From Learning Object to Learning Cell: A Resource Organization Model for Ubiquitous Learning.
Shengquan Yu, Xianmin Yang, Gang Cheng, Minjuan Wang
Abstract
Shengquan Yu, Xianmin Yang, Gang Cheng, Minjuan Wang
Abstract
This paper presents a new model for organizing learning resources: Learning Cell. This model is open, evolving, cohesive, social, and context-aware. By introducing a time dimension into the organization of learning resources, Learning Cell supports the dynamic evolution of learning resources while they are being used. In addition, by introducing a semantic gene (knowledge ontology) into the model, Learning Cell can flexibly describe the internal structure and external relations of learning resources, allowing the evolution of learning resources to occur in an orderly way. Furthermore, by employing a computational model of a social cognition network, Learning Cell enables not only materialized resource sharing but also the sharing of social cognition networks. Finally, by separately deploying resource structures and resource content in the cloud storage model, Learning Cell achieves context awareness of ubiquitous learning (u-learning) resources. Learning Cell represents a resource aggregation model that is different from the learning object model. It makes up for the defects of existing learning technologies in the following areas: the sharing of process information and social cognition networks, the intelligence of resources, and the evolution of content. Learning Cell provides a theoretical framework of u-learning resource organization.
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This paper presents a new model for organizing learning resources: Learning Cell. This model is open, evolving, cohesive, social, and context-aware. By introducing a time dimension into the organization of learning resources, Learning Cell supports the dynamic evolution of learning resources while they are being used. In addition, by introducing a semantic gene (knowledge ontology) into the model, Learning Cell can flexibly describe the internal structure and external relations of learning resources, allowing the evolution of learning resources to occur in an orderly way. Furthermore, by employing a computational model of a social cognition network, Learning Cell enables not only materialized resource sharing but also the sharing of social cognition networks. Finally, by separately deploying resource structures and resource content in the cloud storage model, Learning Cell achieves context awareness of ubiquitous learning (u-learning) resources. Learning Cell represents a resource aggregation model that is different from the learning object model. It makes up for the defects of existing learning technologies in the following areas: the sharing of process information and social cognition networks, the intelligence of resources, and the evolution of content. Learning Cell provides a theoretical framework of u-learning resource organization.
Key concepts: Computer science, Knowledge management, Learning object, Context (archaeology), Open learning, Collaborative learning, Social learning, Synchronous learning