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The distributional learning theory or learning of probability distribution is a framework in computational learning theory. It has been proposed from Michael Kearns , Yishay Mansour , Dana Ron , Ronitt Rubinfeld , Robert Schapire and Linda Sellie in 1994 [ 1 ] and it was inspired from the PAC-framework introduced by Leslie Valiant .
The authors wanted to design a model which explained each component of the teaching and learning process while at the same time examining the relationship between the media and instruction. The model consists of ten elements and was constructed for teachers who both design and deliver instruction. [ 2 ]
Their work has focussed on the architecture of learning networks - aiming to identify arrangements of tasks, tools and people that contribute to successful learning networks. Some conclusions from this work have been published in The architecture of productive learning networks, which also includes a chapter on the history of networked learning ...
ADL uses the term “distributed learning” broadly, to refer to all network-centric learning technologies and their corresponding best practices for their use. Similarly, ADL uses the term “learning” to include education, training, operational performance support, and other forms of ad hoc, just-in-time, or self-directed learning. [10]
Pavlis Korres (2010), in her instructional model (ESG Framework), [10] has proposed an expanded version of ADDIE, named ADDIE+M, where Μ=Maintenance of the Learning Community Network after the end of a course. The Maintenance of the Learning Community Network is a modern educational process that supports the continuous educational development ...
Network planning and design is an iterative process, encompassing topological design, network-synthesis, and network-realization, and is aimed at ensuring that a new telecommunications network or service meets the needs of the subscriber and operator. [1] The process can be tailored according to each new network or service. [2]
The Hierarchical internetworking model is a three-layer model for network design first proposed by Cisco in 1998. [1] The hierarchical design model divides enterprise networks into three layers: core, distribution, and access.
The domain model (also known as the cognitive model or expert knowledge model) is built on a theory of learning, such as the ACT-R theory which tries to take into account all the possible steps required to solve a problem. More specifically, this model "contains the concepts, rules, and problem-solving strategies of the domain to be learned.