GUI BASED PREDICTION OF E-LEARNING WEBSITE USING NAIVE BAYES APPROACH

Computer Science and Engineering

Big Data is a large amount of data in which pouring from various data sources and has different formats. Big Data is much more than a collection of datasets with different formats, it is an important asset which can be used to obtain enumerable benefits. In the previous system, there was huge data which are being stored in databases, but because of the varied nature of this Data, the traditional relational database systems are incapable of handling this Data. The focus of our project to use Educational Data Mining (EDM) techniques to conduct a quantitative analysis of student’s interaction with an e-learning system through instructor-lead non-graded and graded courses. This project is useful for establishing a guideline for a series of online short courses for them. A group of students’ access behavior in an e-learning system was analyzed and they were grouped according to their course access log records. It will create a difference in the learning environments that change the online access behavior of a student group. By this the students have a good technological competency, have moderate competency in interaction with learning content, and lack of interaction skills with their learning community. Here additionally we compare and discuss the performance of comparative study with finding the best accuracy apply in various supervised machine learning techniques from the given dataset with GUI based application by given dataset attributes.

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.