ViDeX


Period: 2018 ~ Present
Grant: Microsoft
Budget: $300,000
Partner: Microsoft OneNote

 


CONTEXTS

 

In higher education, the popularity of flipped and blended classrooms has increased the number of students learning through asynchronous, online educational technologies. It is important that these technologies support students’ cognitive and social engagement. In my collaboration with UBC and Microsoft, I have developed an analytic framework that classifies students’ level of cognitive engagement through their multidimensional clickstream data using unsupervised machine learning methods (e.g., self-organized mapping).

 


METHODS

 

  • Analyzed clickstream big data using unsupervised machine learning methods (e.g., self-organized mapping)
  • Designed an AI agent to identify the conceptually important aspects of a video and automatically generates relevant exam questions in order to test students’ understanding
  • Tools: Deep learning

 


OUTCOMES

 

JOURNAL ARTICLES

  • Seo, K., Dodson, S., Harandi, N., Roberson, N., Sunani, S., Fels, S., & Roll, I. (submitting). How students learn with video: An analytic framework to unveil students’ cognitive engagement with video in different educational contexts. Computers & Education.

 

CONFERENCE PAPERS

 


 

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