Background Quality Report: Qualifications and Destinations of Northern Ireland School Leavers

Introduction

Context for the quality report.

The Department of Education (DE) adheres to the UK Statistics Authority Code of Practice for Statistics and the National Statistician’s guidance on quality. This document provides a summary of how the Qualifications and Destinations of Northern Ireland School Leavers (School Leavers Survey) Accredited Official Statistics (National Statistics) publications, available via the following link, adhere to the code in terms of quality:

School Leavers Survey (opens in a new window)

Information on the qualifications and destinations of pupils leaving grant-aided post-primary schools in Northern Ireland is collected annually from schools in Northern Ireland. This data collection exercise takes place in October/ November following the end of the academic year and includes all qualifications obtained by the pupil on leaving the school system, along with their main destination.

The main purpose of collecting these data is to create a statistical base to inform a wide range of policy areas aimed at raising standards and tackling underachievement. The data are also used in the development, implementation and monitoring of policies, in particular the literacy and numeracy strategies, school improvement programmes and relevant Departmental milestones. School leavers data also inform the “school leavers attainment gap” indicator (within the Brighter Futures domain) in the Programme for Government 2024-2027 ‘Our Plan: Doing What Matters Most’ (opens in a new window) .

The collection of data is facilitated by C2k, who are responsible for the provision of ICT systems in schools. Each school submits electronic returns to the Department at an individual pupil level. As part of Action Short of Strike (ASOS), 22 schools did not submit their School Leavers Survey returns electronically for 2022/23. Paper returns were submitted.

When the data are returned to the Department, statisticians are responsible for processing and validating this information. This process is the main responsibility of one Assistant Statistician with input from one Deputy Principal Statistician. A detailed statistical report based on final data is usually released in May.

Relevance

The degree to which the statistical product meets user needs in both coverage and content.

Relevant users within DE are consulted annually about what data are collated, including any additional information to be collected or any data that are no longer required. This ensures that data meet the needs of key users. Any additional data items collected through the School Census process are also considered for inclusion in the School Leavers data.

In addition, feedback is welcomed from customers outside DE/ Education Authority (EA) via the feedback section on the DE website. Contact details for the relevant statistician are also provided in our statistical report, should a member of the public wish to offer any feedback directly or request further analysis of data.

A user consultation was carried out in September 2023, to which 9 responses were received. Nearly all respondents found the publication and associated outputs to be useful. A summary of the responses is available here (opens in a new window) .

In liaising and engaging with other users, there are very rarely circumstances where necessary information is not collected. In these situations, consideration is given to collecting the requested data in the future, should it be practical and cost-effective to do so.

Accuracy and Reliability

The proximity between an estimate and the unknown true value.

The coverage of the data is 100%.

As the data collected are from an administrative source and are used for schools’ management information purposes, there is a basis to assume that it is in the schools’ interests that the data supplied are as accurate and reliable as possible. Schools obtain information from parents by means of a data collection form, which is then keyed into the SIMS system administered by C2k. These data follow the pupil throughout their school career and can be amended when necessary. Schools also receive examination results and manually enter the main destination of the school leaver, where this information is made available to them. There is a small percentage of leavers (approximately 2.0%) (opens in a new window) for whom destination information is unavailable. Given that some of these data are input manually, there is a possibility of data entry error. Where possible, validation checks are incorporated in the SIMS module in an attempt to mitigate against common mistakes. However, statisticians will also carry out a detailed validation process including confirming that each individual pupil who presents as leaving with no GCSEs or equivalent qualifications does not, in fact, have these qualifications.

Timeliness and Punctuality

Timeliness refers to the time gap between publication and the reference period. Punctuality refers to the gap between planned and actual publication dates.

Data are requested in November following the end of the academic year. One file contains destination data and pupil characteristics while the other two files contain examination information. Data validation takes place throughout January to April and the publication is prepared, checked and usually released in May. Given the workload to process and thoroughly validate the data to the standard required, there is no scope to release the data any sooner.

As part of Action Short of Strike, 22 schools did not submit their School Leavers Survey returns electronically for 2022/23. Processing and validating the paper returns for these schools led to a delay in the 2022/23 report being published until June 2024.

The 2002/03 data were not released (opens in a new window) as there was an issue with software in schools. This resulted in insufficient available time for the validation of returns.

Accessibility and Clarity

Accessibility is the ease with which users are able to access the data, also reflecting the format in which the data are available and the availability of supporting information. Clarity refers to the quality and sufficiency of the metadata, illustrations and accompanying advice.

Data tables are available both within the publication and as Spreadsheet files. These data tables include commonly used and requested data, examples of which include: qualifications by free school meal entitlement, religion of pupils, special educational needs (SEN) and ethnicity. Previous years’ data are also included on the website, so time series analysis is accessible.

A full review of Special Educational Needs (SEN) categories was undertaken in 2017/18 and consequently a new list of SEN categories and associated descriptors was created. The changes to the categories were implemented from January 2019 and impacted on the 2018/19 data relating to school leavers with SEN as schools transitioned to the new system. Data relating to the qualifications and destinations of school leavers with SEN were, therefore, not available for 2018/19. While data relating to the attainment and destinations of school leavers within the new list of SEN categories are available from 2019/20 onwards they are, however, not comparable with SEN data for previous years. A subsequent change in 2020/21 was made to reduce the number of SEN stages from five to three. Further information on the review of SEN categories can be found here: DE Recording children with special educational needs (opens in a new window)

Key statistics, broken down by various geographies, are also currently available via the NISRA Data Portal. (opens in a new window) Metadata explaining the process and all key terms are included on the site.

If data are not available online, users are invited to request specific data via e-mail. These data requests are routinely answered within 15 working days. All data available are provided, the only exception being any figures deemed sensitive, which are suppressed to avoid the potential identification of individual pupils.

Coherence and Comparability

Coherence is the degree to which data that are derived from different sources or methods, but refer to the same topic, are similar. Comparability is the degree to which data can be compared over time and domain.

All data are obtained directly from schools, thus guaranteeing data coherence.

The variables collected have been largely stable and the methods used to collect the data are the same, so the data are comparable over time.

Awarding Arrangements for GCSE and A-level Qualifications from Summer 2020 to Summer 2023

Due to the COVID-19 pandemic, and in line with the other UK regions, public examinations in Summer 2020 were cancelled (opens in a new window) in Northern Ireland. Results awarded by the Council for the Curriculum, Examinations and Assessment (CCEA) for GCSEs were based solely on the Centre Assessed Grades (CAGs) (opens in a new window) provided by schools and colleges. Results awarded for A-levels were the higher of the CAG or the grade initially awarded (opens in a new window) by CCEA on 13 August 2020.

Similarly, public examinations were subsequently cancelled in Summer 2021 (opens in a new window) and all results awarded by CCEA were based on Centre Determined Grades (CDGs) provided by schools and colleges.

While public examinations went ahead in Summer 2022 (opens in a new window) , various adaptations were put in place by CCEA (opens in a new window) . This offered pupils the option to reduce the number of exams and assessments that they had to sit for the Summer 2022 exam series. The return to pre-pandemic standards was continued by CCEA (opens in a new window) in Summer 2023 and additional support, through the provision of Advance Information, was provided for the majority of qualifications.

Finally, Summer 2024 saw the first full series of CCEA examinations (opens in a new window) following a period of alternative awarding and a stepped return to pre-pandemic arrangements.

Given the alternative methods of awarding grades in 2019/20 and 2020/21, and the various assessment adaptations or other supports in place for 2021/22 and 2022/23, caution should be taken when drawing any conclusions relating to changes in student performance. Year-on-year changes might have been impacted by the different process for awarding qualifications in these years rather than reflect a change in underlying performance.

Related information for England, Scotland, Wales and the Republic of Ireland is not included in the publication as, given the different qualifications systems, methodologies and headline measures, it would not be appropriate to present a direct comparative picture of pupil performance.

Trade-offs between Output Quality Components

Trade-offs are the extent to which different aspects of quality are balanced against each other.

The main trade-off is timeliness against accuracy. As the process is carried out by one Assistant Statistician with input from one Deputy Principal Statistician, there are limited resources available for validation. This results in data usually being available in May.

Accuracy is not compromised to meet these deadlines, particularly because these data are used to monitor progress towards Departmental milestones and inform PfG indicators. A detailed range of validation checks are conducted prior to data being made available, and this list of validation checks is reviewed on an annual basis and is amended depending on user needs and common errors.

Assessment of User Needs and Perceptions

The processes for finding out about users and uses, and their views on the statistical products.

The content of the data collection is defined by the Department’s information needs. The relevance of this is checked each year when key users across DE are consulted for additions and amendments for the following year. DE statisticians also meet several times per year with policy officials, ETI, school principals and other groups of interested officials. An additional forum in which we participate is the C2k Liaison Group which captures formal feedback from C2k help teams (and indirectly schools) about the experiences of schools in providing Census data.

Users of the data are surveyed annually via the NISRA Customer Survey (formerly the NISRA Customer Satisfaction Survey). While it is not possible to break down the results of the survey to users that specifically used qualifications/ destination data, the percentages of positive responses for NISRA as a whole remain high. In addition, there is scope for comments raised in the survey to be fed back to the team that manages the School Leavers dataset with regard to making future improvements.

Users are invited in the statistical reports to provide feedback on the publication and to request further information if required.

Performance, Cost and Respondent Burden

The effectiveness, efficiency and economy of the statistical output.

As the infrastructure to collect the data already exists, and schools need to generate much of this data for their own management information purposes, the annual operational cost is minimal year on year.

The respondent burden was measured via a sample survey of schools making data returns. In 2013/14 it was found that the compliance costs for all schools could be estimated to be approximately £37,000 of school staff time.

Confidentiality, Transparency and Security

The procedures and policy used to ensure sound confidentiality, security and transparent practices.

Given the potentially sensitive nature of the pupil level data collected, confidentiality is of the utmost importance.

Data are transferred securely via a school’s SIMS system to a secure web exchange. The data are downloaded from the web exchange to a secure server, to which only statistical staff have access. After processing, datasets are anonymised so that individual pupils are not identifiable.

Sensitive data relating to individual pupils, or to small numbers of pupils, are not published or released externally. Sensitive data include: religion; ethnicity; free school meal entitlement; special educational needs details; and certain groups of qualifications. For such data, figures that are less than five are generally suppressed, and appropriate figures in a column or row in any table with a total is counter-suppressed to avoid the potential identification of pupils. Consideration is, however, given to balancing the provision of information against the risk of disclosure of sensitive information.