The number of college and university students taking classes online keeps on growing. According to the National Center for Education Statistics (NCES), a third of all students now take at least one online course. In fact, if it were not for online education, college and university enrollments would be declining even more.

The online learning industry is growing stronger with the help of technologies like machine learning. Machine learning is a sub-division of artificial intelligence. The technology involves algorithms that can draw conclusions and make predictions based on large data sets. The strength of the system lies in its ability to identify patterns and trends in the data and, based on those patterns, to make predictions that can benefit humans.

In terms of online learning, these systems can be invaluable in a number of ways.

1. Machine learning can personalize content

Machine learning algorithms use pattern recognition to predict outcomes. For example, ML algorithms can spot when a student repeatedly struggles with a concept, and the system can adjust the e-learning content to provide additional, more detailed information to help the student. So an online student who has not mastered the basic concepts needed to continue a course may receive specific course material to help the student catch up.

The system will adjust to deliver the eLearning content in a format that’s suited to each student’s needs – more advanced material for those students who progress fast through the material and less  advanced material for students who need to catch up.

2. Automate time-consuming administrative tasks

Machine learning can free lecturers and administrators from time-consuming busy work. For instance, machine learning algorithms can help to automate scheduling and content delivery processes. Scheduling coursework for online learners is a tedious and time-consuming task that can’t be avoided. So is delivering online resources for students.

In the near future, artificial intelligence, through the application of machine learning, will liberate professionals from mundane tasks, allowing them to proceed with more high-level and satisfying work.

 3. Provide personalized feedback

In large online courses, it’s impossible for lecturers to give meaningful feedback to each and every student, even when there are a number of lecturers assigned to the same course.

Machine learning algorithms can change all that. These systems can follow a student’s progress and provide targeted feedback in the form of additional or specially revised course work to help the student succeed in their studies.

Any questions that the student might have, could be answered by machine learning software. This level of assistance will be possible once machine learning has advanced enough to make use of natural language processing in order to understand and answer student questions

4. Improve ROI for online learning

MOOCs, Massive Open Online Courses often have unlimited enrollments with thousands of people across the world taking a single class. As it stands MOOCs have massive dropout rates.

With the help of machine learning, students will waste less time online with work they struggle with because they will get personalized help from the machine learning software. All of this will lead to more students completing their online studies.

Thanks to predictive analytics that can track students’ progress, online companies can also spend less on online training. Feedback from machine learning algorithms will enable online education companies to deploy their online training resources more effectively.