  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.
