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In Afghanistan, High school graduates, to continue higher education, need topass the National University Entrance Exam (Kankor). Kankor is very importantand requires further research as it is used as the only means to identify theparticipant's competence and skills which leads to a qualified higher educationand manpower, employment opportunities, allocation of human capital inappropriate fields of study, and leading to a more specialized labor force inthe long run.  Having a better picture of Kankor in Afghanistan is essential beforeemploying educational data mining techniques and other social and pedagogicalapproaches to support the students and the educational institutions. Hence, theauthor carried out a research on Kankor, in which he assessed and analyzedKankor from different angles. This research paper provides positivecontribution to the Ministry of Higher Education (MoHE), particularly, theKankor committee, and other educational institutions - introducing theimportance of data as an asset and a proper structure of recording andproducing data effective for research studies, paving the way for in-depthdescriptive and predictive analytics which improves the situation within thecontext of the existing structural models in Afghanistan.  The author's research target is to study Kankor using descriptive analyticssupported 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 120,000records, High school performance and grades data from 2011-2013 of 6,000records, data collected through conducting more than 2500 questionnaires amongacademicians as well as the author's personal observations, findings, andanalyses as a student and faculty member at the University in the field ofcomputer science.

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