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Knowledge based higher education

机译:知识为本的高等教育

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While data and/or information based education was built on pedagogic, psychology, philosophy of science and didactic disciplines, the new dimension of knowledge based education will involve new disciplines such as Knowledge Management, Epistemology, Systems Theory, Artificial Knowledge Management Systems, Value Theory and Theory of Measurement. It is often assumed that data, information and knowledge are depicted as a pyramid. The data, the most plentiful type, are at the bottom, information, produced from data, is above it and knowledge, produced from information through the hard work of refining or mining, above it. This schema satisfies specific needs of an organisation of warehouse data systems but it does not explain the role of these objects in the educational process. In education, the distinctions among data, information and knowledge need to be distinguished from the complex pedagogical point of view. Knowledge is the engine asking for more information and more data. Knowledge life cycle produces more information, more information asks for more data - that is: there is "just information". Data, information and knowledge can be considered as object oriented measures assigned to real objects (entities). The following measures can be assigned to the objects: Measure of the zero order - name. Measure of the first order - data. Measure of the second order - information. Metrics of the third order - knowledge. Knowledge based curriculum involves knowledge into study plans and it considers knowledge as a distinctive part of study. Knowledge becomes the engine starting cycle of new information acquisition, reproduction and integration. The following problems have to be solved in building of knowledge based curriculum: Methodology and organisation of educational process. Technical support for knowledge based education. Evaluation and assessment of the process.
机译:虽然基于数据和/或信息的教育建立在教学,心理学,科学哲学和教学学科的基础上,但基于知识的教育的新领域将涉及新学科,例如知识管理,认识论,系统论,人工知识管理系统,价值论和测量理论。通常认为,数据,信息和知识被描述为金字塔。数据是最丰富的类型,位于底部,由数据产生的信息位于数据之上,而知识则是通过精炼或挖掘的辛苦工作从信息中产生的。此架构满足仓库数据系统组织的特定需求,但未解释这些对象在教育过程中的作用。在教育中,需要从复杂的教学法角度区分数据,信息和知识之间的区别。知识是要求更多信息和更多数据的引擎。知识生命周期产生更多的信息,更多的信息需要更多的数据-即:“公正的信息”。数据,信息和知识可以视为分配给实际对象(实体)的面向对象的度量。可以为对象分配以下度量:零阶度量-名称。一阶度量-数据。二阶度量-信息。三阶指标-知识。基于知识的课程将知识纳入学习计划,并将知识视为学习的独特部分。知识成为新信息获取,复制和整合的引擎启动周期。建立基于知识的课程时必须解决以下问题:方法论和教育过程的组织。为基于知识的教育提供技术支持。评估和评估过程。

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