It is beyond any doubt that education has been the dire need of any society. Education is a lifelong process. It continues from the cradle to the grave. It equips people with knowledge and skills to enable them to live a prosperous and happy life. Education serves as supra structure of a country. The development of country depends upon the standard and quality of education in the country. Education is a mean through which a man knows himself and his position and duties in this world. It helps individual in self-realization and is a process of exploring of individual's potentiality and tries to enable the individual using his power in positive manner (Khalid, 1998). The arrival of Syed Ahmad Khan on the India educational scene is perhaps the most outstanding event in the 19 th century in the history of Muslim education. This paper will analyze the views, educational philosophy and contribution of Sir Syed in the field of education and the out put of Aligarh Movement initiated by Sir Syed Ahmad Khan.
Abstract-Students' pedagogical progress plays a pivotal role in any educational institute in order to pursue imperative education. Educational institutes, Universities, Colleges implement various performance measures in order to keep analyzing and tracking progress of students to cultivate benefits of education in a better way. There are several data mining techniques to apply on education in order to build constructive educational strategies and solutions. This study aims to analyze and track engineering under graduate student's records to judge quality education, student motivation towards learning, and student pedagogical progress to maintain education at high quality level and predicting engineering student's forthcoming progress. Different engineering discipline students' (of three different cohorts) data have been analyzed for tracing current as well as future pedagogical progress based on their sessional (preexamination) marks. In this research, the classification techniques by k-nearest neighbor, Naïve Bayes and decision trees are applied to evaluate different engineering technologies student's performance and also there are different methodologies that can be used for data classification.
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