000 03690nam a22004695i 4500
001 978-3-642-28586-8
003 DE-He213
005 20140220083313.0
007 cr nn 008mamaa
008 120309s2012 gw | s |||| 0|eng d
020 _a9783642285868
_9978-3-642-28586-8
024 7 _a10.1007/978-3-642-28586-8
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
082 0 4 _a006.3
_223
100 1 _aDaradoumis, Thanasis.
_eeditor.
245 1 0 _aIntelligent Adaptation and Personalization Techniques in Computer-Supported Collaborative Learning
_h[electronic resource] /
_cedited by Thanasis Daradoumis, Stavros N. Demetriadis, Fatos Xhafa.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg,
_c2012.
300 _aXVI, 336p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aStudies in Computational Intelligence,
_x1860-949X ;
_v408
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.
650 0 _aEngineering.
650 0 _aArtificial intelligence.
650 1 4 _aEngineering.
650 2 4 _aComputational Intelligence.
650 2 4 _aArtificial Intelligence (incl. Robotics).
700 1 _aDemetriadis, Stavros N.
_eeditor.
700 1 _aXhafa, Fatos.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783642285851
830 0 _aStudies in Computational Intelligence,
_x1860-949X ;
_v408
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-642-28586-8
912 _aZDB-2-ENG
999 _c102842
_d102842