About This Project
In the UK, students specialise in particular subjects at a relatively early stage in their education, and this may mean that early decisions can close off careers in which they might have been productive. We plan to study people's choices along the pipeline to mathematical careers, and study at what stage different groups tend to be discouraged from participating, using data on GCSE exams, A-Level exams, and university applications, as well as surveys of secondary school students in the UK.
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What is the context of this research?
Mathematical skills are the foundation of many privately and socially beneficial careers, but finding a career that uses these skills requires students to make the right decisions during their secondary and tertiary education to fully realise their talents. In the UK, this involves pursuing mathematical subjects in A-Level exams, applying to universities that will best nurture their talent, and selecting mathematical majors. These decisions have high stakes, but students make them based on limited information and potentially subject to biases that may lead them not to make the best decisions for themselves. These forces may contribute to gaps on dimensions such as gender in mathematical participation.
What is the significance of this project?
The UK provides a useful environment to study the development of mathematical talent, and the role that students' choices play in the pipeline to mathematical careers. We will be able to develop a coherent picture of students' educational choices between taking GCSE exams, when students have not specialised between subjects, and age 18, where they will have chosen a university course to attend. We will observe and be able to disentangle a large number of potential determinants of these decisions with a combination of administrative data, surveys, and quasi-experimental variation. This will provide new, more comprehensive evidence on the extent to which students are making decisions that allow them to best fulfill their mathematical potential, and what drives their decisions.
What are the goals of the project?
The project has three specific components.
First, we will use the administrative data on university applications in the UK to describe the points at which different groups tend to stop studying mathematics, and predict some of the drivers of choice.
Second, we will use the removal of AS-Levels in England as a natural experiment to study how removal of information about students' math performance affects selection into applications for mathematical courses and university.
Third, we plan to work with two educational non-profits, Women in Science and Engineering (WISE) and Causeway Education, to work directly with a few secondary schools to survey students about their university application choices and randomise the provision of information about courses to students.
Our project requires us to spend an extended period of time in the UK for two reasons. First, the administrative data on university applications in the UK can only be accessed from Safe Rooms physically in the UK, so all our analysis of this dataset needs to be conducted in the UK. Second, we will need to be present in the UK to discuss the implementation of our survey of university applicants with schools and our non-profit partners. We thus need some funding for accommodation and travel in the UK. We have additional funding from an internal MIT department fund, but this funding is limited and will not fully cover our expenses.
We plan to work in parallel on the design and implementation of our survey and the analysis of our administrative dataset over the summer and autumn of 2023. The dissemination of the survey will need to be planned around school terms in the UK as we will be distributing the survey through schools. While in the UK, we will also work on analysing the administrative data for the first and second components of our project.
Jun 12, 2023
Jun 13, 2023
Travel to the UK and begin working with administrative data
Jun 25, 2023
Specify design of survey of students
Jul 21, 2023
Field first wave of student survey
Aug 18, 2023
Complete analysis of administrative data
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