Machine learning facilitates lecturers in the process of improving online learning courses for students in organizations.
FREMONT, CA: Online courses seem like a savior today because of the rise in the number of college and university students opting for an online class. A look at the survey by the National Center for Education Statistics (NCES) shows that about one-third of students choose at least one online course. In actuality, if it were not for digital education, organizations would have seen a sharp decline in the enrollment.
The online learning industry is emerging stronger than before because of technologies like Machine Learning (ML). The strong point of the system remains in the ability to recognize trends and patterns in the data that help individuals make predictions.
In terms of online learning, systems can be beneficial in several ways.
The algorithms used in machine learning can use the patterns to predict outcomes. For instance, ML can identify learners struggling with a concept, and the system consequently adjusts the e-learning subject to provide additional and more detailed information to assist the student. Online learners who have difficulty with basic concepts can receive less advanced course material to catch up with the theory. On the other hand, students who progress rapidly can receive advanced study material.
Mechanize Time-Consuming Organizational Tasks
ML frees administrators and lecturers from time-consuming jobs. For example, ML algorithms help educators in automating the way the content is delivered and also manage the preparation time. To frame coursework and provide online resources is a tedious task, but ML makes the job easy in place of time-consuming.
In online courses where the student’s strength is more, it becomes impossible for educators to provide feedback to every student. With ML algorithms, the system can track a learner’s progress and provide targeted feedback in the form of revised coursework to help students thrive in their studies.