Recently, a team of researchers from the University of California, Berkeley have developed a machine learning approach that can give teachers and researchers insights into the entire class, rather than just a few select students. This approach, which was recently published in the journal PLOS ONE, uses machine learning to analyze student data from the classroom and suggest strategies for improving student performance. The research team tested their approach on over 3,000 students in the United States and found that the machine learning approach was able to accurately identify which strategies would be most effective for each student. This approach could revolutionize the way teachers and researchers interact with students, as it gives them the ability to better understand and address the individual needs of each student in the classroom.

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source: Phys.org