How Machine Learning Is Improving Education: The hidden gems

How Machine Learning Is Improving Education: The hidden gems
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How Machine Learning Is Improving Education: The hidden gems

OpenEduCat

Machine learning is the new game changer in the industry. It is all about innovation and improving the life of the millennial and beyond. If you have heard about automated card driving, you already know how machine learning can improve the life of the people.


Machine learning may look more inclined towards the mechanical parts, but it is already showing promises in the education sector. Machine learning can easily be used in Student management system or school ERP system.


The usage also depends on its application. There are many platforms that aim to improve learning of students using machine learning.


For the uninitiated, Machine learning is a subset of artificial intelligence. It basically finding the pattern in the collected data and use algorithms to make decisions or basically data-driven predictions. All of this is achieved in a continuous process and the learning aspect provides the subject the name, "Machine learning".

It is just how humans learn.


Currently, Machine learning is being used in cancer solution, terrorism, climate change, and much more.

In education, it does have its own impacts. In today's article, we will go through the platforms/software that showcase how machine learning is improving the education.


Content Analytics

Content analytics refer to machine learning platform that optimize content modules. Some of the brightest examples in this sub-niche are IBM Watson Content analytics and Gooru.


Learning Analytics

Learning analytics is focused on tracking student knowledge and enhance their learning environment.

Some of the notable platforms in adaptive learning systems are ALEKS, Dreambox, Reasoning Mind, and Knewton.


Dynamic Scheduling platforms

Learning can be a daunting task. And, that's why some platform follows the learning patterns of the students and ask teachers to step in when needed.


New Classroom is a prime example which utilizes this approach and can easily schedule personalized math learning for the masses.


Grading Systems

Current grading system relies on humans, but with machine learning students learning and knowledge can be scored. The computer assignments are score via peer grading or automated.


WriteToLearn and LightSide are two prime examples that utilize the simple machine learning algorithm to grade essays and detect plagiarism.


Process Intelligence

Process intelligence is mainly focused on analyzing a large amount of data. IT is all about finding the structured and unstructured data, identifying new opportunities and visualizing work-flow.


Three platforms really flourish in this section are Bright-bytes Clarity, IBM SPSS, Odoo, and Jenzabar.

IBM SPSS, Odoo, Jenzabar are ERP system that has better boost retention and automate and enhance another important business process.


Synchronizing teachers and Schools

Not every school has the similar requirement. TeacherMatch and MyEdMatch handle school/teacher matching.


Predictive Analysis

Predictive Analysis helps data mining jobs. It can be used to improve retention, learning, and application.

Last, but not the least, machine learning is also making it past the back office software. Good examples would be Evolution, EDULOG, DietMaster, etc.


Conclusion

Data is the main driver. To utilize big data, machine learning is playing a crucial role. Anyone related with education will be deeply improved using machine learning. Students, teachers, and administrator will find the tools very useful.


The future looks bright and if we keep improving at this speed, we will sure make our future secure and improved for our children.