Using Strongly Typed Genetic Programming for knowledge discovery of course quality from e-learning's web log
Created by W.Langdon from
gp-bibliography.bib Revision:1.7975
- @InProceedings{Yudistira:2013:KST,
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author = "Novanto Yudistira and Sabriansyah Rizqika Akbar and
Achmad Arwan",
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booktitle = "5th International Conference on Knowledge and Smart
Technology (KST, 2013)",
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title = "Using Strongly Typed Genetic Programming for knowledge
discovery of course quality from e-learning's web log",
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year = "2013",
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pages = "11--15",
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month = jan # " 31 2013-" # feb,
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address = "Chonburi, Thailand",
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isbn13 = "978-1-4673-4850-8",
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keywords = "genetic algorithms, genetic programming, LMS,
e-learning, knowledge",
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DOI = "doi:10.1109/KST.2013.6512779",
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abstract = "Learning Management System (LMS) has become the
popular instrument in academic institutions by
providing feasible pedagogical interaction. In the
abundance of registered users take some activities
inside LMS, the result of analysing the quality of
courses becomes remarkable feedback for teachers to
enhance their teaching program via e-learning.
Unexceptionally, mining web server log has been
fascinating area in e-education environment. Our
objective is to find interrelationships knowledge among
e-learning web log's metrics. Strongly Typed Genetic
Programming (STGP) as the cutting the edge technique
for finding accurate rule inductions is used to achieve
the goal. Revealed knowledge may useful for teachers or
academicians to rearrange strategies in the purpose of
improving e-learning usage quality based on the course
activities.",
-
notes = "Also known as \cite{6512779}",
- }
Genetic Programming entries for
Novanto Yudistira
Sabriansyah Rizqika Akbar
Achmad Arwan
Citations