Role of Machine Learning in Online Education

Machine learning-enabled encoding, translation, and text-to-speech algorithms allow content more available to students worldwide.

FREMONT, CA: According to the one latest market research report, AI and Machine learning in the U.S. education sector are projected to rise at a CAGR of 47.77 percent between 2018 and 22. Another market research agency expects AI to invest 6 billion dollars globally in education by 2025.

Machine learning is opening up new doors for educators and learners. Another recent study proposed that technologies could theoretically save teachers about 13 hours a week and redirect them to events that contribute to improved student outcomes.

Personalize Online Content

Personalization is one of the significant advantages of computer learning in education. ML facilitates improved learning experience—a crucial reason for a very dynamic e-learning industry. Besides, ML-based customization offers e-learning systems with a more scalable and reliable way to provide exclusive one-to-one learning experiences. ML algorithms can help predict whether a student struggles with a topic and changes the content, time, and speed of e-learning to suit their needs.

Strengthen ROI and Retention

Low retention is one of the problems often faced by online learning educators. Online learners are struggling with low enthusiasm, poor course design, or lack of contact. Any of these can influence the student's decision to drop out of class. By using ML in online education, teachers can develop a greater understanding of their students and produce high-quality, open, and individualized programs that contribute to higher degree satisfaction.

Enhance Online Learning Reach

Communicating through languages can be tricky, particularly with complicated concepts and high-speed online learning material, such as video lectures and course discussion groups. This instance becomes much more complicated as individuals with varying degrees of language skills are not in the same geographic place. ML-enabled encoding, translation, and text-to-speech algorithms allow content more available to students worldwide.

Automate Administrative Busywork

AI and other data-driven tools reduce teachers' need to perform repetitive administrative activities such as scheduling, maintaining student lists, attendance, and research content records. Instead of removing teachers, AI frees them from the pressure of tiresome jobs, allowing them more time to devote to the process of education.

See Also: Top Machine Learning Companies