Author: Shahriar Kibriya, Benjamin Tkach, Jaehyun Ahn, Natalia Valdez Gonzalez, Zhicheng Xu, and Yu Zhang
Year: 2016
Agency: USAID
Full Citation: Kibriya, S. et al. (2016). The effects of school-related gender-based violence on academic performance: Evidence from Botswana, Ghana, and South Africa. Washington D.C: USAID
Resource Type:
Target Population(s):
Rigor: High
Outcome(s): Increased Learning, Reduced incidence / acceptance of bullying
Intervention(s): Linked Outcomes
Associated Resource Tool(s):
Overview: The Bureau for Africa, Office of Sustainable Development, Education Division (AFR/SD/ED) of the United States Agency for International Development (USAID) commissioned the Strategic Analytics Lab of the Center on Conflict and Development (ConDev) at Texas A&M University under the Opportunities for Achievement and Safety in Schools (OASIS) program to empirically assess the effect of bullying on student academic achievement. ConDev is a multidisciplinary center sponsored by USAID’s Higher Education Solutions Network (HESN). In support of the USAID Education Strategy, the Bureau for Africa Office of Sustainable Development’s Regional Development Cooperation Strategy (RDCS), and the United States Strategy to Prevent and Respond to Gender-based Violence Globally, the OASIS program aims to increase access and quality in education for students and out-of-school youth by focusing on school-related gender-based Violence (SRGBV). OASIS is designed to help reduce SRGBV by enabling USAID and its partners to effectively address SRGBV through better understanding of SRGBV by (a) generating evidence, (b) fostering better capability to generate such evidence, (c) improving coordination, and (d) increasing awareness... The present study is a contribution to the first objective of OASIS: “Generating Data.” It is expected to contribute to the evidence base in order to help the international development community understand how SRGBV affects academic achievement. (pp.i-ii).
Methodology: The present study aims to identify and quantify the effects of bullying on academic performance using the datasets collected from the PIRLS and TIMSS surveys conducted in 2011 in Botswana, Ghana, and South Africa. We adopt an analytical approach that enables differentiation between the influence of bullying and demographic and economic factors on academic performance in an effort to inform educational policy.
  • The datasets are internationally comparative, and enriched by comprehensive background information related to students and their households, teachers, and schools. The exams are administered in the fourth and eighth grades, enabling comparisons between cohorts of students. Over 36,000 students participated in the exams in 2011....
We utilize several statistical techniques to evaluate the relationship between bullying and academic performance. Each technique is adopted to overcome limitations resulting from academic performance and bullying data having been collected at a single point in time. The analysis utilizes ordinary least square (OLS), propensity score matching (PSM), and directed acyclic graph (DAG) techniques.
  • Matching techniques are employed to match each bullied student with a student who is not bullied but very similar in all other observed variables. We are able to identify the influence of bullying by comparing the average difference in academic performance between the two groups of students. Finally, it is possible that poor academic performance is a driver of bullying as opposed to bullying being the driver of poor performance. To account for this possibility, DAG analysis is employed to differentiate between those two interpretations. Student achievement in reading, math, and science is reported on a scale of 0 to 1000. (pp.2-3)
Findings: Bullying negatively impacts academic performance in each country.
  • For Botswana and Ghana, science scores are most susceptible to the negative effects of bullying.
  • The negative effects of bullying are more pronounced in eighth graders than fourth graders in Botswana—the only country that collected data for both grade cohorts in math and science.
  • In addition to bullying, other factors affect academic performance, such as teachers’ experience, parents’ education, geographical location, as well as teachers’ sex and students’ sex and age.
  • The interdependencies between these factors and bullying are complex and vary from country to country.
However, in all countries the effect of bullying is more influential than the effect of these other variables... The DAG results depict that bullying is one of the root causes of lower academic performance and nullify the notion of any reverse causality (meaning the interpretation that lower academic performance makes students more likely to be bullied). The graphical analysis also verifies that bullying in most cases is not affected by student-, teacher-, and school-specific attributes that were collected through the PIRLS and TIMSS surveys. (pp.7-8).
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