ENHANCING PERSONALIZED LEARNING THROUGH INTERACTIVE VISUAL ANALYTICS SYSTEMS

PhD Qualifying Examination


Title: "ENHANCING PERSONALIZED LEARNING THROUGH INTERACTIVE VISUAL 
ANALYTICS SYSTEMS"

by

Mr. Zixin CHEN


Abstract:

Challenging the conventional “one-size-fits-all” approach in education, 
there is a critical shift towards personalized learning experiences, 
designed to accommodate individual factors such as student abilities and 
learning preferences. Technological advancements, including visual 
analytics and artificial intelligence, are playing a pivotal role in this 
transformation by facilitating efficient data analysis. However, given the 
absence of a universally accepted definition of personalized learning, the 
role and impact of these technologies in executing personalized learning 
remain ambiguous.

This survey aims to consolidate existing literature by delving deeper into 
the concept of personalized learning, its associated facets, and notably, 
the impact of supportive technologies. We present a taxonomy of 
requirements derived from various user scenarios, aiming to enhance the 
implementation of personalized learning.

To characterize the degree of personalized learning, we also propose two 
dimensions, granularity and preciseness, in our analysis. Lastly, we 
identify gaps in current practices and categorize various efforts. With 
the aid of advanced AI technologies like Large Language Models, there is 
substantial potential to elevate personalized learning to the next level.


Date:			Tuesday, 3 October 2023

Time:                  	2:00pm - 4:00pm

Venue:			Room 5510
 			lifts 25/26

Committee Members:	Prof. Huamin Qu (Supervisor)
   			Prof. Pedro Sander (Chairperson)
 			Dr. Xiaojuan Ma
 			Dr. Shuai Wang


**** ALL are Welcome ****