A cluster-based predictive modeling to improve pedagogic reasoning
This paper discusses a cluster knowledge-based predictive modeling framework actualized in a learning agent that leverages on the capability of a clustering algorithm to discover in logged tutorial interactions unknown structures that may exhibit predictive characteristics. The learned cluster model...
Saved in:
Main Authors: | Legaspi, Roberto S., Sison, Raymund, Fukui, Ken Ichi, Numao, Masayuki |
---|---|
Format: | text |
Published: |
Animo Repository
2005
|
Online Access: | https://animorepository.dlsu.edu.ph/faculty_research/1052 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | De La Salle University |
Similar Items
-
Predicting high-level student responses using conceptual clustering
by: Legaspi, Roberto S., et al.
Published: (2005) -
A category-based framework of a self-improving instructional planner
by: Legaspi, Roberto S., et al.
Published: (2006) -
A category-based self-improving planning module
by: Legaspi, Roberto S., et al.
Published: (2004) -
MSIP: Agents embodying a category-based learning process for the ITS tutor to self-improve its instructional plans
by: Legaspi, Roberto S., et al.
Published: (2004) -
A category-based framework of a self-improving instructional planner
by: Sison, Raymund C., et al.
Published: (2006)