Datasets on demographic trends in enrollment into undergraduate engineering programs at Covenant University, Nigeria

In this data article, we present and analyze the demographic data of undergraduates admitted into engineering programs at Covenant University, Nigeria. The population distribution of 2649 candidates admitted into Chemical Engineering, Civil Engineering, Computer Engineering, Electrical and Electronics Engineering, Information and Communication Engineering, Mechanical Engineering, and Petroleum Engineering programs between 2002 and 2009 are analyzed by gender, age, and state of origin. The data provided in this data article were retrieved from the student bio-data submitted to the Department of Admissions and Student Records (DASR) and Center for Systems and Information Services (CSIS) by the candidates during the application process into the various engineering undergraduate programs. These vital information is made publicly available, after proper data anonymization, to facilitate empirical research in the emerging field of demographics analytics in higher education. A Microsoft Excel spreadsheet file is attached to this data article and the data is thoroughly described for easy reuse. Descriptive statistics and frequency distributions of the demographic data are presented in tables, plots, graphs, and charts. Unrestricted access to these demographic data will facilitate reliable and evidence-based research findings for sustainable education in developing countries.


a b s t r a c t
In this data article, we present and analyze the demographic data of undergraduates admitted into engineering programs at Covenant University, Nigeria. The population distribution of 2649 candidates admitted into Chemical Engineering, Civil Engineering, Computer Engineering, Electrical and Electronics Engineering, Information and Communication Engineering, Mechanical Engineering, and Petroleum Engineering programs between 2002 and 2009 are analyzed by gender, age, and state of origin. The data provided in this data article were retrieved from the student biodata submitted to the Department of Admissions and Student Records (DASR) and Center for Systems and Information Services (CSIS) by the candidates during the application process into the various engineering undergraduate programs. These vital information is made publicly available, after proper data anonymization, to facilitate empirical research in the emerging field of demographics analytics in higher education. A Microsoft Excel spreadsheet file is attached to this data article and the data is thoroughly described for easy reuse. Descriptive statistics and frequency distributions of the demographic data are presented in tables, plots, graphs, and charts. Unrestricted access to these

Subject area
Engineering Education More specific subject area

Demographic Analytics
Type of data Tables, charts, and spreadsheet file How data was acquired The demographic data were retrieved from the information submitted to the Department of Admissions and Student Records (DASR) and Center for Systems and Information Services (CSIS) by the candidates during the application process into the various engineering undergraduate programs.

Data format
Raw, analyzed

Experimental factors
Applicants with incomplete academic records were excluded

Experimental features
Descriptive statistics and frequency distributions of the demographic data are analyzed and presented in tables and charts.

Data accessibility
In order to encourage evidence-based research in admission analytics, detailed datasets are made publicly available in a Microsoft Excel spreadsheet file attached to this article.

Value of the data
Demographic data provided in this article will encourage empirical research and the adoption of data analytics in understanding the trends in enrollment of undergraduates in higher education, especially in developing countries [1][2][3][4][5].
Unrestricted access to these demographic data will give executives, management, and policy makers in higher education useful insights for better decision-making [6,7].
Further exploration of these data by the global educational research community will facilitate gender equality in higher education and encourage women participation in the field of engineering. Also, underserved population can be identified and possible solutions may be recommended to relevant authorities [8][9][10][11][12][13].
Descriptive statistics and frequency distributions that are presented in tables and charts will make data interpretation much easier for scientific conclusions [14][15][16][17].
Data shared in this data article will open up doors for new research collaborations.

Data
The fourth goal (Goal 4) of the Sustainable Development Goals (SDGs) set by the general assembly of the United Nations in September 2015 focus on "ensuring inclusive and equitable quality education, and promoting lifelong learning opportunities for all" [18][19][20]. It is expected that both women and men should have equal access to "affordable and quality technical, vocational, tertiary education" by 2030. This, in essence, will encourage gender equality in higher education, most especially for mendominated programs of study. Table 1 presents the gender distribution of undergraduates admitted into the seven engineering programs (Chemical Engineering, Civil Engineering, Computer Engineering, Electrical and Electronics Engineering, Information and Communication Engineering, Mechanical Engineering, and Petroleum Engineering) over the period of eight years (2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)). In each year, the engineering programs are significantly male-dominated. Fig. 1 shows a good graphical visualization of the gender distribution of undergraduates admitted into the seven engineering programs in the eight-year period. The proportions of female to male undergraduates in the engineering programs are illustrated in Fig. 2 In addition, age distribution of the undergraduates admitted into the engineering programs at Covenant University are presented and analyzed. The ages of the students are grouped into four categories: 14-17 years old; 18-21 years old; 22-25 years old; and 26 years old and above. The population distribution of the undergraduates by age is presented in Table 2. The bar chart in Fig. 3 shows the graphical visualization of the age distribution. The proportions of undergraduates each of the age groups are shown in Fig. 4(a)-(b).

Experimental design, materials and methods
For the eight-year admission period covered in this study, the demographic data (gender, age, and state of origin) of undergraduate admitted into the seven engineering programs available at Covenant University, Nigeria were retrieved from the student bio-data submitted to the Department of Admissions and Student Records (DASR) and Center for Systems and Information Services (CSIS). The  The population sample of the undergraduates admitted into the engineering programs are analyzed by state of origin and the results are presented in Table 3. All of the states of the Federation and Economic, political, and educational resources are often shared across six geopolitical zones in Nigeria. The states of the federation are grouped into the six geopolitical zones as presented in Table 4. The analysis of the contributions of each zone to the total number of engineering undergraduates are also available in Table 4. Fig. 13 shows the percentage contribution of each zone to the total number of undergraduates admitted into engineering programs at Covenant University, Nigeria.

Conclusion
This data article presented and analyzed the demographic trends in enrollment into undergraduate engineering programs at Covenant University, Nigeria. Demographic data provided in this article will encourage empirical research and the adoption of data analytics in understanding the trends in enrollment of undergraduates in higher education, especially in developing countries. Descriptive statistical analyses were performed based on gender, age, and state of origin of the population sample. Evidence-based insights gained from these data will inform proper formulation of admission policies that govern entry into engineering programs in the sub-Saharan African region. The contribution of these data is considered to be significant in the sense that it revealed the need to advocate for the recruitment and retention of women in technical disciplines in developing countries. Free accessibility to these demographic data will give executives, management, and policy makers in higher education useful insights for better decision-making.