Learning analytics: Predicting student performance with classification trees (in R and SPSS)

Facilitators: Dennis Foung (ELC), Hilary Ng (EDC)
Date: 24 Oct 2018
Time: 12:30 PM - 2:00 PM
Venue: TU616

The classification tree is one of the most commonly used data mining techniques for predicting student performance. This technique is popular because it is easy to interpret and can provide students with specific suggestions for improvement. This session aims to help colleagues master the basic concepts of classification trees and develop classification trees for their teaching context. To achieve the most from the workshop, you are expected to (1) bring your laptop to the session; (2) install R and R studio; and (3) try to access SPSS before attending the session. More information and download links will be sent to registered participants later. Come and join us to experience learning analytics! 

This activity is jointly organised by the CoP on Conducting Learning Analytics to Inform Teaching and Learning and EDC.