AI Case Study
Yixue Squirrel AI Learning maximises students' progress through a individualised AI-powered adaptive learning system
Yixue Squirrel AI Learning has developed a system that is able to provide highly personalised course syllabus for each individual student with the use of AI. The technology is used for diagnosis and prescription, where the content of courses is adjusted to each student according to their performance and progress.
Public And Social Sector
Education And Academia
"One such programme, provided by Chinese edtech company Yixue Squirrel AI Learning, goes much further than a simple online course. Boasting over 1,000 education centres across the whole of China, Squirrel AI provides students with AI-powered adaptive learning system which tutors in many different subjects. Working from either a supervised learning centre after school, or via an online space featuring regular video call contact with personal mentors, Yixue tailors a course exactly according to a student’s strengths and progress thus far.
After school, students are able to study in a supervised environment in the education centres or at home. They can work through the course content at their own pace, with each new course item a unique data point of thousands designed to optimize learning efficiency.
Diagnosis & prescription: using AI to adjust content by performance
Any adaptive learning system, explains Yixue’s Chief Data Scientist Dan Bindman, is made possible by three components. The first is a necessary part of all learning: the content itself. Some subjects are better-suited to this than others. Math, for example, has a natural structure and progression to it, whereas more open-ended subjects such as the humanities are more difficult to model. For Bindman, it comes down to the strength of the content itself: “How strong is the content? How complete is the content? How deep is the content? These questions apply whether you’re going to introduce adaptive learning or not: it’s the content you’re going to be teaching.”
Secondly, there’s what Bindman calls ‘diagnosis’. This is where the system identifies exactly what the student does and doesn’t know at an extremely high resolution; something traditionally performed—painstakingly—by a teacher. This is achieved through breaking up the content into units made up of thousands of ‘items’—a group of similar questions that aim to teach students solutions to specific problems.
“If I showed you how to do x+7 = 14 once, I wouldn’t give you that problem again because you’d just do it by memory. Instead, I’ll give you a different problem,” Bindman says. “That makes up a single item, and in all of Beginners’ Algebra there might be 1000 to 2000 items that make up the entire course.”
What makes adaptive learning special is that it figures out exactly which of those items a student is strong and weak at in order to identify what they’re ready to learn. Unlike a traditional classroom where all 30 or 40 students are taught the same thing—regardless of individual progress—adaptive learning is able to provide a highly individualised course syllabus in order to maximise a student’s progress."
"The traditional model of classroom education, sadly, continues to be very much one-size-fits-all. A course syllabus is interpreted and delivered by a teacher en masse to large groups of students, with little flexibility allowed for the bright sparks or the slow learners. This is as true of schools the world over.
However, this one-size-fits-all approach is problematic—especially in highly competitive education systems like that of China. China’s high school and university admissions tests are among the most challenging and demanding in the world, and with every parent looking to get their child ahead, there’s a huge market out there for innovative, individualized e-learning tools."