Knowledge Discovery with Genetic Programming for Providing Feedback to Courseware Authors
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- @Article{Romero:2004:umuai,
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author = "Cristobal Romero and Sebastian Ventura and
Paul {De Bra}",
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title = "Knowledge Discovery with Genetic Programming for
Providing Feedback to Courseware Authors",
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journal = "User Modeling and User-Adapted Interaction",
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year = "2004",
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volume = "14",
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number = "5",
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pages = "425--464",
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month = jan,
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keywords = "genetic algorithms, genetic programming, adaptive
system for web-based education, data mining,
evolutionary algorithms, grammar-based genetic
programming, prediction rules",
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ISSN = "0924-1868",
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DOI = "doi:10.1007/s11257-004-7961-2",
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abstract = "We introduce a methodology to improve Adaptive Systems
for Web-Based Education. This methodology uses
evolutionary algorithms as a data mining method for
discovering interesting relationships in students'
usage data. Such knowledge may be very useful for
teachers and course authors to select the most
appropriate modifications to improve the effectiveness
of the course. We use Grammar-Based Genetic Programming
(GBGP) with multi-objective optimization techniques to
discover prediction rules. We present a specific data
mining tool that can help non-experts in data mining
carry out the complete rule discovery process, and
demonstrate its utility by applying it to an adaptive
Linux course that we developed.",
- }
Genetic Programming entries for
Cristobal Romero Morales
Sebastian Ventura
Paul De Bra
Citations