WOMEN ENGINEERS: A STUDY OF PARTICIPATION IN EDUCATION AND EMPLOYMENT IN AMHARA REGION, ETHIOPIA

Abstract

According to African Development Bank (AFDB) data, the annual growth of Ethiopian GDP was very low before the year 2000 because of low production, drought condition, Ethio-Eretria war, low-level of infrastructure development, and inconsistent technological development. However, it increased remarkably and experienced a 7.9% annual growth rate since 2000 onward. Now, Ethiopia's main challenges is to sustain its positive economic growth for which the government has given enough attention on developing its higher education landscape besides other. Like other countries, higher education is valued in Ethiopia because it develops an appropriate human capital required for national development. Specifically, engineering education is key for the development of appropriate technology of enhancing productivity. Traditionally, women are underrepresented in engineering education and employment as in many other parts of the globe. In this background, the purpose of this study is to investigate the issue thread bear. The education aspect has been discussed at three level as, the factors which affect women’s choice of pursuing engineering education, the factors which affect women’s achievements in engineering. At the employment aspect, it has investigated the factors affecting women graduates' employability in engineering in Ethiopia, and analysing the challenges faced by them at the work place. An effort has also been made to examine the effect of economic growth on women human capital formation in engineering during 1997-2018. Both primary and secondary data has been used to justify arguments. Secondary data for the study has been gathered from a variety of secondary sources as Annual reports from the Ethiopian Ministry of Education, UNESCO, the African Development Bank Group, the World Bank, and ILOSTAT. Reputable journals, books, various papers, periodicals, proceedings and other sources on women's involvement in engineering education and employment have also been considered. Primary data have been collected from 843 women students of engineering and science using well-structured questionnaires and detailed interviews through phone. Appropriate statistical tools have been used for analysing the data. To check the stationarity of the secondary data, Augmented Dickey-Fuller unit root test has been used. The bound test was used to investigate whether there is co-integration in the short run and V long run. After checking through the bound test, the ARDL model with error correction term has been estimated. Logit and Probit binary regression models, and OLS (ordinary least square multiple linear regression estimation) have also been used. Spearman’s Rank Correlation test of selected variables has also been computed. In addition, various post estimation tests were also computed in order to check the unbiasedness of estimated coefficients and model fitting. Detailed analysis of secondary data has been made (chapter 4) in support of the first objective that women are underrepresented in engineering education and employment. Through ARDL model with error correction term, an effort has been made to verify the impact of economic growth and government expenditure on education on women's human capital formation through engineering education. The result shows a significant and positive impact in the long run for both government expenditure and economic growth on education but these are insignificant in the short run. The reason may be the small-time frame during, which it is difficult to expect significant result. The Logit regression has been used for analysing factors affecting women’s choice of learning engineering, which reveals that expected salary is the most influencing factor. Other factors have been ranked on the basis of their influences are high school education performance (results of grade 12 exam), having an engineer in the family and accessibility of the role models. The family’s annual income has least influence on the choice of learning engineering. The OLS multiple regression model has been used for the fourth objective on women's academic performance in engineering education. The result shows that students’ capabilities to gather information about the institution before joining the university is the most influencing factor. The second one is university’s infrastructure followed by institutions’ support for women students and the least affecting factor is peer learning habits of students. However, sexual harassment and the presence of engineers in the family have negative impact. The reason for negative impact of sexual harassment is quite obvious. However, negative impact of engineers in the family on academic performance needs further investigation as it does not look very logical. The Probit model has been used for the fifth objective which is on factors affecting employability of the women graduate engineers. The dependent variable was unemployment among them and the independent variables are communication skills, academic performance (cumulative GPA), willingness to migrate from one place to another for searching jobs, and non- VI technical skills. As unemployment was dependent variable, the reverse of results may be seen as factors for employability. The last objective was on challenges faced by working women. Out of 244 total respondents, 35.25% have mentioned major problems and challenges faced by women engineers at the work place. Two third of the respondent said that they do not face any problem. Among the rest one-third, most of them complained about conflict with customer, staff member and leaders as well as discrimination, undermining and discouragement on the basis of gender, race and religion. Though on the basis of finding from a sample of a state, suggestion may not be generalised for the whole country. However, the government regulatory bodies of higher education and other stakeholders may be suggested to take affirmative measures to enhance women’s enrolment and academic performance to reduce the gender gap. Engineering colleges must pay attention to students’ psychological, economic, and educational wellbeing, improving and expanding infrastructure, and show zero tolerance for sexual harassment through strict implementation of regulations. The women engineering graduates must improve their communication skills and non-technical skills, record better grade points, and be ready for employment migration. They are also suggested for late marriage as they can concentrate on their career well. The government must create a channel between universities and firms through teaching with a work placement curriculum, more emphasis on practical works, and maintaining law and order situation for taking care citizens' peace and security, and expanding infrastructure.