How Educators Can Benefit from Machine Learning?

A few classrooms are already seen devoting resources to ML adoption. Teachers use this form of AI to predict pupils’ performance, assess progress objectively, enhance instruction and retention, and more.

FREMONT, CA: Today, much of technology power lies in machine learning. The concept of training a computer to analyze and act on its own preference is part of the push to craft Artificial Intelligence (AI), while the process of creating AI, on the other hand, is an involved one. AI relies on machine learning (optimized algorithms) that, in turn, summarizes deep learning (layers of mathematical formulas). Machine learning is still new in the education industry, but it is growing up fast. This form of AI brings benefits in several areas.  

Experiential Learning 

Artificial intelligence simulates learning in ways that a textbook cannot. Reading requires the use of visual sense, but experiential learning in the form of virtual reality needs the use of multiple senses. 

Students registered in the Mandarin Project, for instance, take on in immersive learning to practice their Mandarin skills. Other scenarios include a restaurant and a tai chi class where pupils communicate with a machine-learned Mandarin-speaking chatbot. At the virtual restaurant, learners stand in a virtual room where a bot offers to seat them at a table. Furthermore, it takes their food order, helping with Mandarin tone and delivery. Students can practice pronunciation and grammar without the fear of harsh judgment from native speakers.

Real-Time Data Analytics

A few classrooms are already seen devoting resources to ML adoption. Teachers use this form of AI to predict pupils’ performance, assess progress objectively, enhance instruction and retention, and more. Many schools have also employed learning management systems and tutorial programs that recognize student weaknesses and strengths. This effort assists learners in developing their understanding of concepts.

Mental Health Predictions 

The number of students experiencing mental illness has seen a rise in recent times. Furthermore, more than half of school-age children experience at least one traumatic episode, and early identification of diseases like PTSD may allow for the prevention of the diagnosis. Machine learning facilitates researchers to accurately predict the probability of developing mental illness, in particular, post-traumatic-stress-disorder (PTSD). 

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