The Society for Social Work and Research

2013 Annual Conference

January 16-20, 2013 I Sheraton San Diego Hotel and Marina I San Diego, CA

Individual and School Effects On Academic Performance of Youth in the Ghana Youthsave Experiment

Thursday, January 17, 2013: 4:00 PM
Executive Center 2A (Sheraton San Diego Hotel & Marina)
* noted as presenting author
Gina Chowa, PhD, Assistant Professor, University of North Carolina at Chapel Hill, Chapel Hill, NC
Rainier D. Masa, MSW, Doctoral Student, University of North Carolina at Chapel Hill, Chapel Hill, NC
Christopher Wretman, Student-Doctoral, University of North Carolina at Chapel Hill, Cahpel Hill, NC
David Ansong, MSW, PhD Student, Washington University in Saint Louis, St. Louis, MO
Isaac Osei-Akoto, Senior Fellow, Univesity of Ghana, Legon, Ghana
Purpose:  A major goal of education is to provide high-quality education experiences and adequate educational preparation for every student. Researchers have observed that a variety of individual-level variables, including socioeconomic status, are consistently linked to academic achievement (Jeynes, 2006; Konstantopoulous, 2006; Stewart, 2008). Researchers have also found that school structural characteristics influence academic performance (Bryk & Raudenbush, 1988; Konstantopoulous, 2006). In many developing countries, the conditions of school facilities, access to school resources, and teacher quality have been viewed to be a widespread problem that may affect student performance (Glewwe & Kremer, 2006). This study aims to contribute to the growing body of research on individual and school factors influencing academic performance of youth in developing countries. Particularly, this study examines the individual- and school-level characteristics associated with academic performance of Ghanaian youth.


Method: This study used the YouthSave baseline data. 6,252 youth attending 100 schools from eight of Ghana’s ten regions constituted the sample. The outcome variables are math and english examination scores. The highest possible score for both subjects is 50. Because of the hierarchical nature of educational data, we used hierarchical linear modeling (HLM) in the analysis (Raudenbush & Bryk, 2002). We conducted a two-level HLM to explore the between-school variability and the effects of individual and school characteristics on average student examination scores. One-way ANOVA with random effects was estimated to determine intraclass correlation. The intercepts-and-slopes-as-outcomes model was estimated to examine the effects of individual and school characteristics.

Results: The average Math and English scores were 22.53 (9.65) and 23.04 (9.88), respectively. Thirty-seven percent of the variation in math and 32% of the variation in english scores are between schools. The remaining variation is due to differences among students within schools. Four individual-level characteristics (gender, age, self-efficacy, and home parental involvement) are statistically significant (p < .05) predictors of math exam scores. Five individual-level characteristics (gender, age, ownership of household possessions, self-efficacy, and home parental involvement) are statistically significant (p < .05) predictors of english exam scores. None of the school-level variables are a statistically significant (p > .05) predictor of either math or english scores.  


Conclusion and Implications: This study illustrates the role of individual- and school-level characteristics on academic scores of Ghanaian youth. The variance decomposition suggests that most of the variation is within schools; however the between-school variation is above 0.25 which indicates the importance of using HLM (Heinrich & Lynn, 2001; Guo, 2005). The study finds evidence to support that there are substantial associations between individual-level predictors and youth’s academic achievement. Some of the findings are consistent with prior studies in Ghana and other developing countries that have shown association between individual characteristics and academic performance (Etsey, 2005; Lockheed, Fuller, & Nyirongo, 1989). Contrary to prior studies in developing countries (Fuller and Clarke, 1994; Kasirye, 2009; Suryadarma, Suryahadi, Sumarto, & Rogers, 2006), we did not find statistically significant associations between school factors and academic performance.