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Generation as method for explorative learning in computer science education

机译:生成作为计算机科学教育中探索性学习的方法

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The use of generic and generative methods for the development and application of interactive educational software is a relatively unexplored area in industry and education. Advantages of generic and generative techniques are, among other things, the high degree of reusability of systems parts and the reduction of development costs. Furthermore, generative methods can be used for the development or realization of novel learning models. In this paper, we discuss such a learning model that propagates a new way of explorative learning in computer science education with the help of generators. A realization of this model represents the educational software GANIFA on the theory of generating finite automata from regular expressions. In addition to the educational system's description, we present an evaluation of this system.
机译:在交互式教育软件的开发和应用中使用通用和生成方法在工业和教育领域是一个相对未开发的领域。通用技术和生成技术的优势尤其包括系统部件的高度可重用性和降低开发成本。此外,生成方法可用于开发或实现新型学习模型。在本文中,我们讨论了这样一种学习模型,该模型在生成器的帮助下传播了计算机科学教育中探索性学习的新方法。该模型的实现代表了教育软件GANIFA,它基于从正则表达式生成有限自动机的理论。除了对教育系统的描述之外,我们还对该系统进行了评估。

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