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001			102410
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005			20230102113040.0
007			cr nn 008mamaa
008			171027s2018 gw | s |||| 0|eng d
020			_a9783319679280
024	7		_a10.1007/978-3-319-67928-0 _2doi
050		4	_aLB1028.43 _bM668 2018 EB
100	1		_aMontebello, Matthew _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _1http://viaf.org/viaf/1209151304644549460001/
245	1	0	_aAI Injected e-Learning _bThe Future of Online Education _cby Matthew Montebello.
264		1	_aCham _bSpringer International Publishing _c2018
300			_a1 recurso en línea (XIX, 86 páginas 6 ilustraciones)
347			_atext file _bPDF
490	0		_aStudies in Computational Intelligence _x1860-949X _v745
505	0		_aIntroduction -- e-Learning so far -- MOOCs, Crowdsourcing and Social Networks -- User Profiling and Personalisation -- Personal Learning Networks, Portfolios and Environments -- Customised e-Learning -- Looking Ahead.
520	3		_aThis book reviews a blend of artificial intelligence (AI) approaches that can take e-learning to the next level by adding value through customization. It investigates three methods: crowdsourcing via social networks; user profiling through machine learning techniques, and personal learning portfolios using learning analytics. Technology and education have drawn closer together over the years as they complement each other within the domain of e-learning, and different generations of online education reflect the evolution of new technologies as researcher and developers continuously seek to optimize the electronic medium to enhance the effectiveness of e-learning. Artificial intelligence (AI) for e-learning promises personalized online education through a combination of different intelligent techniques that are grounded in established learning theories while at the same time addressing a number of common e-learning issues. This book is intended for education technologists and e-learning researchers as well as for a general readership interested in the evolution of online education based on techniques like machine learning, crowdsourcing, and learner profiling that can be merged to characterize the future of personalized e-learning.
650		7	_aInteligencia artificial _xAspectos educativos _2embne
776	0	8	_iEdición impresa: _z9783319679273
776	0	8	_iEdición impresa: _z9783319679297
776	0	8	_iEdición impresa: _z9783319885131
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-319-67928-0 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
490	0		_aEngineering (Springer-11647)
988			_aEBSPRINGER_2018
998			_b12/2018 _dz _ek _feng _ggw _h0
999			_c102410 _d102410 _x1