Classification Technique for Predicting Learning Behavior of Student in Higher Education

In education system it is very important to decide learning behavior of students. Today there is huge competition in higher educational institutes. Quality education is essential for facing new educational challenges. Educational Data Mining is useful to classify students according to their knowledge and learning behavior. It helps teachers to implement different teaching methodology as per learning behavior of student. Researcher used Naïve Bayes classification technique on training data set of students. Classification is a supervised learning approach which categorized data into predefined classes. The implementation is carried out using C . Algorithm is implemented on set of multivalued attributes to predict slow learner, average learner and fast learner students. The objective of researcher is to extract hidden knowledge from dataset for prediction of learning behavior of student. Mrs. Varsha. P. Desai "Classification Technique for Predicting Learning Behavior of Student in Higher Education" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | International Conference on Digital Economy and its Impact on Business and Industry , October 2018, URL: http://www.ijtsrd.com/papers/ijtsrd18697.pdf