Abstract
Information and Communication Technologies (ICTs) today permeate every aspect of our lives including the education system. To this effect, a number of Education Management Information Systems (EMIS) have been developed and put to use especially in the developed nations. However, many developing countries, especially in sub-Saharan Africa and South East Asia, are yet to fully exploit the potential of these EMIS(s). Successful management of today's education systems requires effective policy-making and system monitoring through data and information. However, in many cases, EMIS design and development has been limited to information technology enhancements, and/or data storage and maintenance, with insufficient attention paid to data utilization for policy decisions. This paper proposes a simple revision toolkit whose power is in the utilization of data by applying fundamental artificial Intelligence technique known as K-Nearest Neighbour (KNN) classifiers to enhance utilization of EMIS in delivering the right content to students based on their abilities and also giving their instructors (teachers) a data driven insight into what subjects/sub-topics are posing challenges to students.
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