在线教育众筹的技术机制与学习神经元

发布时间：2019-03-11 15:42

【摘要】：在线教育已经成为终身教育背景下的主流教育形式之一。成功的在线教育必然是那种实现了基于知识产品的、长期稳定的、以学习者为中心的个性化教育服务。由此,在线教育的知识产品开发必然要追求模块化、可定制、快速进化等特点。但目前在线教育的产品模块化没有真正达到可聚合的水平,也没有达到可定制和快速进化的水平。摆脱这些困境的办法之一是教育众筹,即由大众中的能手创建可聚合的知识产品模块,由专业团队将它们组装成高质量的在线课程并提供学习支持服务。这需要在线教育产品开发模式与产品技术机制的革新。学习神经元(Learning Neuron,简称LN)是一种能够提供富交互学习情境、旨在完整达到特定学习目标、可记录学习过程、可识别学习行为的可互联微型学习系统。它具有知识建模图属性,可实现跨平台互联聚合;它在客户端设有学习行为感知器,在服务器端设有学习分析引擎,可以解决学习分析和定制的问题。将学习神经元作为基础模块,在技术机制上可实现在线教育的众筹,以形成快速进化的状态。我们开发的一个简单学习神经元,初步检验了这种技术机制的可行性。
[Abstract]:Online education has become one of the mainstream forms of education under the background of lifelong education. Successful online education must be a long-term, stable, learner-centered personalized education service based on knowledge products. Therefore, the knowledge product development of online education must pursue the characteristics of modularization, customizability and rapid evolution. However, the modularization of online education products has not really reached the level of aggregation, nor has it reached the level of customizability and rapid evolution. One way out of these dilemmas is to educate crowdfunding by creating aggregable knowledge product modules, assembled by professional teams into high-quality online courses and providing learning support services. This requires on-line education product development model and product technology mechanism innovation. Learning neuron (Learning Neuron, (LN) is a kind of interconnected micro-learning system, which can provide rich interactive learning situation, achieve specific learning goals, record learning process and identify learning behavior. It has the attribute of knowledge modeling diagram, which can realize cross-platform interconnection and aggregation, and it has a learning behavior perceptron on the client side and a learning analysis engine on the server side, which can solve the problems of learning analysis and customization. Learning neurons are used as basic modules to realize on-line education crowdfunding in technical mechanism to form a state of rapid evolution. We developed a simple learning neuron and preliminarily tested the feasibility of this technical mechanism.
【作者单位】：北京师范大学教育技术学院;甘肃省白银市第八中学;北京一日一思科技有限公司;
【分类号】：G434

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