

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    By gathering information about students’ educational experiences together with their mathematics and science achievement on the TIMSS assessment, it is possible to identify factors or combinations of factors related to high achievement. As in previous assessments, TIMSS in 2003 administered a broad array of questionnaires to collect data on the educational context for student achievement. For TIMSS 2003, a concerted effort was made to streamline and upgrade the questionnaires. The TIMSS 2003 contextual framework (Mullis, et al., 2003) articulated the goals of the questionnaire data collection and laid the foundation for the questionnaire development work.

    Across the two grades and two subjects, TIMSS 2003 involved 11 questionnaires. National Research Coordinators completed four questionnaires. With the assistance of their curriculum experts, they provided detailed information on the organization, emphasis, and content coverage of the mathematics and science curriculum at fourth and eighth grades. The fourth- and eighth-grade students who were tested answered questions pertaining to their attitudes towards mathematics and science, their academic self-concept, classroom activities, home background, and out-of-school activities. The mathematics and science teachers of sampled students responded to questions about teaching emphasis on the topics in the curriculum frameworks, instructional practices, professional training and education, and their views on mathematics and science.

    Separate questionnaires for mathematics and science teachers were administered at the eighth grade, while to refl ect the fact that most younger students are taught all subjects by the same teacher, a single questionnaire was used at the fourth grade. The principals or heads of schools at the fourth and eighth grades responded to questions about school staffi ng and resources, school safety, mathematics and science course offerings, and teacher support.

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NSW Department of Education (2025). Student retention rates at NSW government schools (2014-2023) [Dataset]. https://data.nsw.gov.au/data/dataset/nsw-education-student-retention-rates-nsw-gov-schools
Organization logo

Student retention rates at NSW government schools (2014-2023)

Explore at:
pdf(151686), csv(395), pdf(129474), csv(1021), pdf(173748), pdf(286524), csv(949), pdf(193811), csv(956), csv(230)Available download formats
Dataset updated
Mar 3, 2025
Dataset provided by
NSW Department of Educationhttps://education.nsw.gov.au/
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Area covered
Government of New South Wales, New South Wales
Description

The full-time apparent retention rate (ARR) measures the proportion of a cohort of full-time students that moves from one grade to the next, based on an expected rate of progression of one grade per year. It does not track individual students through their final years of secondary schooling.

Data Notes:

  • The ARR is the ratio of the total number of full-time school students in a designated year (e.g. Year 12 in 2020) divided by the total number of full-time students in a previous year (e.g. Year 7 in 2015). This would be the Year 7 to 12 apparent retention rate in 2020.

  • From 2020, students in mainstream support classes (previously excluded from this data) are reported by their underlying grade of enrolment. As a result, data from 2020 onwards is not directly comparable to previous years. A separate column in the CSV files has been provided to show the 2020 retention rates with both previous and revised counting rules. 2021 retention rates use the revised counting rules.

  • Support students at Schools for specific purposes (SSPs) do not have a designated grade and therefore are not counted in the calculation of ARRs. Support students in mainstream schools have been included in the calculations from 2020 (see above).

  • Reporting on ARRs based on small numbers of students can lead to unreliable ARR estimates. The tables combine ABS SA4 areas to ensure the underlying number of students is sufficiently large to generate reliable estimates.

  • Only full-time students are counted in the calculation of full-time apparent retention. Part-time students are excluded.

  • Students enrolled in distance education classes are included with their appropriate grade levels. Sydney-Inner includes enrolments from Sydney Distance Education High School.

  • ARRs can exceed 100 per cent due to factors including student migration from interstate and overseas and between school sectors.

  • Norfolk Island Central School is not included in the Apparent Retention Rate factsheet, but from 2018 to 2021 was included under NSW Government data in the ABS Schools Australia publication. This can lead to a slight difference in reported figures between Schools Australia and this dataset.

  • Aboriginal and/or Torres Strait Islander students are identified based on responses to the school enrolment form. This information may change throughout an individual’s schooling.

  • Reporting by non-binary gender is not possible due to system limitations.

Data Source:

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