Module 16: Learning Path Generation

Faculty Contact: Xifeng Yan

Research Areas:

Abstract: UNESCO estimates that more than 59 million children of primary-school age do not have access to education. In order to teach these children today, 2.7 million additional teachers are needed. By 2030, an additional 25.8 million teachers are needed to meet world demand. Companies like Coursera, Khan Academy, Udacity and others are aiming to improve the availability of education to all. However much of this process still requires a significant amount of human interaction. With the huge amount of information available on the internet we can use this knowledge to alleviate the demand on the number of teachers. For this research, we will investigate the ability for computers to automatically generate a learning path to help an individual master a subject area.

To achieve our goal of enabling computers to plan out a teaching curriculum for any individual, we will need to answer the following questions:

  • How can an easiness rating be assigned to a subject are?
  • How do we assign a relative ordering to topics for learning?
  • What is the background knowledge necessary for understanding?
  • What are the subject areas that an individual can quickly improve on?
  • How do we enable computers to extract the information to do all this?

As scientists, we have been fortunate to receive the best possible education society offers. With this research, we hope to take a small step towards making the education we have received available for everyone. 

Active Quarters:

  • Spring 2016: Yi Ding