Closing Gaps in Educational Trajectories: Building School Capacity to Support Students in the Transition to Higher Education

The randomized controlled trial assigns participating high school networks into three experimental groups. All students in the study—regardless of group—receive an information package with key resources to support informed decision-making about higher education. Beyond this common component, two groups receive additional interventions aimed at strengthening students’ post-secondary planning.
In the first treatment group, a subset of students in each class receives personalized support through small-group mentoring sessions led by trained counselors. These sessions focus on helping students explore their post-secondary options, understand the application and financial aid systems, and make informed choices about their future.

In the second treatment group, teachers and school staff receive structured training delivered by external facilitators. After completing the training, educators implement a classroom-based intervention, reaching all students in the class with similar content to that provided in the mentoring program. This design allows us to evaluate whether training school staff can serve as a cost-effective and scalable alternative to personalized mentoring.

The third group serves as the control group and only receives the information package. By comparing outcomes across the three groups, we can assess the added value of both personalized mentoring and school-based delivery, relative to providing information alone.

The RCT will randomly assign one-third of the high school networks to the control group, which receives an information package; one-third to a treatment group that receives both an information package and personalized mentoring; and one-third to a treatment group where teachers and school counselors receive training and subsequently deliver a five-session intervention to their students. All interventions are focused on high school senior students enrolled in schools that offer a vocational track. All the students enrolled in treated and control schools will receive an information package either addressed to their homes when possible or sent through their schools when the address is not available/unreachable by the postal service (e.g. rural addresses). The package will provide information on three central aspects:

(1) Funding opportunities.
(2) Important variables to consider when choosing higher education programs.
(3) Steps they need to follow to apply for funding and to higher education.

Since all the students in our sample come from relatively disadvantaged settings, all of them are eligible for public funding. Thus, the information package will highlight the fact that, if they decide to enroll in higher education, they will receive generous support from the government.

The information package will also provide statistics on the benefits of attending higher education in terms of employment and earnings. However, considering that employment and wages greatly depend on the quality of the match between student and major-institution, the information package will also highlight the heterogeneity that exists in these variables across different fields and institutions. Students will be provided with links to official sources that offer tools to compare programs and institutions along with different variables including the labor market performance of recent graduates.

Finally, the information package will contain information on applications to funding and to higher education. The material will stress important deadlines and the requirements to apply to different types of funding and institutions. As in the previous case, it will also direct students to official sources providing additional details.

The package will contain three information pieces. First, an informative brochure that will contain the same information for everyone. Second, a calendar highlighting important deadlines and providing some guidelines to students who want to apply to higher education. Finally, a personalized letter that will reinforce the information in the package, customized based on typical higher education trajectories followed by students in that high school in previous years. Customization will focus on the Labor market outcomes in the four areas of study in which students from their same high school (in previous years) were more interested.

On top of the information package, 6 students of each last-year class in high schools allocated to the second treatment group will receive additional support from mentors. Mentors will be psychologists and school counselors who will contact the selected group of students 9 times between August and December. Each contact will have a specific goal in mind, but the general idea is to discuss with students their plans after completing high school. Apart from providing information about higher education opportunities, mentors will be available to answer any questions that students may have about different aspects of higher education (e.g., applications, funding and admissions requirements, important deadlines, variables to consider when deciding whether to enroll and where to enroll in higher education, etc). All the information provided by mentors will come from official sources. Finally, mentors will have 5 sessions with groups of 6 students, to cover topics like deciding what to do after high school and navigating the financial aid and application system. All session will be conducted in person. To make sure that mentoring affects students through either mentor interaction or peer interactions, we will make sure that mentors do not interact with other students in their school's visits and that mentorship materials are not shared with the school or other students.
In the second treatment group, teachers receive specialized training before delivering the mentoring sessions to students. The training equips them with key information about the benefits of higher education, available financial aid, and the application process. After completing the training, teachers conduct a five-session intervention in their classrooms, guiding students through the same topics covered in the personalized mentoring program. The sessions are conducted during the study program orientation block and are taught to all students in the class. This approach allows us to assess whether training educators can replicate the effects of one-on-one mentoring in a more scalable and cost-effective manner.

Finally, students in the control group will receive the information package but not the mentorship program. However, like the rest of the students in our project, they will answer an entry and exit survey.

2024-03-11

2025-12-19

1. Applies to funding for higher education.
2. Takes the university admission exam.
3. Applies to university
4. Enrolls in higher education:
- University
- Professional Institute
- Vocational Training Center

All the primary outcomes will be directly collected from administrative data.

- Understanding of the financial aid system (see next point for additional details).
- Understanding of the higher education system (see next point for additional details).

To assess students’ understanding of the higher education and financial aid systems, we will administer surveys that include a knowledge test covering the key areas described above. The test will include objective questions on topics such as eligibility criteria for financial aid, application deadlines, and other characteristics of the funding programs for which they are eligible.

We will examine the proportion of correct responses across treatment and control groups for each item, allowing for an item-level comparison of knowledge acquisition. In addition, we will construct a composite knowledge index using the first principal component of a principal component analysis (PCA) on all test items. This index will capture the underlying variation in overall knowledge across students and provide a continuous measure for impact estimation.

The RCT will randomly assign one-third of the high school networks to the control group, which receives an information package; one-third to a treatment group that receives both an information package and personalized mentoring; and one-third to a treatment group that receives an information package and where teachers receive training before delivering a five-session mentoring intervention to the entire class during study program orientation sessions. The treatments aim to affect the understanding that senior high school students have of their higher education opportunities. Additionally, they seek to evaluate whether training teachers and school counselors can replicate the positive effects of personalized mentoring in a cost-effective and scalable manner. Randomization will be done in an office by a computer. Schools in the control group will not receive any additional intervention. Senior students enrolled in schools in any of the treated or control groups will receive an information package. In addition, 6 randomly chosen students per class in the first treatment group will receive, on top of the information package, a personalized mentorship program. In the second treatment group, teachers will receive training and then conduct a five-session mentoring intervention for the entire class during study program orientation sessions. The effects of the mentorship program will be measured on both mentored students and on their classmates. Randomly assigning students will allow us to test for spillover effects and if there is any heterogeneity in these spillovers.

The RCT will randomly assign one-third of the high school networks to the control group, which receives an information package; one-third to a treatment group that receives both an information package and personalized mentoring; and one-third to a treatment group that receives an information package and where teachers receive training before delivering a five-session mentoring intervention to the entire class during study program orientation sessions. The treatments aim to affect the understanding that senior high school students have of their higher education opportunities and, consequently, their aspirations and post-secondary education trajectories. Additionally, they seek to evaluate whether training teachers and school counselors can replicate the positive effects of personalized mentoring in a cost-effective and scalable manner. Randomization will be done in an office by a computer. Schools in the control group will not receive any additional intervention. Senior students enrolled in schools in any of the treated or control groups will receive an information package. In addition, 6 randomly chosen students per class in the first treatment group will receive, on top of the information package, a personalized mentorship program. In the second treatment group, teachers will receive training and then conduct a five-session mentoring intervention for the entire class during study program orientation sessions. The effects of the mentorship program will be measured on both mentored students and on their classmates. Randomly assigning students will allow us to test for spillover effects and if there is any heterogeneity in these spillovers.

Randomization done in the office by a computer.

School network

Yes

181 schools

14,000 senior high school students

- Information only (control): 71 schools (personalized information sent to all senior students).
- Information and mentoring program (branch 1): 56 schools (personalized information sent to all senior students and mentorship program allocated to highly connected individuals within each class).
- Information and Teacher-Guided Sessions (branch 2): 54 schools (personalized information sent to all senior students and a mentoring program delivered by trained teachers to the entire class).

Unfortunately, we do not have complete information to make accurate power calculations for our outcomes measuring how well students understand their funding and higher education opportunities at the moment. The best we can do is to rely on figures reported by previous studies in Chile. We base the following power analyses on the results of Hastings et al. (2016). The survey used in this paper was applied to students registered for the university admission exam (PSU) who accepted an email invitation to answer it. Our study focuses on schools in which an important share of the students do not even register for the PSU. Even those who take the PSU perform well below those in the sample of Hastings et al. (2016). For instance, while the average score of students in Hastings et al. (2016) was 539, the average performance of students from schools in our sample in 2018 was 439 (this is a difference of approximately 1SD). Since we focus on students from particularly disadvantaged settings, their knowledge of the system is likely to be lower than the one in Hastings et al. (2016). Having these caveats in mind, we can assume an error in the expected earnings Benchmark of between 0.43 to 0.50. Assuming an intercluster correlation of 0.044, these figures imply we would be able to identify effects above 0.065 at a significance level of 5% and with a power of 80%. When studying the effect of the teacher-guided sessions, then the minimum detectable effect is 0.057. Below, a list of binary outcomes that we will study, their means in previous cohorts of schools in our sample, and the minimum detectable effect in percentage points (power 80%, significance 95%). All the outcomes are measured at the individual level, and since they are reported in administrative records, we can use previous cohorts to make very precise power calculations. 1. Mentorship intervention: • Application to funding: 76% (mean), 5.29 pp (MDE). • Registration in university admission exam: 83.5% (mean), 5.99 pp (MDE). • Enrollment in higher education: 48% (mean), 5.71 pp (MDE). • Enrollment in university: 22% (mean), 5.85 pp (MDE) 2. Teacher-guided sessions (Individuals who receive mentorship delivered to the entire class by the teacher.): • Application to funding: 76% (mean), 4.61 pp (MDE). • Registration in university admission exam: 83.5% (mean), 5.64 pp (MDE). • Enrollment in higher education: 48% (mean), 4.73 pp (MDE). • Enrollment in university: 22% (mean), 5.18 pp (MDE)