More and more machines are learning from the data and are becoming more intelligent. This became possible because of the advancements in ML and AI. And all this innovation, in our opinion, will change the world.
But for good!
Why are such innovations picking pace? It’s because of the evolution and ease of access to Tools and frameworks for building things using machine learning. This enables more and more entrepreneurs, companies, and even governments to use ML and AI to resolve many issues faced by humanity.
Now coming towards education. Many educationists and experts have discussed at length how our current methods of teaching are obsolete and need massive transformation.
The good news is that Machine Learning can help with this transformation. Let’s look at some of the ways machine learning can transform education.
Predictive Analytics
Machine Learning, being a subset of Artificial Intelligence, can work with large data sets to identify patterns and make predictions. So, a system that can learn the habits and response of students and then recommend the best method of teaching, can be a game changer.
So, Predictive Analysis can also be used to estimate how easily the students will grasp the concepts of a course. This is especially useful in terms of relative learning and can be employed to take the whole class together.
DreamBox Learning Math is an example of such a system designed to adjust the pace of learning.
Content Personalisation
One of the biggest problems with conventional teaching methods is that the course content is fixed. But every student has its own learning pace and aptitude. So, the traditional methods can’t help a teacher in personalizing the content or teaching style.
Machine Learning can help resolve this issues by identifying students and grading them as per their current progress. Such a system can also determine which teaching style works better with a certain individual. This can help in adjusting course content for the student who is struggling or excelling.
Student Assessment
Artificial Intelligence has long been used to grade MCQ-based tests to remove errors.
Teachers are using tools like Turn It In to grade student assignments.
Not only can Machine Learning save the instructor time grading the assignment, but can also help with identifying plagiarism.
Universal Access
Machine Learning with Natural Language Processing that can be used for translation. This essentially enables people across the globe to translate any content and learn from it using their own language.
Presentation Translator is an excellent example of how AI can be used for this purpose.
Student Drop-Out Prediction
Predictive Analysis can help with the identification of high dropout rates. It can identify, before time, which student is most likely to do so.
This is possible by learning the student’s interest in subjects, then evaluating the overall performance, then accessing the feedback of teachers and advisors.
Career Path Suggestions
Machine Learning can also help a student with picking up the career paths based upon his/her interest and performance.
So, with Machine Learning, no Maths genius will be forced to go through the horrors of reading fiction and becoming an editor.
Teaching Method Experimentation
Experimentation coupled with learning is the best source of correcting your course.
Why not use machines for that?
Machine learning can enable schools to conduct different teaching experiment to test different methods and then find the best one.
Summing Up:
We can safely conclude that Machine Learning will rapidly transform the educational sector in the coming years. It will not only replace the conventional and outdated teaching methods but will also make learning fun.