Sciweavers

Free Online Productivity Tools i2Speak i2Symbol i2OCR iTex2Img iWeb2Print iWeb2Shot i2Type iPdf2Split iPdf2Merge i2Bopomofo i2Arabic i2Style i2Image i2PDF iLatex2Rtf Sci2ools

16

AIED
2007
Springer

favoriteEmaildiscussreport

121views Artificial Intelligence» more AIED 2007»

Learning Tutorial Rules Using Classification Based On Associations

13 years 10 months ago

Learning Tutorial Rules Using Classification Based On Associations

Download www.cs.uic.edu

Rules have been showed to be appropriate representations to model tutoring and can be easily applied to intelligent tutoring systems. We applied a machine learning technique, Classification based on Associations, to automatically learn tutorial rules from annotated tutoring dialogues of a human expert tutor. The rules we learn concern the tutor’s attitude, the domain concepts to focus on, and the tutor moves. These rules have very good accuracy. They will be incorporated in the feedback generator of an Intelligent Tutoring System. Keywords. Tutorial rules, Natural language feedback, Expert tutoring

Xin Lu, Barbara Di Eugenio, Stellan Ohlsson

Real-time Traffic

AIED 2007 | Artificial Intelligence | Intelligent Tutoring System | Tutorial Rules | Tutoring |

claim paper

Related Content

» A Novel Rule Ordering Approach in Classification Association Rule Mining

» Using Classification to Evaluate the Output of ConfidenceBased Association Rule Mining

» Data mining in course management systems Moodle case study and tutorial

» A Novel Rule Weighting Approach in Classification Association Rule Mining

» A study on interestingness measures for associative classifiers

» Constructing Associative Classifier Using Rough Sets and Evidence Theory

» Classification Based on Consistent Itemset Rules

» Spatial associative classification propositional vs structural approach

» Fuzzy rule selection using Iterative Rule Learning for speech data classification

Post Info
More Details (n/a)

Added	07 Jun 2010
Updated	07 Jun 2010
Type	Conference
Year	2007
Where	AIED
Authors	Xin Lu, Barbara Di Eugenio, Stellan Ohlsson

Comments (0)