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008 150903s2012 gw | o |||| 0|eng d
020 _a9783642285868
_99783642285868
024 7 _a10.1007/9783642285868
_2doi
035 _avtls000358803
039 9 _a201509031017
_bVLOAD
_c201405070236
_dVLOAD
_y201402191541
_zstaff
040 _aMX-SnUAN
_bspa
_cMX-SnUAN
_erda
050 4 _aQ342
100 1 _aDaradoumis, Thanasis.
_eeditor.
_9337916
245 1 0 _aIntelligent Adaptation and Personalization Techniques in Computer-Supported Collaborative Learning /
_cedited by Thanasis Daradoumis, Stavros N. Demetriadis, Fatos Xhafa.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg,
_c2012.
300 _axvI, 336 páginas
_brecurso en línea.
336 _atexto
_btxt
_2rdacontent
337 _acomputadora
_bc
_2rdamedia
338 _arecurso en línea
_bcr
_2rdacarrier
347 _aarchivo de texto
_bPDF
_2rda
490 0 _aStudies in Computational Intelligence,
_x1860-949X ;
_v408
500 _aSpringer eBooks
505 0 _aFrom the content: Reuse of data flow designs in complex and adaptive CSCL scripts: A case study -- System orchestration support for a collaborative blended learning flow -- Adaptive Collaboration Scripting with IMS LD -- Extending IMS-LD capabilities: A review, a proposed framework and implementation cases -- Prototype Tools for the Flexible Design of CSCL Activities based on the Adaptation Pattern Perspective. An overview.
520 _aAdaptation and personalization have been extensively studied in CSCL research community aiming to design intelligent systems that adaptively support eLearning processes and collaboration. Yet, with the fast development in Internet technologies, especially with the emergence of new data technologies and the mobile technologies, new opportunities and perspectives are opened for advanced adaptive and personalized systems. Adaptation and personalization are posing new research and development challenges to nowadays CSCL systems. In particular, adaptation should be focused in a multi-dimensional way (cognitive, technological, context-aware and personal). Moreover, it should address the particularities of both individual learners and group collaboration. As a consequence, the aim of this book is twofold. On the one hand, it discusses the latest advances and findings in the area of intelligent adaptive and personalized learning systems. On the other hand it analyzes the new implementation perspectives for intelligent adaptive learning and collaborative systems that are brought by the advances in scripting languages, IMS LD, educational modeling languages and learning activity management systems. Given the variety of learning needs as well as the existence of different technological solutions, the book exemplifies the methodologies and best practices through several case studies and adaptive real-world collaborative learning scenarios, which show the advancement in the field of analysis, design and implementation of intelligent adaptive and personalized systems.
590 _aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700 1 _aDemetriadis, Stavros N.
_eeditor.
_9345088
700 1 _aXhafa, Fatos.
_eeditor.
_9313917
710 2 _aSpringerLink (Servicio en línea)
_9299170
776 0 8 _iEdición impresa:
_z9783642285851
856 4 0 _uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-3-642-28586-8
_zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
942 _c14
999 _c305956
_d305956