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Adaptation 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.
Adaptation 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.
Intelligent Systems and Learning Data Analytics in Online Education
provides novel artificial intelligence (AI) and analytics-based
methods to improve online teaching and learning. This book
addresses key problems such as attrition and lack of engagement in
MOOCs and online learning in general. This book explores the state
of the art of artificial intelligence, software tools and
innovative learning strategies to provide better understanding and
solutions to the various challenges of current e-learning in
general and MOOC education. In particular, Intelligent Systems and
Learning Data Analytics in Online Education shares stimulating
theoretical and practical research from leading international
experts. This publication provides useful references for
educational institutions, industry, academic researchers,
professionals, developers, and practitioners to evaluate and apply.
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