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:1.3872

@InProceedings{Yudistira:2013:KST,
  author =       "Novanto Yudistira and Sabriansyah Rizqika Akbar and 
                 Achmad Arwan",
  booktitle =    "5th International Conference on Knowledge and Smart
                 Technology (KST, 2013)",
  title =        "Using Strongly Typed Genetic Programming for knowledge
                 discovery of course quality from e-learning's web log",
  year =         "2013",
  pages =        "11--15",
  month =        jan # " 31 2013-" # feb,
  address =      "Chonburi, Thailand",
  isbn13 =       "978-1-4673-4850-8",
  keywords =     "genetic algorithms, genetic programming, LMS,
                 e-learning, knowledge",
  DOI =          "doi:10.1109/KST.2013.6512779",
  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