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How is Machine Learning Helping Students

How is Machine Learning Helping Students

Machine Learning

The National Center for Education Statistics reports that more than 30% of all university students in the United States enroll in at least one online course each semester. With the COVID-19 epidemic showing no signs of abating, this figure is likely to climb even higher, bolstering the online learning sector’s development in both academic and corporate contexts.

The worldwide corporate eLearning market is estimated to reach $30 billion by the end of the research period, expanding at a 13% CAGR.

Unbiased assessments

The automatic grading system can also benefit from machine learning. This enables thoroughly unbiased grading that is not influenced by the teacher’s relationship with any students. Thus, it saves time for teachers and gives a more accurate picture of a child’s academic success.

Although, allowing a machine to assess student papers is not always a promising idea, as valuable as it may be. Traditional techniques of grading essays and other tasks will continue to be used by educators. Computers are incapable of appraising items that do not meet a specific technological necessity. They can analyze multiple-choice questions quickly but struggle with time-consuming essay projects.

Increased efficiency

Machine learning, often known as artificial intelligence, can increase instructor productivity by automating procedures such as classroom management and scheduling. Consequently, educators may concentrate on tasks that AI cannot do and require a human touch.

Personalized and contextualized learning

In the form of customized learning, machine learning might be utilized to provide each student with a unique educational experience. Personalized learning is an educational concept in which students direct their learning, progressing at their speed and, in some situations, making their judgments about what to study. In an ideal world, students in a customized learning classroom pick what they are interested in, and teachers tailor the curriculum and standards to the students’ interests.

Machine learning may be utilised in customised learning to provide each student with a unique educational experience. Personalized learning is an educational concept in which students direct their own learning, going at their own speed and, in some instances, choosing what to study. In an ideal world, students in a customised learning classroom select what they want to learn about, and instructors adapt the curriculum and standards to meet their needs.

Contextualized and relevant data are significantly absent in the market’s sales intelligence products. As a result, sales teams spend around 55% of their time conducting further research, analysis, and planning on their prospects. With companies worldwide being disrupted rapidly, there is a significant need for sales teams to have real-time and 360-degree information on prospects, their digital activities, technology investments, outsourcing agreements, and their ecosystem. Draup is an AI-powered sales intelligence solution that offers sales teams complete account and stakeholder knowledge to enable microtargeting.

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