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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:在基于知识的社会中,新一代人们越来越强烈地淹没了继承和新生成的知识的叙述,这对于这些世代来说是可供使用的,或者被他们获得。信息学和计算机科学持续开发新的信息存储设备和多种软件,而不是以往任何时候。然而,有效的信息搜索和处理需要一种信息素养,其特征性地是新的一代,越来越聪明地,没有。国家和国际实证研究证明,当涉及到数字工具的有效和生产性使用时,对信息学的世界不可或缺的算法思考。此外,超级关注现象侵入了年轻一代的日常生活和学习习惯,以更大更大程度。 HY-DE模型的精髓是为了帮助学生的学习过程,以帮助教师对关注阶段的有目的的控制(超级,混合和深受关注)。本研究的一个目的是引入HY-DE模型的新应用,题为数据结构验证器HY-DE模型(DASVA HY-DE)。在介绍性阶段,达斯瓦模型侧重于Hy-de注意力如何在网页搜索中表现出来,以及其产生的信息检索以及超级,混合和深度关注模式的角色是什么在制定计算思维和算法技巧中。在完整的超级关注状态下,执行指定内容的搜索,专注于网页,该网页包含在表格或表的结构中组织的数据。然而,网页的自动化和半自动化转换需要降低超级注意力,导致深层或密切关注。此转换过程的最终结果是结构良好的表格,适用于电子表格,数据库管理和编程中的自动数据检索。原始HY-DE模型的应用将导致我们修改。在DESVA HY-DE模型的高级阶段,学生还可以体验网页的设计和结构,如何支持信息和数据检索,如何成功算法的算法检索,以及如何将学生引导学生结构良好的网页设计理论的应用。通过这种模型,从超重数据收集状态,通过深度和/或混合注意力算法建设和数据分析过程,学生将达到更高级别的超级关注,开发人员状态。

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