Applications of machine learning in improving learning environment

Abstract

Machine learning are having a tremendous impact on the teaching industry. Teaching industry is adopting new technologies to predict the future of education system. It is Machine learning which predict the future nature of education environment by adapting new advanced intelligent technologies. This work explores the application of Machine Learning in teaching and learning for further improvement in the learning environment in higher education. We explore the application of machine learning in customized teaching and learning environment and explore further directions for research. Customized teaching and learning consider student background, individual student aptitude, learning speed and response of each student. This customized teaching and learning approach provide feedback to teacher after real-time processing of the data. This way a teacher can easily recognize student attention and take corrective measures. This will improve student participation and hence the overall results. Individual student concepts and goals can easily be track with the help of Machine learning by taking real-time feedback. Based on that feedback, curriculum, topics and methodology can be improved further. In simple terms, machine learning makes the process automatic for decision making process and analyzed the individual student data. Overall, the assessment process is made more streamlined, accurate and unbiased with the help of machine learning. In the near future, machine learning will be more efficient and produce even better results.