Career goals and investments in education: Experimental evidence from Cambodia

In our intervention, students will go through an “interest exploration tool” on a tablet. This tool is designed to help students discover their personality, and to help them understand which jobs their interests could match with. After the students completed the tool, they participate in an information session about educational paths, which provides detailed information on high schools and vocational training options as well as scholarship possibilities. This information session will be conducted in small groups.

IMPORTANT NOTICE: Our intervention had to be interrupted on March 16, 2020, because schools were closed until further notice in Cambodia due to the COVID-19 crisis. The details below reflect the changes we made to the project since then. The original research plan is outlined in the pre-analysis plan from February 5, 2020.

The interest exploration tool is an electronic application that has been designed by the project team together with a Cambodian consultant. It is based on the preference assessment test developed by the National Employment Agency (NEA) of Cambodia, as well as on internationally used personality tests (mainly RIASEC). The application takes approximately 90 minutes. At the end of the tool, students will be revealed their personality type, as well as shown a list of 18 jobs (with description of typical tasks and required educational degree), ordered by their strongest type.

2020-02-17

2020-04-30

Primary outcomes will be (i) partcipation in the final exam, (ii) final-exam scores, and (iii) transition to high school.

The school closure due to the COVID-19 crisis forced us to modify our research plan. Because schools are to remain closed for the rest of the school year, we can only collect individual-level administrative information on participation in the final exam, final exam scores and high school transition.

The final exam is a standardized exam across all schools in Cambodia. The records of each student’s performance in this exams are kept by the teacher. These scores will be standardized for the purspose of our analysis. Students will be classified as drop-outs if they do not participate in the final exam. Finally, as soon as the new school year starts, the project team will collect information regarding high school transition from the high schools in the area (i.e. did student i enroll in that particular institution).

Secondary outcomes are, (i) participation in learning activities during July - August, (ii) stated educational aspirations, and (iii) stated career goals.

These outcomes will be collected via phone surveys (starting on July 6, 2020) with students from treatment and control schools. Educational aspirations are measured as the highest degree the student wishes to attain (categorical answer). Career goals are measured by open ended questions about the most preferred jobs the student wishes to do at age 25 (open ended). We will categorize a career goal as ambitious if it goes beyond the typical reference window of students of the same age-group and area.

We target students from grade 9 in Northwest Cambodia. We construct a sample of 60 lower secondary schools from which we randomly select 50% for our intervention. We then randomly select one class of grade 9 to participate in the intervention (treatment schools), or to have only their students' data collected (control schools). Within these ‘treatment’ schools, we then invite all students of the selected class to participate in a workshop carried out at their school. All students that are willing to participate are randomly allocated into one of three arms: a) full-treatment group (40%), b) placebo-treatment group (40%), c) information-only group (20%). Students in the control schools serve as controls.

By March 16, 2020, the day of school closure until further notice in Cambodia, we had visited (and conducted our intervention in) 18 of the 30 treatment schools. This leaves us with a sample of 785 treated students, and roughly 1,800 control students. The experimental control group comprises 19 control schools that are located in the same district as the 18 intervention schools (our original randomization was stratified at the district level). The non-experimental control group comprises all original treatment schools that were not visited (12), and the control schools from those districts (11).

The school sample consists of 49 pre-selected schools that are cooperating with Child’s Dream, one of our partner NGOs. These schools are distributed across four provinces: Banteay Meanchey, Battambang, Oddar Meanchey, and Siem Reap, provinces that experience particularly high drop-out rates. We exclude schools with less than 30 students in grade 9 (which drops 10 schools). To increase power, we additionally sample 23 lower secondary schools from other districts in the same provinces that are similar in characteristics to the partner schools of Child’s Dream. Of these schools, we randomly select 2 schools to serve as back-up, the remaining 21 schools are included in the main sample. We stratify schools by size (more or less than 100 students in grade 9), by Child’s Dream partnership, and by district, and randomly select half of the schools to participate in our intervention.
There are three treatment arms within treatment schools, and a pure control group in control schools. In addition to the main intervention (treatment group), we designed a placebo intervention for the placebo-treatment group that is similar in structure and design to the IET, but asks students about gender attitudes and about climate change awareness. We also hold the level of job-related information that students receive constant by providing the job details also to the placebo group, the only difference being that the job-related information is not personalized but generic. In addition to the treatment and placebo arms, we also have an information-only arm. This arm is included to assess the possibility that the entire effect might be driven by giving students access to (new) job-related information. Students in the information-only group complete the survey on the tablets, but otherwise only participate in the information session. While the students from the treatment and placebo arms work through the app, students in the control group play a game outside.

The assignment into treatment arms is done randomly in a two-stage process. First all sample schools will be randomly allocated to treatment schools (50%) or control schools (50%). Randomization will be done by computer.
Students within selected classes in treatment schools will then randomly be allocated to one of three treatment arms before the intervention begins (on the same day). Randomization will be done by having students blindly draw numbered badges from a bag.

School and individual

Yes

60 schools

2,700 students

The sample size consists of a) 785 students in treatment schools (all three arms) visited by March 6, 2020, b) 820 students in the experimental control group, c) 990 students in the non-experimental control group.

We calculate the smallest real effect sizes that we can detect at a 5% significance level with 80% power. We perform the calculation based on 18 treatment and 19 control schools with approximately 43 students per cluster. When calculating the minimum detectable effect size (MDE), we take into account that we have baseline information on student age, gender, grades, attendance and class size. We expect that these baseline characteristics can explain between 20% and 50% of the variation in the outcome variable. We further assume that the intra-cluster correlation coefficient (ICC) ranges between 0.1 and 0.3 depending on the variable considered. Depending on the ICC and explained variance, the MDEs range between 0.23 of a SD and 0.46 of a SD. These are the detectable effect sizes for outcomes with mean zero and a standard deviation of one (such as standardized grades).

Students in low-income contexts often lack guidance in their career decisions which can lead to a misallocation of educational investments. We report on a randomized field experiment conducted with 1715 students in rural Cambodia and show that a half-day workshop designed to support adolescents in developing occupational aspirations increased educational investments. We document substantial heterogeneity in treatment effects by baseline student performance. While the workshop increased schooling efforts of high-performing students, treated low-performing students reduced their educational investments. We develop a simple model that explains why an information intervention can affect educational aspirations and investments in opposing directions.

Gehrke, Esther and Lenel, Friederike and Schupp, Claudia, Occupational Aspirations and Investments in Education: Experimental Evidence from Cambodia (2023). CESifo Working Paper No. 10608

http://dx.doi.org/10.2139/ssrn.4553149