A neuro-fuzzy approach to detect student's motivation

dc.contributor.author	Σταθακοπούλου, Ρεγγίνα	el
dc.contributor.author	Σαμαράκου, Μαρία	el
dc.contributor.author	Γρηγοριάδου, Μαρίλια	el
dc.contributor.author	Μαγούλας, Γεώργιος Δ.	el
dc.date.accessioned	2015-04-26T10:34:50Z
dc.date.issued	2015-04-26
dc.identifier.uri	http://hdl.handle.net/11400/8976
dc.rights	Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/us/	*
dc.source	http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=1357377&abstractAccess=no&userType=inst	en
dc.subject	Student
dc.subject	World Wide Web
dc.subject	Φοιτητής
dc.subject	Διαδίκτυο
dc.title	A neuro-fuzzy approach to detect student's motivation	en
heal.type	conferenceItem
heal.generalDescription	Proceedings of the (ICALT 2004) 4th IEEE International Conference on Advanced Learning Technologies. Joensuu, Finland, 30th August-1st September 2004. IEEE Computer Society Press. pp. 71-75.	en
heal.classification	Technology
heal.classification	Computer science
heal.classification	Τεχνολογία
heal.classification	Πληροφορική
heal.classificationURI	http://zbw.eu/stw/descriptor/10470-6
heal.classificationURI	http://data.seab.gr/concepts/77de68daecd823babbb58edb1c8e14d7106e83bb
heal.classificationURI	N/A-Τεχνολογία
heal.classificationURI	N/A-Πληροφορική
heal.keywordURI	http://id.loc.gov/authorities/subjects/sh95000541
heal.dateAvailable	10000-01-01
heal.language	en
heal.access	forever
heal.recordProvider	Τ.Ε.Ι Αθήνας. Σχολή Τεχνολογικών Εφαρμογών. Τμήμα Μηχανικών Ενεργειακής Τεχνολογίας Τ.Ε.	el
heal.publicationDate	2004
heal.bibliographicCitation	Stathacopoulou R., Samarakou M., Grigoriadou M. and Magoulas G. D. (2004). A neuro-fuzzy approach to detect student's motivation. In the 4th IEEE International Conference on Advanced Learning Technologies. Joensuu, Finland, 30th August-1st September 2004. IEEE Computer Society Press.	en
heal.abstract	In this paper the fuzzy knowledge representation of a neural network-based fuzzy model is presented. The model is used to assess student's motivational state in a discovery learning environment. Student?s observable behavior and motivational factors are described with linguistic variables. The inputs of the model are tailored from real students? data, with the assistance of a group of expert teachers. Results of our preliminary study were encouraging, since data obtained from real students? log files, have been successfully used to form the membership functions that assign membership degrees to the linguistic values of the linguistic variables.	en
heal.publisher	IEEE Computer Society Press	en
heal.fullTextAvailability	false
heal.conferenceName	International Conference on Advanced Learning Technologies	en
heal.conferenceItemType	full paper