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Data-structure validator: An application of the HY-DE model

机译:数据结构验证器:HY-DE模型的应用

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In knowledge-based societies new generations are flooded more and more intensely with narratives of inherited and newly generated knowledge, which is simply accessible for these generations, or to be acquired by them. Informatics and computer sciences are continuously developing new information-storage devices and a multitude of software more rapidly than ever. However, effective information search and processing require an information literacy which the new generations characteristically, and more and more demonstrably, do not have. National and international empirical research proves that the algorithmic thinking of the younger generations, which is indispensable for the world of informatics, is underdeveloped when it comes to the effective and productive use of digital tools. Moreover, the phenomenon of hyper attention invades the everyday life and the learning habits of the younger generation to a greater and greater degree. The essence of the HY-DE model is to aid the students' learning process with the help of the teacher's purposeful control of the phases of attention (hyper, mixed and deep attention). One aim of the present study is to introduce a new application of the HY-DE model, entitled Data-Structure Validator HY-DE model (DaSVa HY-DE). In the introductory phase, the DaSVa model focuses on how the HY-DE attention-divisions manifest themselves in webpage-search as well as in the information retrieval that it yields, and what the roles of the hyper, mixed, and deep attention modes are in the development of computational thinking and algorithmic skills. In the full hyper attention status the search for specified contents is carried out, focusing on webpages which consist of data organized in table or table-like structures. The automated and semi-automated conversion of the webpages however requires the decreasing of hyper attention leading to deep or mixed attention. The final result of this conversion process is/are well-structured table(s) suitable for automated data retrieval in spreadsheets, database management, and programming. The application of the original HY-DE model would lead us to its modification. In the advanced phase of the DaSVa HY-DE model the students can also experience how the webpages are designed and structured, how they support information and data retrieval, how successful the algorithmic based retrieval can be, and how the approach would lead students to the application of the theory of well-structured webpage design. With this model, from the hyper attention data collection status, through a deep and/or mixed attention algorithm building and data analyzing process, students would reach a higher-level hyper attention, the developer status.
机译:在以知识为基础的社会中,新世代越来越多地被继承和新生成的知识的叙事所淹没,这对于这些世代来说都是可以轻易获得的,或者被他们所吸收。信息学和计算机科学正在以比以往更快的速度持续开发新的信息存储设备和众多软件。然而,有效的信息搜索和处理需要信息素养,这是新一代特征,并且越来越明显地没有。国内外的经验研究证明,在有效和高效地使用数字工具方面,对于信息学世界来说不可或缺的年轻一代算法思维。此外,过度注意的现象越来越多地侵袭年轻一代的日常生活和学习习惯。 HY-DE模型的本质是在老师有目的地控制注意力阶段(超级,混合和深层注意力)的帮助下,帮助学生进行学习。本研究的一个目的是介绍HY-DE模型的新应用,名为数据结构验证器HY-DE模型(DaSVa HY-DE)。在入门阶段,DaSVa模型专注于HY-DE注意区如何在网页搜索以及它产生的信息检索中表现出来,以及超注意,混合注意和深注意模式的作用是什么在计算思维和算法技能方面的发展。在全神贯注状态下,将搜索特定内容,重点放在由表或表状结构组织的数据组成的网页上。但是,网页的自动和半自动转换需要减少过度关注,从而导致深度关注或混合关注。此转换过程的最终结果是结构良好的表,适用于电子表格中的自动数据检索,数据库管理和编程。原始HY-DE模型的应用将导致我们对其进行修改。在DaSVa HY-DE模型的高级阶段,学生还可以体验网页的设计和结构方式,他们如何支持信息和数据检索,基于算法的检索如何成功以及该方法如何将学生引向结构化网页设计理论的应用。使用此模型,从超注意力数据收集状态到深度和/或混合注意力算法的构建和数据分析过程,学生将达到更高级别的超注意力,即开发人员状态。

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