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