A Data Mining Approach to Reveal Representative Collaboration Indicators in Open Collaboration Frameworks [Konferenzbericht] Paper presented at the International Conference on Educational Data Mining (EDM) (2nd, Cordoba, Spain, Jul 1-3, 2009).

Autor/inn/en	Anaya, Antonio R.; Boticario, Jesus G.
Institution	International Working Group on Educational Data Mining
Titel	A Data Mining Approach to Reveal Representative Collaboration Indicators in Open Collaboration Frameworks [Konferenzbericht] Paper presented at the International Conference on Educational Data Mining (EDM) (2nd, Cordoba, Spain, Jul 1-3, 2009).
Quelle	(2009), (10 Seiten) PDF als Volltext kostenfreie Datei Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Monographie
Schlagwörter	Data Analysis; Cooperative Learning; College Students; Adult Students; Distance Education; Electronic Learning; Computer Mediated Communication; Interaction; Multivariate Analysis; Mathematics; Foreign Countries; Spain + Suchen Sie Ihr Suchwort? Auswertung; Kooperatives Lernen; Collegestudent; Adult; Adults; Student; Students; Erwachsenenalter; Studentin; Schüler; Schülerin; Distance study; Distance learning; Fernunterricht; Computerkonferenz; Interaktion; Multivariate Analyse; Mathematik; Ausland; Spanien
Abstract	Data mining methods are successful in educational environments to discover new knowledge or learner skills or features. Unfortunately, they have not been used in depth with collaboration. We have developed a scalable data mining method, whose objective is to infer information on the collaboration during the collaboration process in a domain-independent way and to improve collaboration process management and learning in an open collaborative educational web environment. Thus, we used statistical indicators of learner's interactions in forums as the data source and a clustering algorithm to classify the data according to learner's collaboration. We showed the information on learner's collaboration to the tutor and learners to help them with collaboration process management. The experimental results support this method. (Contains 1 figure and 2 tables.) [For the complete proceedings, "Proceedings of the International Conference on Educational Data Mining (EDM) (2nd, Cordoba, Spain, July 1-3, 2009)," see ED539041.] (As Provided).
Anmerkungen	International Working Group on Educational Data Mining. Available from: International Educational Data Mining Society. e-mail: admin@educationaldatamining.org; Web site: http://www.educationaldatamining.org
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10