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“The professors are much better prepared for a single class so that they can give much more individualized instruction,” Lui said. “The practical effectiveness of this means that teachers are now able to use their time more efficiently to hone in on the things that are most troublesome or useful for different groups of students. You’re not teaching to the mean or bottom quartile.”

The technology seems to be working. After a pilot project at Arizona State University with 5,000 remedial math students, pass rates improved from 66 percent to 75 percent, with half the class finishing four weeks early

ata mining and take various inputs, like test question results, activity on the system, what links students clicked, etc. to make a prediction of the next best piece of content for a student to learn.

Analyzing and collecting big data is really what Junyo is about, enabling everyone in the education sector to make the learning experience more personal.

The students also have their own dashboard to see recommended content.

Teachers don’t have the time to do detailed reporting of a student’s progress and even if they did, they wouldn’t be able to provide one on one tutoring for every single student at different stages of learning.

students are learning more outside the classroom than in the classroom, and educators are finally starting to acknowledge that.