- author = "C. Romero and S. Ventura and C. Hervas and P. Gonzalez",
- title = "Rule discovery in Web-based educational systems using Grammar-Based Genetic Programming",
- booktitle = "Data Mining VI: Data Mining, Text Mining and their Business Applications",
- publisher = "WitPress",
- year = "2005",
- editor = "A. Zanasi and C. A. Brebbia and N. Ebecken",
- volume = "35",
- series = "Information and Communication Technologies",
- pages = "113--126",
- keywords = "genetic algorithms, genetic programming, web usage mining, rule discovery, web-based adaptive education, evolutionary algorithms, grammar-based genetic programming",
- ISBN = "1-84564-017-9",
-
URL = "
http://library.witpress.com/pages/listPapers.asp?q_bid=327",
-
DOI = "
doi:10.2495/DATA050211",
-
abstract = "This paper describes the use of data mining methods in
an e-learning system for providing feedback to
courseware authors.
The discovered information is presented in the form of prediction rules since these are highly comprehensible and they show important relationships among the presented data.
The rules will be used to improve courseware, particularly Adaptive Systems for Web-based Education (ASWE). We propose to use evolutionary algorithms as the rule discovery methods, concretely Grammar-Based Genetic Programming (GBGP) with multi-objective optimisation techniques. We have developed a specific tool named EPRules (Education Prediction Rules) to facilitate and simplify the knowledge discovery process for usage data in web-based education systems.",
- size = "10 pages",
