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Machine Learning and the future of Education

Machine Learning and the future of Education
Machine Learning and the future of Education
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Machine Learning was started with the concept that based on algorithms the machines will learn by themselves without human intervention. Learning can do the magic of all kinds, be it for humans or for bots. Technology is advancing at a very high pace in world today- both for good and bad. ML learns from examples and experiences. They don’t generate codes but develop algorithms based on the trends and patterns they are given as data. In simple terms, it can be defined as a field of computer science that uses statistical techniques to give computer systems the ability to “learn”.

How come machine learning is helping in developing the Education sector? There are essential ML applications that are being developed, let us discuss on brief about them,

  • Adaptive Learning

The name itself suggests the way this application will work. This application will study a student’s behavior by using real-time data and develop a curriculum. It can also be used as a personalized engagement tool that tries to adapt to the individual for better understanding.

  • Increase in Efficiency

With ML, you can manage and organize content and curriculum. Depending on the capabilities of a person, ML can bifurcate and assign them tasks which help to understand which work is suitable for student and which is suitable for a teacher. This increases the participation of both of them towards education as they will be happy to work on the tasks which are easy for them.

  • Learning Analytics

The teacher tends to also get stuck and doesn’t able to explain concepts to student as they have to be and students lose focus on the subject. With learning analytics teachers can analyze data to make connections and will be in a better position to interpret them before teaching. This will positively impact learning and teaching process.

  • Predictive Analysis

This application can help the teacher to understand the mindset and needs of the students. It will help teachers to come to conclusion on the things that might happen in the future. This means that with the results of class tests and half-yearly examination results teachers can predict which student will do well in the final exams and which students will need more focus on their studies.

  • Personalized Learning

A customized application that can cater to the needs of students and teachers based on personalized approach to a particular requirement. Using this model students and teachers can guide their own learnings. It will give them the authority to judge at what pace they have to learn and what to learn and when. Students can choose the subject they want to learn and can also choose the teacher from whom they want to get guidance from during the course.

  • Assessment Evaluation

The basic technology for assessment that was being used until now was the OMR Sheet Design Software. Similarly Machine Learning and Artificial Intelligence are now being developed to assess exam and test papers which increases accuracy of the results based on the algorithm that ML develops. There will be a bit of human intervention required but the results from the assessment evaluation tool will be more reliable and have lower chances of errors.

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