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Sabitha, A. Sai; Mehrotra, Deepti; Bansal, Abhay – Education and Information Technologies, 2016
e-Learning industry is rapidly changing and the current learning trends are based on personalized, social and mobile learning, content reusability, cloud-based and talent management. The learning systems have attained a significant growth catering to the needs of a wide range of learners, having different approaches and styles of learning. Objects…
Descriptors: Multivariate Analysis, Electronic Learning, Cognitive Style, Knowledge Management
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Di Bitonto, Pierpaolo – International Journal of Distance Education Technologies, 2010
The success of communities generally implies both growth of the participants (and thus of their contributions), and an increasing array of services offered. For this reason, it is often difficult for new users to fully understand the potential of the community, while for expert users it becomes difficult both to manage the resources available in…
Descriptors: Individualized Instruction, Knowledge Management, Cognitive Style, Computer Assisted Instruction
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Knauf, Rainer; Sakurai, Yoshitaka; Tsuruta, Setsuo; Jantke, Klaus P. – Journal of Educational Computing Research, 2010
University education often suffers from a lack of an explicit and adaptable didactic design. Students complain about the insufficient adaptability to the learners' needs. Learning content and services need to reach their audience according to their different prerequisites, needs, and different learning styles and conditions. A way to overcome such…
Descriptors: Prerequisites, College Instruction, Educational Experiments, Cognitive Style
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Silva, Luciano; Mustaro, Pollyana N.; Stringhini, Denise; Silveira, Ismar F. – Electronic Journal of e-Learning, 2006
Ideally, learning resources should be built over a shared pool of fine reusable granular learning objects. However, in order to avoid contextual lacks, dynamic creation of such resources would mostly rely on the conceptual relationships among learning objects inside a repository. These conceptual relationships, as well as the learning objects…
Descriptors: Resource Units, Metadata, Cognitive Style, Concept Mapping
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Maule, R. William – Internet Research, 1998
Develops frameworks to help Internet media designers address end-user information presentation preferences by advancing structures for assessing metadata design variables which are then linked to user cognitive styles. An underlying theme is that artificial intelligence (AI) methodologies may be used to help automate the Internet media design…
Descriptors: Artificial Intelligence, Cognitive Mapping, Cognitive Style, Design Requirements