Using big data techniques for measuring productive friction in mass collaboration online environments

dc.contributor.author	Holtz, Peter
dc.contributor.author	Kimmerle, Joachim
dc.contributor.author	Cress, Ulrike
dc.date.accessioned	2019-06-12T08:17:16Z
dc.date.available	2019-06-12T08:17:16Z
dc.date.issued	2018
dc.identifier.issn	1556-1615
dc.identifier.uri	http://hdl.handle.net/10900/89496
dc.language.iso	en	de_DE
dc.publisher	Springer	de_DE
dc.relation.uri	http://dx.doi.org/10.1007/s11412-018-9285-y	de_DE
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject.ddc	004	de_DE
dc.subject.ddc	370	de_DE
dc.title	Using big data techniques for measuring productive friction in mass collaboration online environments	de_DE
dc.type	Article	de_DE
utue.quellen.id	20190321153956_00255
utue.publikation.seiten	439-456	de_DE
utue.personen.roh	Holtz, Peter
utue.personen.roh	Kimmerle, Joachim
utue.personen.roh	Cress, Ulrike
dcterms.isPartOf.ZSTitelID	International Journal of Computer - Supported Collaborative Learning	de_DE
dcterms.isPartOf.ZS-Issue	4	de_DE
dcterms.isPartOf.ZS-Volume	13	de_DE
utue.fakultaet	07 Mathematisch-Naturwissenschaftliche Fakultät	de_DE