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Career goals and investments in education: Experimental evidence from Cambodia
Initial registration date
February 16, 2020
July 04, 2020 2:06 PM EDT
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Wageningen University and Research
Other Primary Investigator(s)
University of Hannover
University of Goettingen
Additional Trial Information
In this project, we analyze whether an interest exploration tool – combined with information about potential careers, paths to higher education and financing options – can provide guidance to students in rural Cambodia, help them to develop long-term career goals and thereby motivate them to continue in school. We target the intervention to adolescents in grade 9, who are about to decide whether to enroll in high school. We use survey data, as well as individual-level administrative data obtained from treatment and control schools to track educational decisions.
Gehrke, Esther, Friederike Lenel and Claudia Schupp. 2020. "Career goals and investments in education: Experimental evidence from Cambodia." AEA RCT Registry. July 04.
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.
Intervention Start Date
Intervention End Date
Primary Outcomes (end points)
Primary outcomes will be (i) partcipation in the final exam, (ii) final-exam scores, and (iii) transition to high school.
Primary Outcomes (explanation)
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 (end points)
Secondary outcomes are, (i) participation in learning activities during July - August, (ii) stated educational aspirations, and (iii) stated career goals.
Secondary Outcomes (explanation)
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).
Experimental Design Details
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
Was the treatment clustered?
Sample size: planned number of clusters
Sample size: planned number of observations
Sample size (or number of clusters) by treatment arms
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.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
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).
INSTITUTIONAL REVIEW BOARDS (IRBs)
Social Sciences Ethics Committee, Wageningen University & Research
IRB Approval Date
Ethics committee of the University of Goettingen
IRB Approval Date