Knowledge Discovery with Genetic Programming for Providing Feedback to Courseware Authors

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@Article{Romero:2004:umuai,
  author =       "Cristobal Romero and Sebastian Ventura and 
                 Paul {De Bra}",
  title =        "Knowledge Discovery with Genetic Programming for
                 Providing Feedback to Courseware Authors",
  journal =      "User Modeling and User-Adapted Interaction",
  year =         "2004",
  volume =       "14",
  number =       "5",
  pages =        "425--464",
  month =        jan,
  keywords =     "genetic algorithms, genetic programming, adaptive
                 system for web-based education, data mining,
                 evolutionary algorithms, grammar-based genetic
                 programming, prediction rules",
  ISSN =         "0924-1868",
  DOI =          "doi:10.1007/s11257-004-7961-2",
  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