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Modelling Math Learning on an Open Access Intelligent Tutor

Authors: 

David Azcona, I-Han Hsiao, Alan Smeaton

Publication Type: 
Refereed Conference Meeting Proceeding
Abstract: 
This paper presents a methodology to analyze large amount of students’ learning states on two math courses offered by Global Freshman Academy program at Arizona State University. These two courses utilised ALEKS (Assessment and Learning in Knowledge Spaces) Artificial Intelligence technology to facilitate massive open online learning. We explore social network analysis and unsupervised learning approaches (such as probabilistic graphical models) on these type of Intelligent Tutoring Systems to examine the potential of the embedding representations on students learning.
Conference Name: 
International Conference on Artificial Intelligence in Education AIED 2018
Proceedings: 
Lecture Notes in Computer Science book series (LNCS, volume 10948) Proceedings of the International Conference on Artificial Intelligence in Education AIED 2018
Digital Object Identifer (DOI): 
10.1007/978-3-319-93846-2_7
Publication Date: 
20/06/2018
Conference Location: 
United Kingdom (excluding Northern Ireland)
Research Group: 
Institution: 
Dublin City University (DCU)
Open access repository: 
Yes