Factors affecting university application decisions

The intervention will involve providing secondary school students in the UK with information, mentorship, and subsidized in-person visits to universities, with the treatment arms varying the content and nature of each.

Low-income students in the UK “undermatch”, attending lower-ranked universities despite good academic credentials and uniform tuition fees. This project looks into whether and how social exposure to individuals who attend high-ranked universities shapes university aspirations. Using administrative data, we document that school-to-university pipelines are persistent and dense; on average, 32% of students attend the modal university attended by students in the prior cohort at their school. These effects are more pronounced in economically disadvantaged schools, where students who attend pipeline universities are also more likely to undermatch. Additionally, students are more likely to attend a university their schoolmates have historically attended, even when they have offers from higher-ranked universities. In light of these patterns, we propose learning about university opportunities through schoolmates as one driver of undermatching. To obtain causal evidence and disentangle mechanisms of this type of social learning, we will run an RCT on ~2,000 students in the UK applying to university. Mechanisms we will test include the effectiveness of social exposure compared to standard information interventions, whether students respond more to information from individuals who are demographically similar, and the importance of coordination within friend groups.

The intervention will involve in-person workshops in secondary schools in the UK providing information about the university application process to participants, video clip anecdotes from current university students, matching participants with current university student mentors to discuss life at university and the application process, and subsidized in-person visits to universities. Our treatment arms will vary whether students see videos, are matched to mentors, and are subsidised for visits. The target population is Year 12 and/or Year 13 secondary school students in the UK in the year before they apply to university (typically January of Year 13). We plan on conducting the intervention in multiple waves in order to maximize the number of schools that can be included in the study. The first wave will take place in October through November 2024, and the second wave will take place between April through July 2025.

2024-10-01

2026-01-01

Short-run outcomes (collected at midline and endline surveys):
- Interest in mentorship / further exposure to researcher-assigned universities*
- Stated interest in applying to researcher-assigned universities*

Long-run outcomes (collected by schools after university applications are submitted):
- Applications / attendance to researcher-assigned universities*
- Applications / attendance to mentor's university
- Applications / attendance to university with subsidized visit

*Note: researcher-assigned universities are sets of universities that are suitable for the student based on their grade profiles (universities to which students with similar grades have attended based on national data). Researcher-assigned universities will exclude universities already familiar to the students such as the universities their parents and/or siblings have attended as well as universities that are commonly attended by students at their school.

We will look into heterogeneity of treatment effects on the primary outcomes by demographic similarity between participating students and mentors (where demographics include socioeconomic status, ethnicity, gender, and location). For instance, we will examine whether female students matched with female mentors were more likely to apply to their mentor's university compared to female students matched to male mentors.

The experimental design consists of two treatment arms and a control group with randomization at the individual student level. All students will complete baseline, midline, and endline surveys before and after the intervention.

The intervention will be randomized at the student level and consist of two treatment arms and an active control group. All participating students will attend in-person workshops led by school alumni, teachers, or other university or school-adjacent professionals and fill out a baseline survey ahead of the workshops about their university aspirations, and a midline survey at the end of the workshop. Based on their responses to the baseline survey as well as their demographics and academic records, participating students will be assigned to an “academic cell” - a set of universities and majors that they are academically well-matched to. The midline survey will ask students to state universities for which they would like mentors. After students in T1 and T2 have conducted their mentorship calls, students in C, T1, and T2 will be asked to fill out an endline survey asking which university they would like a subsidized visit to.
Students in the active control group C will attend an in-person workshop that includes generic information and application tips such as information about the university application process in the UK, timelines, and personal statement advice, as well as national and school-specific statistics on applications and universities. Students in treatment arm T1 will attend the same workshop and similarly take baseline, midline and endline surveys. During the baseline survey, they will be shown videos of students from the same academic cell discussing their experiences applying to and attending university. After the workshop and midline survey, students in arm T1 will also be matched with mentors at universities that they list in the midline survey, and will have at least one call with their mentors. In treatment arm T2, students attend the workshop and receive videos, and mentors, but will also be offered a reimbursement for travel costs to visit a university of their choice in person, subsidising their visit.

Randomization will be conducted on a computer. Within each participating school, we will receive a list of participating students, and then randomly assign students from this list to either the control arm C, treatment T1, or treatment T2.

Individual, stratified by school

No

As the randomization is at the individual level, the number of clusters at the unit of randomization level is the same as the number of individuals. However, we will be sampling particular schools, and our central estimate is that we will recruit 20 schools.

Our central estimate is that we will have a sample size of 2000 individuals, but we may get fewer or more as we are still in the process of recruiting schools to the study. We present MDEs as a function of sample size below to give a sense of how power will depend on the sample size.

Given budgetary constraints, we plan to assign 100 students to treatment arm T2, 400 to arm T1, and the remainder to arm C. Under our central estimate of 2000 students, we will thus have 1500 students in arm C.

Our primary outcomes are all binary / probability outcomes, so for power calculations we use the standard formula for the variance of a proportion. The minimum detectable effect size then depends on the baseline probability of the outcome and the sample size in each arm. We have limited information about the baseline probabilities for most primary outcomes, but we expect many to fall between 0.05 and 0.2. Below we present power under baseline probabilities of 0.05, 0.1, and 0.2. We assume assignment of 1500 students to C, 400 to T1, and 100 to T2, as in our central estimate for sample size described above. For comparisons of arm T1 against C, we have the following MDEs: Baseline 0.05: 3.4 pp Baseline 0.1: 4.7 pp Baseline 0.2: 6.3 pp For comparisons of arm T2 against C, we have the following MDEs: Baseline 0.05: 6.3 pp Baseline 0.1: 8.7 pp Baseline 0.2: 11.6 pp