Predicting Students Performance and Review on EDM: Machine Learning Theory

Authors: Ankita Patidar, Prof. Mohit Jain

Certificate: View Certificate

Abstract

Learning is a field of artificial intelligence that can use past information for the future purpose. Machine learning is similar to data mining in the way that both are looking for the pattern. Machine learning can detect a pattern in data and adjust the action. Machine learning is a field that is used in every system. Machine learning is used in the educational system, pattern recognition, Games, Industries, Social media services, online customer support, Product Recommendation Etc. In the education system, its importance becomes more because of the future of the students. There is a huge amount of data in higher education because nowadays every student is looking for higher education, so there is more need for machine learning methods in the education system. Many methods are there for the analysis of the students’ performance. Hidden information is carried out with the use of data mining, which will help in the analysis of students’ information. There is a huge amount of data in education and all the data are useful for students as well as for teachers. With the growth of institute, it becomes more importance of machine learning technology in the educational field. Clustering is one of the basic techniques often used in analysing data sets. Many clustering techniques are there but modified K-means is one of most efficient and used method. Classification techniques are also there and the most popular is the decision tree. A decision tree is also a method used for analysis of the students’ performance but compared to modified K-means, it is less stable. The unsupervised algorithm is discussed. These make use of cluster analysis to segment students into groups according to their characteristics. Elbow method is there to determine the cluster size; it will help in the optimal solution. Elbow method looks over the arm and elbow point is there. With the help of machine learning concept, it is easy to improve the result and future of students. It is not only useful for students but also for teacher and institute to improve their result.

Introduction

Education is very important for student’slife. Higher education institute are focus on analysis of every objects because of private participation. Data mining techniques is applied in many fields like marketing, medicine, fraud detection, web, and engineering and in the field if education it becomes more useful. The main aim of data mining is to know hidden information from large set of data. There are many method of machine learning which is used to predict students’ performance. Clustering is a method which is more efficient as compare to other method, and K-means is one of them. Data mining provides various methods analysis; these include classification,association,k-means,decision tree, regression, time series, neural network,etc.

Conclusion

Machine learning is very emerging technology that every placed it used. Now days in bank, labs, telecom, industrial each and every place machine learning is used. Data mining is part of it which helps in prediction, future prediction is very important in many place which help so much. Many algorithm is build and more and more research is going on every technology used the concept of it. We survey many papers for prediction of students’ performance .On comparing decision tree and k means it is seen that k means is more efficient as compare to decision tree.Students performance is so important for their future it not only help student but also help teachers institute parents. Many big institutes used the concept of AI for prediction.