- Info
Structure and Dynamics of Knowledge
Knowledge is a Network
The structure of knowledge can be better described in terms of a
network, as in a semantic network, is the point of departure of the lab's
work. Meaning of any concept that we harbour or any activity that we do
as cognitive agents is generated out of links between
concepts or activities. No node in such a network is meaningful on its
own right, but only by virtue of the links the node has with the
neighbouring nodes. Nothing will be considered a bit of information
unless it is linked to others.
We use this framework to study the problem of conceptual change in
both ontogeny (individual cognitive development) and phylogeny (history
of ideas). By studying the nature of changes in the knowledge network
we wish to capture the dynamics of knowledge, and each snapshot of the
network at any given time as the structure of knowledge. This is how
we are approaching the problem of structure and dynamics of knowledge.
In concrete terms we undertake research and development work in the
gnowledge laboratory, where we are currently investigating on the
following topics.
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Developing GNOWSYS, a node oriented computing system (an official GNU project.).
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Studying the nature of dependency relations in a cognitive system (working paper).
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Using dependency relation to develop a unique roadmap of all knowledge (this project is now online at www.gnowledge.org.) This will eventually develop as an atlas of knowledge. This is our version of knowledge cartography.
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Refined concept mapping for science education, for teaching, learning and assessment.
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Testing the hypothesis that rigor develops by minimal use of relation types,
and not by refining the concept. This is also the basis of our
cognitive development model where agents begin with procedural,
implicit, modular knowledge and develop declarative, explicit and
non-modular knowledge.
- A characterisation of scientific knowledge as procedurally re-described reproducible knowledge.
Refined Concept Mapping (RCM) is an extension of Novakian concept
mapping for representing scientific knowledge. Any concept map can be
turned into an RCM by using well defined and non-redundant linking
phrases (relation names). One of the main assumptions for trusting
this approach is that science is a pursuit to advance rigor (clear
thinking) so that all subjects hold onto the same meaning to the extent
possible.
Some of the tasks that we are currently working using this approach include:
Researchers
Publications:
In Books:
- Heather D. Pfeiffer, Dmitry I. Ignatov, Jonas Poelmans and Nagarjuna Gadiraju (Eds.) (2013). Conceptual Structures for STEM Research and Education, Proceedings of the 20th International Conference on Conceptual Structures, Mumbai, India January 2013. Springer-Verlag, Berlin.
- Nagarjuna G. & Meena Kharatmal (2011): A Proposal
for Developing a Primer for Constructing and Analyzing
Conceptual Structures. In S. Andrews et al. (Eds.), Lecture
Notes in Artificial Intelligence: Vol 6828. Conceptual Structures -
Learning Teaching and Assessment. In International Conference on
Conceptual Structures: Conceptual Structures for Discovering Knowledge
(p. 402-405). Berlin, Germany: Springer-Verlag. Doi: 10.1007/978-3-642-22688-5_36
- Meena Kharatmal & Nagarjuna G. (2010): Introducing rigor in concept maps. In M.
Croitoru, S. Ferre, and D. Lukose (Eds.), Lecture Notes in Artificial
Intelligence: Vol. 6208. International Conference on Conceptual
Structures 2010: From Information to Intelligence (p. 199-202). Berlin,
Germany: Springer-Verlag. Doi: 10.1007/978-3-642-14197-3_22
In Journals:
In Proceedings:
- Meena Kharatmal & Nagarjuna G. (2013): Representing Change Using Concept Maps. In G. Nagarjuna et.al. (Eds.) Proceedings of epiSTEME 5 -- International Conference to Review Research on Science, Technology and Mathematics Education, p. 124-131. India: Cinnamonteal.
Structure and Dynamics of a Model Semantic System
A semantic interpretation has been given to the dependency network
of a free-software operating system. To preserve uniqueness of
operations in this network, the nodes
(software packages) obey an exclusion principle, with no two nodes
being exactly alike in their functionality. From a semantic viewpoint
this implies that the meaning derived from a particular node is defined
uniquely only by its dependency neighbourhood. The frequency
distributions of links in this network follow a scale-free power-law
behaviour for the intermediate nodes, but the extremal nodes exhibit a
saturation behaviour as a result of the finiteness of semantic
possibilities in the network. Across two generations of free-software
network, the saturation properties of the in-degree and the out-degree
distributions are affected oppositely. The primordial nodes of the
out-degree distribution are the foundation of the entire network, and
in a semantic sense, meaning flows from these nodes to the derivative
nodes. In a mature network, semantic variations are more likely in the
weakly-linked derivative nodes than in the primordial nodes (where all
axioms are founded). The notion of a semantic system, based on
dependency relations, and behaving like a scale-free network, has been
extended to understand the structure of knowledge in general.
Read the full paper
Making of an atlas of knowledge
The article is about a new online resource, a collaborative portal
for teachers, which publishes a network of prerequisites for
teaching/learning any concept or an activity. A simple and effective
method of collaboratively constructing teachinglearning sequences is
presented. The special emergent properties of the dependency network
and their didactic and epistemic implications are pointed. The article
ends with an appeal to the global teaching community to contribute
prerequisites of any subject to complete the global roadmap for an
altas being built on similar lines as Wikipedia. The portal is launched
and waiting for community participation at http://www.gnowledge.org.
Read the full paper
Publications
In Journals:
In Proceedings:
- Nagarjuna G. Kharatmal, M., Nair, R. (2010): Building Dependency Network for Teaching-Learning Conceptual Structures. In Polovina, Simon; Andrews, Simon; Hill, Richard; Scharfe, Henrik;
Øhrstrøm, Peter (Eds.) Proceedings of the First Conceptual Structures
– Learning, Teaching and Assessment Workshop (CS-LTA) at the 18th
International Conference on Conceptual Structures (ICCS 2010),
Published by MIMOS BERHAD » Technology Thrust Areas » Knowledge
Technology (ISBN: 978-983-41371-5-1), Kuching, Malaysia.
- Divya,
S., Gajbe A., Nair R., Gajre G., Nagarjuna G., (2009)
GNOWSYS-mode
in Emacs for collaborative construction of knowledge networks in
plain text,
Proceedings
of 8th
International Semantic Web Conference (ISWC),
October
25-28, 2009, Washington, D.C.
- Divya
S., Gajbe A., Nair R., Gajre G. and Nagarjuna G. (2009)
GNOWSYS-mode:
An Emacs based Text Editor for Semantic and Structured. Document
Editing
Proceedings
of Workshop
on Collaborative Construction, Management and Linking of Structured
Knowledge (CK 2009),
October
25-28, 2009, Washington, D.C.
-
Gajbe
A., Nair R. (2009) Node Oriented Knowledge Management, Proceedings
of National Conference on Open Source Software,
25-27 May 2009, C-DAC, Navi Mumbai.
- Kharatmal
M. (2009) SELF-Platform---A
Teacher-Centric Collaborative Authoring System,
Proceedings of National Conference on Open Source Software,
25-27 May 2009, C-DAC, Navi Mumbai.
- Nair
R., Nagarjuna G., Ray A (2009)., Semantic
network in a free-software computer operating system,
Proceedings
of the Annual Conference of Vijnana Parishad of India and National
Symposium on Recent Development in Applicable Mathematics and
Information Technology,
Jaypee Institute of Engineering & Technology, Guna.
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