Modelling math learning on an open access intelligent tutor
Azcona, DavidORCID: 0000-0003-3693-7906, Hsiao, I-HanORCID: 0000-0002-1888-3951 and Smeaton, Alan F.ORCID: 0000-0003-1028-8389
(2018)
Modelling math learning on an open access intelligent tutor.
In: The 19th International Conference on Artificial Intelligence in Education, June 27 - 30, 2018, London, UK.
ISBN 978-3-319-93846-2
This paper presents a methodology to analyze large amount of students’ learning states on two math courses offered by Global Fresh- man Academy program at Arizona State University. These two courses utilised ALEKS (Assessment and Learning in Knowledge Spaces) Arti- ficial 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 Tu- toring Systems to examine the potential of the embedding representa- tions on students learning.
Item Type:
Conference or Workshop Item (Poster)
Event Type:
Conference
Refereed:
No
Uncontrolled Keywords:
Machine Learning; Intelligent Tutoring Systems; Social Network Analysis; MOOC
This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:
Irish Research Councile Irish Research Council with the National Forum for the Enhancement of Teaching and Learning in Ireland project no. GOIPG/2015/3497, Science Foundation Ireland grant SFI/12/RC/2289, Fulbright Ireland
ID Code:
22448
Deposited On:
03 Jul 2018 12:14 by
David Azcona
. Last Modified 11 Feb 2019 14:50