Subject choice in post-16 education: a breakdown by student characteristics

This dashboard offers insights into how certain demographic and socio-economic factors are related to the take-up of subjects in post-16 education in the English educational system.

This tool highlights long-term trends and facilitates a granular examination of choices across the following student characteristics: gender, ethnicity, eligibility for free school meals (FSM), Income Deprivation Affecting Children Index (IDACI), Special Educational Needs and Disabilities (SEND) and English as an additional language (EAL) status. Designed as a tool for exploratory and descriptive analysis, it is important to note that although this dashboard offers valuable context, it does not make assertions on causality.

The data used for this dashboard is taken from work by the National Foundation for Educational Research, commissioned by the British Academy, that led to the report 'Subject choice trends in post-16 education in England' which aimed to better understand how patterns of subject choice and subject combinations at Level 3 in England have changed over the past two decades. This dashboard complements the report by providing more detailed data focused on student characteristics and a broader list of subjects.

Both pages of this dashboard present data using a stacked bar chart. This visualisation illustrates the proportion of students choosing the specified subject, broken down by the selected characteristic for each academic year. It is important to clarify that the 100 per cent scale in each bar represents the total number of students who opted for that subject, rather than the entire student population.

Before using the dashboard, we strongly encourage users to read the sections below for important details on data sources, limitations, and guidance on effectively interpreting the dashboard.

The dashboard allows the user to observe differences in subject uptake across different demographics and student characteristics. This data provides a valuable foundation for understanding factual differences across various groups and serves as an important starting point for deeper exploration, including the examination of educational inequalities.

The British Academy acknowledges that the use of certain labels can be limiting and may not fully encompass the richness and diversity of all identities and experiences. However, due to the nature of data analysis and the necessary methodological approach, the definitions and classifications of student characteristics in this dashboard are directly derived from the Spring Census in the National Pupil Database (NPD).

Here is an overview of the characteristics featured in the dashboard:

• Personal and educational characteristics: the dashboard includes ethnicity, gender and Special Educational Needs and Disabilities (SEND) to highlight patterns in subject take-up across diverse identity and support needs.
• Socio-economic and linguistic factors: the dashboard includes eligibility for Free School Meals (FSM), Income Deprivation Affecting Children Index (IDACI) and English as an Additional Language (EAL). These indicators are proxies for economic disadvantage and linguistic diversity that provide context on students' academic and social environments.

This dashboard complements the original report by providing a detailed exploration of all available subjects, as detailed in the Technical Appendix (section 2.3 Typology of subjects). Each subject is presented independently, so users can analyse trends at both an individual subject level and major subject categories.

However, it's important to note that some subjects, like 'Arts', are broken down by qualification type (e.g., A-levels and Other L3s) but do not add up to the aggregate Arts category. This aggregate represents broader subject participation across all Level 3 qualifications, while specific breakdowns focus on either 'A levels' or 'Other L3s'. Thus, a major category like 'Arts' is not necessarily the aggregation of its subcategories (e.g., 'Arts A-level' and 'Arts Level 3 vocational'). Instead, 'Arts' represents a distinct grouping of students who have chosen at least one qualification within this subject area.

This difference in the aggregation is explained by how the data sources are designed and managed, which is outlined in the Technical Appendix of the original report. First, we are working with the National Pupil Database (NPD) and Individualised Learner Record (ILR) which record academic qualifications (such as A-levels and vocational qualifications) in different ways. At the same time, students with incomplete data for certain characteristics are excluded from specific descriptive analyses, but they may still appear in other parts of the analysis, and this can lead to slight variations in the reported counts. Additionally, some students take a mix of A-levels and vocational Level 3 qualifications. For instance, following the previous example, a student enrolled in both A-level Art and a vocational Design course will appear in the breakdowns for both A-level Arts and Other L3 Arts. However, within the overall 'Arts' aggregate, the student is counted only once to ensure their participation in the subject area is accurately represented without duplication.

To interpret the data accurately, it is important to keep in mind the following:

• Data interpretation: both pages of this dashboard feature data displayed in a stacked bar chart. This chart displays the percentage of students selecting the chosen subject, segmented by the selected characteristic, for each academic year. It is important to note that the 100 per cent for each bar refers to the total number of students who selected a particular subject, not the entire student population. For example, when analysing the 2007/08 in the first page, and if selecting 'Arts' as the subject filter, and EAL as the student characteristic, the correct interpretation would be: 7.6 per cent of the students who chose Arts had EAL status, while the remaining 92.4 per cent of students did not have EAL status.
• Representation of student characteristics: during the analysis period, there have been changes in the way some characteristics are measured or labelled, for example the identification criteria for Special Educational Needs and Disabilities (SEND). For further details, please refer to the Technical Appendix (Table 1).
• IDACI quintiles: The Income Deprivation Affecting Children Index (IDACI) measures the proportion of children under the age of 16 living in low-income households within a particular area in England. It is divided into five quintiles: a higher percentage in the first quintile would suggest that a larger share of students taking a specific subject come from more deprived backgrounds, whereas a higher percentage in the fifth quintile would indicate greater participation from less deprived areas. This measure is useful because it provides insights to better understand the relationship between socioeconomic status and student participation in subject uptake.
• Data inconsistencies: over the 20 years considered in this dashboard, some subjects and qualifications have undergone renaming, reclassification, or discontinuation, which may influence the continuity of the data; so, users should consider these alterations while interpreting the longitudinal trends.
• Context of data changes: the dashboard shows data during specific periods but in itself can’t explicitly account for broader temporal shifts or the impact of significant policy changes (reforms to A-levels or the COVID-19 pandemic), yet its content provides insights to encourage further analysis as they likely played a significant role in shaping these trends.
• Broad aggregations: as mentioned above, the student characteristics employed for this dashboard stem directly from available data, but it's important to recognize that aggregated groupings in, for example, ethnicity (such as 'Asian' or 'Mixed') can simplify complex identities and inequalities within these groups. Similarly, gender data presented in a binary format and metrics like eligibility for Free School Meals (FSM) may not fully capture the nuanced identities and contexts of students.
• Detailed data available: the work conducted by the National Foundation for Educational Research, commissioned by the British Academy, involved providing detailed data in Excel format that enhances the report's analysis, including the database used for this dashboard.