Machine Learning- Future of the Education System?
Machines have taken over all important functionalities of the urban life. To a considerable measure the mechanical tentacles have also spread through the rural areas too. While every industry and field is advancing with the use of high tech machinery, education has also upped their game by using advanced technology for better and effective learning. Online modules, virtual classroom sessions, topic-based discussion, open forums etc. are some of new techniques that universities have embraced with open arms. These new techniques have made the learning process more comprehensive and simplified for students. Machine learning is perhaps the future of education.
The Benefits of Machine Learning:
Increasing Efficiency: By completing tasks such as classroom management, virtual classroom sessions, etc. machine learning as artificial intelligence can make educators more efficient. This way, educators get the freedom to focus on tasks that cannot be achieved by AI, and that require a human touch.
Customized Learning: Machine learning can develop detailed logs for each student and deliver concepts and establish goals that fit their strengths and learning backgrounds. The technology will soon be capable of gauging the capacity of student with reference to understanding the concepts. Customized learning will also help in determining the technologies that are beneficial for students and the ones that are not, for future application.
Learning and Predicative Analytics: Data that cannot be gleaned by human brain, machine learning in the form of learning analytics can aid educators gain insight into this data. Machine learning in the form of predictive analytics can predict the future and draw conclusion. For example, using a data set of students’ cumulative records, predictive analytics can predict which ones are more likely to drop out because of poor academic performance.
Unbiased Grading: Machines can detect plagiarism or other infractions which will help in examining student’s assignments. Provide a potential grade for students while suggesting areas of improvements to help them achieve their target grade. This technology can eliminate human error and make grading more efficient and reliable. The process will be more accurate than the human brain, also reduce effort with higher quality.
Career Paths: Advanced machine learning platforms can gather information from the student’s assignments and tests that can help the educators to judge the expertise of the students. At the same time, technology can also determine the trouble areas of the students and help the teachers in planning tutoring or workshops for them to help the students achieve their goals.
Personal Meeting and Setting Up Appointments: Machine Learning can also be molded into personalized learning giving every student an individualized learning experience. In personalized learning students are free to guide their own learning, study at their pace and, in some cases, make their own decision about curriculum. Appointment scheduling between students and teachers can be a hard task, but machine learning can remedy the logistical issues involved. Machines can create a well defined and organized meeting for the teachers and students and carry out the process smoothly.
Over the next several years, artificial intelligence and machine learning could have an outsized effect on how students learn, as well as how universities structure their academic curriculum.
