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dc.thesis.supervisorJayaratne, K.L. (Dr.)-
dc.thesis.supervisorPremaratne, H.L. (Dr.)-
dc.contributor.authorJayathilaka, Fr.P.R. (Rev)-
dc.description.abstractThis research is on an application of neural network and fuzzy models to evaluate the sociological factors, which affect the educational performance of the students in Sri Lanka. One of its major goals is to prepare the grounds to device a counseling tool, which helps these students for a better performance at their examinations, especially at their G.C.E O/L examination. Closely related sociological factors are collected as raw data and the noise of these data are filtered through the fuzzy interface and the supervised neural network is being utilized to recognize performance patterns against the chosen social factors. The geographical area of the research is Puttalam District. It is a district in the North West Province of Sri Lanka and it is an area of people of different religions, ethnicities, and etc. It also covers two Educational Zones namely Puttalam and Chilaw. The System is trained with the data obtained from a questionnaire given to the sample students before their G.C.E. Ordinary Level Examination and Examination results of the particular group of students. These data are fed into the system and the ANN is trained. Well trained ANN would be able to utilize as a counseling tool to help the children. With the questionnaire tool the selected social environmental data of a student could be obtained. With the well trained ANN, it is possible to predict the G.C.E. O/L results and identify the socially weak area which needs more attention. If possible the social environment could be adjusted to encourage student to perform better at the Examination.en_US
dc.titleAn AI Approach to Investigate Sociological Impact on Education in Puttalam District Sri Lanakaen_US
Appears in Collections:2014

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