Using Descriptive Analytics for the Improvement of National University Entrance Exam: A case study in the Context of Kankor in Afghanistan

In Afghanistan, High school graduates, to continue higher education, need to pass the National University Entrance Exam (Kankor). Kankor is very important and requires further research as it is used as the only means to identify the participant's competence and skills which leads to a qualified higher education and manpower, employment opportunities, allocation of human capital in appropriate fields of study, and leading to a more specialized labor force in the long run. Having a better picture of Kankor in Afghanistan is essential before employing educational data mining techniques and other social and pedagogical approaches to support the students and the educational institutions. Hence, the author carried out a research on Kankor, in which he assessed and analyzed Kankor from different angles. This research paper provides positive contribution to the Ministry of Higher Education (MoHE), particularly, the Kankor committee, and other educational institutions - introducing the importance of data as an asset and a proper structure of recording and producing data effective for research studies, paving the way for in-depth descriptive and predictive analytics which improves the situation within the context of the existing structural models in Afghanistan. The author's research target is to study Kankor using descriptive analytics supported by Kankor Results Data (KRD) of 1.5 million records from 2003-2015, Detailed Kankor Results Data which is a subset of KRD from 2004-2006 of 120,000 records, High school performance and grades data from 2011-2013 of 6,000 records, data collected through conducting more than 2500 questionnaires among academicians as well as the author's personal observations, findings, and analyses as a student and faculty member at the University in the field of computer science.
Comment: 15 pages, 5 figures