Predictive Analytics in Educational Data Mining With Machine Learning

This book consists of information related to Educational Data Mining and Machine Learning. First, Teacher's performance predicted to find the quality of teaching to get the better performance of learner and to provide the better quality of materials. Machine Learning Algorithms used for prediction of instructor performance depends on the feedback collected from the students. The supervised machine learning algorithms applied in the dataset. The implementation was done in R Programming. The Support Vector Machine provides high accuracy comparing with other classifiers. Second, the students need to be classifying with different groups based on knowledge level value and level of interest such as beginner, intermediate and master. The benchmark dataset used from Kaggle. The same dataset executed with the different machine learning and deep learning algorithms. The high performance produced by Deep Neural Network comparing with other machine learning classifiers. Third, the Recommendation system was developed which is used to recommend needed materials to the students based on their interest using Context Aware-Neural Collaborative Filtering.

Autorentext

Dr. Vijayalakshmi Vengattaramane, an Assistant Professor in the Data Science and Business Systems department at SRM Institute of Science and Technology, Chennai, has over 11 years of teaching experience. Her research interests include Machine Learning, Deep Learning, Natural Language Processing, and Earth System Science.