Paper Info
Title
Fading and Deepening: The Next Steps for Andes and other Model-Tracing Tutors
Abstract
Model tracing tutors have been quite successful in teaching cognitive skills; however, they still are not as competent as expert human tutors. We propose two ways to improve model tracing tutors and in particular the Andes physics tutor. First, tutors should fade their scaffolding. Although most model tracing tutors have scaffolding that needs to be gradually removed (faded), Andes' scaffolding is already "faded," and that causes student modeling difficulties that adversely impact its tutoring. A proposed solution to this problem is presented. Second, tutors should integrate the knowledge they currently teach with other important knowledge in the task domain in order to promote deeper learning. Several types of deep learning are discussed, and it is argued that natural language processing is necessary for encouraging such learning. A new project, Atlas, is developing natural language based enhancements to model tracing tutors that are intended to encourage deeper learning.
Year
DOI
Venue
2000
10.1007/3-540-45108-0_51
Intelligent Tutoring Systems
Keywords
Field
DocType
andes physics tutor,next steps,important knowledge,deeper learning,proposed solution,cognitive skill,natural language processing,expert human tutor,natural language,deep learning,model-tracing tutors,new project,cognitive skills
TUTOR,Computer science,Knowledge management,Natural language,Cognitive skill,Graphical user interface,Mathematics education,Artificial intelligence,Deep learning,Tracing
Conference
Volume
ISSN
ISBN
1839
0302-9743
3-540-67655-4
Citations 
PageRank 
References 
26
4.28
12
Authors
12
Name
Order
Citations
PageRank
Kurt VanLehn12352417.44
Reva Freedman26916.18
Pamela W. Jordan370983.97
R. Charles Murray415623.25
Remus Osan5427.28
Michael A. Ringenberg621122.20
Rosé Carolyn72126222.80
Kay Schulze829528.07
Robert Shelby929528.07
Donald Treacy1029528.07
Anders Weinstein1130430.26
Mary Wintersgill1229528.07