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Improving the Mathematics Pipeline

Project information

Aims

This project has two broad aims.

Firstly, it will investigate patterns of excellence and engagement throughout mathematics education in England, from the start of school through to postgraduate study and research. Many aspects of the mathematics pipeline are of research interest, though not all of them are as amenable to influence. The first major ‘leak’ is at 16, from GCSE to A level. Much has been written about this and several policy initiatives have aimed to retain more post-16 students in mathematical study. Yet, research also shows that many young people have been effectively filtered out of the excellence pipeline well before the age of 16, so understanding the long-term pipeline dynamics is important. Not only are the key choice moments at 16, 18, 21 and others important, but so too is what happens within the phases of education that frame those later choices.  

Developing insights on the nature of the mathematics pipeline is, however, only one side of the problem. The second aim of the project is therefore to investigate the opportunities for, limitations on, and potential impact of interventions to enhance access to mathematical excellence in the pipeline. Short, sharp interventions (such as scholarships) might have considerable impact upon those who benefit from them, but they are unlikely to change the system as a whole. Interventions aimed at changing the system run the risk of being diluted by, and/or entangled with, other initiatives so any change in mathematics pathlines are difficult to discern at scale or attribute cause. The project aims to develop a framework for understanding the affordance and constraints of various intervention options.  

Objectives and methods

The research sets out to answer two key questions posed by the funder:

• What does the maths pipeline actually look like?
• What are highest potential opportunities to improve efficiency in the pipeline? 

In order to answer these questions the project has four broad objectives: 

1. Undertake a thorough – potentially systematic - review of:
   a) research and grey literatures
   b) relevant national and local policy initiatives and interventions
2. Undertake secondary data analysis of:
   a) 5-18 mathematics progress, participation and outcomes
   b) undergraduate mathematics choices, progress and transition to postgraduate study and research
3. run a series of stakeholder interviews to explore mathematics pipeline challenges, strategies and interventions opportunities
4. scope potential interventions for enhancing (access to) mathematical excellence pathways

The secondary data analysis comprises four phases/points:

1. Primary-secondary (7/11-16): to understand filtering from Key Stages 1/2-4
2. Upper secondary (A level): to understand selection at 16 and outcomes at 18
3. Undergraduate (UG): to understand entry filtering, cohort structure and outcomes
4. Postgraduate (PG): to understand entry filtering and cohort composition  

The 7-18 phase analysis (1/2) will be based on analysis on the National Pupil Database (NPD) whilst the HE phases analysis (3/4) will be based on analysis of a Higher Education Statistics Agency (HESA) dataset linked to prior NPD data. The research will also investigate whether the Millennium Cohort Study offers complementary insights into students’ progression through the mathematics pipeline.   

The stakeholder interviews will explore how current and past interventions designed to increase access and engagement and raise attainment in mathematics worked, or did not work in practice, in order to inform the design of future developments. These will be semi-structured interviews adapted to the specific experience and position of the interviewees.   

The ultimate goal of the project is to identity areas for future investment - either scaling up existing interventions or designing new ones - which will enhance mathematical excellence and increase access to excellence pathways for students from disadvantaged backgrounds. The secondary data analysis will be used to help identify promising educational interventions, phases and places which might yield the greatest impact. It will also provide baseline analysis for the future impact evaluation of any such initiatives.