Demo: GetSmart
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| What
is in the GetSmart System?
How
do you build a concept map in GetSmart?
Would
you like to see some interesting examples?
| Research
Goal |
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GetSmart
is intended to integrate curriculum
support, search functions, and knowledge
visualization tools in a digital library,
learning-oriented environment.
The
National Science Digital Library (NSDL),
launched in December 2002, is emerging
as a center of innovation in digital
libraries as applied to education.
As a part of this extensive project,
the GetSmart system was created to
apply knowledge management techniques
in a learning environment. The design
of the system is based on an analysis
of learning theory and the information
search process. Its key notion is
the integration of search tools and
curriculum support with concept mapping.
More than 100 students at the
University
of Arizona and Virginia Polytechnic Institute used the system in the fall of 2002.
A database of more than one thousand
student-prepared concept maps has
been collected with more than forty
thousand relationships expressed in
semantic, graphical, node-link representations.
Preliminary analysis of the collected
data is revealing interesting knowledge
representation patterns.
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| Funding |
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NSF
National SMETE Digital Library: “Intelligent
Collection Services for and about
Educators and Students: Logging, Spidering,
Analysis and Visualization”
Award No. DUE-0121741, Program
7444. September 2001-August 2003.
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| Acknowledgements |
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Related
Projects:
We would like to
thank the NSF for supporting this
project.
We would also like
to thank Rao Shen in Virginia, the
GetSmart team and the other members
of the Artificial Intelligence Lab
at the
University of
Arizona
who developed modules used in this
system.
User evaluation surveys
have been conducted with the help
of Dr. Lillian Cassel
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| Approach
& Methodology |
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Concept
mapping has been identified in many
educational psychology studies as
a useful technique to enhance learning.
Visual node and link semantic graphs
have been applied to numerous knowledge-related
lines of investigation including:
as an assistant tool for individual
learning (Novak, 1984), as an evaluation
of learning effectiveness (Stanford
Education Assessment Laboratory, 1992),
as a group communication tool (Trochim,
1989), Organizing hypermedia resources
using concept map (Carnot et al.,
2000), Online collaboration through
concept mapping (Gains et al. 1995),
etc
. The GetSmart system
brings together basic curriculum functions,
concept mapping and advanced information
retrieval techniques in a web-based
learning environment.
Current
lines of research include the provision
of concept maps as OAI objects, analysis
of the relationship of source texts
to human-drawn concept maps, and the
categorization of human-created link
labels into semantically similar link
types. One important goal is to support
the accumulation of knowledge using
matching and merging algorithms and
to increase the usefulness of text
resources by creating concept maps
from text.
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| Team
Members |
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| Publications |
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B.
Marshall, H. Chen, T. Madhusudan, "Matching
Knowledge Elements in Concept Maps
using a Similarity Flooding Algorithm",
Decision Support Systems, Vol.42, No.3,
Dec 2006, Pages 1290-1306., October 2005
Byron
Marshall, Yiwen Zhang, Hsinchun
Chen, Ann Lally, Rao Shen, Edward
Fox and Lillian Cassel “Knowledge
Management and E-Learning: the GetSmart
Experience” Presented at the
Third ACM and IEEE Joint Conference
on Digital Libraries (JCDL-2003),
Houston, May 2003.
“Element Matching
in Concept Maps”, Byron Marshall,
Therani Madhusudan , Accepted, to
be presented at the fourth ACM and
IEEE Joint Conference on Digital Libraries
(JCDL-2004) June 7-11, Tucson, AZ
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