NotesFAQContact Us
Search Tips
Peer reviewed Peer reviewed
PDF on ERIC Download full text
ERIC Number: EJ1115369
Record Type: Journal
Publication Date: 2009
Pages: 54
Abstractor: As Provided
ISSN: EISSN-2157-2100
Combining Unsupervised and Supervised Classification to Build User Models for Exploratory Learning Environments
Amershi, Saleema; Conati, Cristina
Journal of Educational Data Mining, v1 n1 p18-71 2009
In this paper, we present a data-based user modeling framework that uses both unsupervised and supervised classification to build student models for exploratory learning environments. We apply the framework to build student models for two different learning environments and using two different data sources (logged interface and eye-tracking data). Despite limitations due to the size of our datasets, we provide initial evidence that the framework can automatically identify meaningful student interaction behaviors and can be used to build user models for the online classification of new student behaviors online. We also show framework transferability across applications and data types.
International Educational Data Mining. e-mail:; Web site:
Publication Type: Journal Articles; Reports - Descriptive
Education Level: Higher Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A