000070840 001__ 70840
000070840 005__ 20180608094649.0
000070840 0247_ $$2doi$$a10.1007/978-3-319-58509-3_22
000070840 0248_ $$2sideral$$a101149
000070840 037__ $$aART-2017-101149
000070840 041__ $$aeng
000070840 100__ $$0(orcid)0000-0002-6873-0996$$aSein-Echaluce, María Luisa$$uUniversidad de Zaragoza
000070840 245__ $$aAdaptive and cooperative model of knowledge management in MOOCs
000070840 260__ $$c2017
000070840 5060_ $$aAccess copy available to the general public$$fUnrestricted
000070840 5203_ $$aOne of the characteristics of Massive Open Online Courses (MOOC) is the heterogeneity of their participants’ profiles and, for the most traditional MOOC model, this is an important cause of the low completion rate. The MOOC model presents two apparent antagonistic concepts, globalization and diversity. MOOCs represent globalization (participants have to be adapted to the course) and their participants represent diversity. The authors of this paper argue that both concepts complement each other; that is, a MOOC can adapt the contents and navigation to the diversity of participants; and in turn the participants themselves can increase and improve the contents of the MOOC, through heterogeneous cooperation, to encourage massive learning. To proof it, this paper presents a new model, called ahMOOC, combining the hybrid-MOOC (hMOOC) and the adaptive MOOC (aMOOC). The hMOOC allows integrating characteristics of xMOOCs (based on formal e-training) with cMOOCs (based on informal and cooperative e-training). The aMOOC offers different learning strategies adapted to different learning objectives, profiles, learning styles, etc. of participants. The ahMOOCs continues having a lower dropout rate (such as hMOOC) than the traditional MOOCs. The qualitative analysis show the capacity of participants, with heterogeneous profiles, to create, in a cooperative and massive way, useful knowledge to improve the course and, later, to apply it in their specific work context. The study also shows that participants have a good perception on the capabilities of the ahMOOC to adapt the learning process to their profiles and preferences.
000070840 536__ $$9info:eu-repo/grantAgreement/ES/MINECO/TIN2016-80347-R
000070840 540__ $$9info:eu-repo/semantics/openAccess$$aAll rights reserved$$uhttp://www.europeana.eu/rights/rr-f/
000070840 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/submittedVersion
000070840 700__ $$aFidalgo-Blanco, Ángel
000070840 700__ $$aGarcía-Peñalvo, Francisco J.
000070840 7102_ $$12005$$2595$$aUniversidad de Zaragoza$$bDepartamento de Matemática Aplicada$$cMatemática Aplicada
000070840 773__ $$g10295 (2017), 273-284$$pLect. notes comput. sci.$$tLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)$$x0302-9743
000070840 8564_ $$s515562$$uhttps://zaguan.unizar.es/record/70840/files/texto_completo.pdf$$yPreprint
000070840 8564_ $$s59971$$uhttps://zaguan.unizar.es/record/70840/files/texto_completo.jpg?subformat=icon$$xicon$$yPreprint
000070840 909CO $$ooai:zaguan.unizar.es:70840$$particulos$$pdriver
000070840 951__ $$a2018-06-08-08:26:10
000070840 980__ $$aARTICLE