Student attendance rate by SA4 (2011-2024)

This data set shows the average attendance rate for students in NSW government schools by Statistical Area 4 (SA4).

Data notes

• 2021 data is not comparable to previous years due to the continued effects of the COVID-19 pandemic, changes to calculation rules to align with ACARA’s national standards (version 3) and changes to the way attendance data is transferred into the department’s centralised data warehouse. Please refer to 2021 Semester 1 student attendance factsheet for more information.

• 2020 data is not provided because students were encouraged to learn from home for several weeks in Semester 1. Please refer to the factsheet on The effects of COVID-19 on attendance during Semester 1 2020 for more information.

• In 2018 NSW government schools implemented the national standards for student attendance data reporting. This resulted in a fall in attendance rates for most schools due to the inclusion of part day absences and accounting for student mobility in the calculation. Data from 2018 onwards is not comparable with earlier years.

• Schools for Specific Purposes (SSPs) are only included from 2021. Prior to this SSP attendance data was not collected centrally.

• The attendance rate is defined as the number of actual full-time equivalent student days attended by full-time students in Years 1–10 as a percentage of the total number of possible student-days attended in Semester 1. Figures are aligned with the National Report on Schooling and the My School website.

• SA4 refers to the ABS Australian Statistical Geography Standard (ASGS) Edition 3 Statistical Area 4 (SA4) – 2021.

• ‘Other Territories’ has been assigned to Norfolk Island Central School, which operated under the responsibility of NSW Department of Education between 2018-2021.

Data source

Semester 1 Return of Absences Collection

Data quality statement

The Attendance Data Quality Statement addresses the quality of the Attendance dataset using the dimensions outlined in the NSW Department of Education's data quality management framework: institutional environment, relevance, timeliness, accuracy, coherence, interpretability and accessibility. It provides an overview of the dataset's quality and highlights any known data quality issues.