Developing Computational Thinking Skills With Algorithm-Driven Spreadsheeting

The paper presents the details of a four-year project to test the effectiveness of teaching spreadsheeting with spreadsheet programming, instead of the traditional, widely accepted surface approach methods. The novel method applied in the project, entitled Sprego (Spreadsheet Lego), is a concept-bas...

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Main Authors: Maria Csernoch, Piroska Biro, Janos Math
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9606871/
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author Maria Csernoch
Piroska Biro
Janos Math
author_facet Maria Csernoch
Piroska Biro
Janos Math
author_sort Maria Csernoch
collection DOAJ
description The paper presents the details of a four-year project to test the effectiveness of teaching spreadsheeting with spreadsheet programming, instead of the traditional, widely accepted surface approach methods. The novel method applied in the project, entitled Sprego (Spreadsheet Lego), is a concept-based problem-solving approach adapted from the didactics of other sciences and computer programming. In the experimental group contextualized, real-world programming problems are presented in a spreadsheet environment. A semi-unplugged data-driven analysis is carried out based on each problem, which is followed by the building of a feasible algorithm, expressed by natural language expressions. The coding is completed in the following step by applying a limited number of spreadsheet (Sprego) functions, multilevel, and array formulas. The final steps of the process are discussion and debugging. On the other hand, classical, tool-centered approaches are applied in the control groups. Our research reveals that the traditional surface approach methods for teaching spreadsheeting do not provide long lasting, reliable knowledge which would provide students and end-users with effective problem-solving strategies, while Sprego does. Beyond this finding, the project proves that Sprego supports schema construction and extended abstraction, which is one of the major hiatus points of traditional surface navigation methods. The project also reveals that developing computational thinking skills should not be downgraded, and the misconceptions of self-taught end-users and user-friendly applications should be reconsidered, especially their application in educational environments. Gaining effective computer problem-solving skills and knowledge-transfer abilities is not magic, but a time-consuming process which requires consciously developed and effective methods, and teachers who accept the incremental nature of the sciences.
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spelling doaj.art-1b1b7c419d024c11928305cddfca26c22022-12-22T04:24:44ZengIEEEIEEE Access2169-35362021-01-01915394315395910.1109/ACCESS.2021.31267579606871Developing Computational Thinking Skills With Algorithm-Driven SpreadsheetingMaria Csernoch0https://orcid.org/0000-0002-7088-7714Piroska Biro1https://orcid.org/0000-0001-5997-2515Janos Math2Faculty of Informatics, University of Debrecen, Debrecen, HungaryFaculty of Informatics, University of Debrecen, Debrecen, HungaryFaculty of Humanities, University of Debrecen, Debrecen, HungaryThe paper presents the details of a four-year project to test the effectiveness of teaching spreadsheeting with spreadsheet programming, instead of the traditional, widely accepted surface approach methods. The novel method applied in the project, entitled Sprego (Spreadsheet Lego), is a concept-based problem-solving approach adapted from the didactics of other sciences and computer programming. In the experimental group contextualized, real-world programming problems are presented in a spreadsheet environment. A semi-unplugged data-driven analysis is carried out based on each problem, which is followed by the building of a feasible algorithm, expressed by natural language expressions. The coding is completed in the following step by applying a limited number of spreadsheet (Sprego) functions, multilevel, and array formulas. The final steps of the process are discussion and debugging. On the other hand, classical, tool-centered approaches are applied in the control groups. Our research reveals that the traditional surface approach methods for teaching spreadsheeting do not provide long lasting, reliable knowledge which would provide students and end-users with effective problem-solving strategies, while Sprego does. Beyond this finding, the project proves that Sprego supports schema construction and extended abstraction, which is one of the major hiatus points of traditional surface navigation methods. The project also reveals that developing computational thinking skills should not be downgraded, and the misconceptions of self-taught end-users and user-friendly applications should be reconsidered, especially their application in educational environments. Gaining effective computer problem-solving skills and knowledge-transfer abilities is not magic, but a time-consuming process which requires consciously developed and effective methods, and teachers who accept the incremental nature of the sciences.https://ieeexplore.ieee.org/document/9606871/Algorithm-driven spreadsheetinglong lasting knowledgeschema constructioncognitive loadend-user computingcomputational thinking
spellingShingle Maria Csernoch
Piroska Biro
Janos Math
Developing Computational Thinking Skills With Algorithm-Driven Spreadsheeting
IEEE Access
Algorithm-driven spreadsheeting
long lasting knowledge
schema construction
cognitive load
end-user computing
computational thinking
title Developing Computational Thinking Skills With Algorithm-Driven Spreadsheeting
title_full Developing Computational Thinking Skills With Algorithm-Driven Spreadsheeting
title_fullStr Developing Computational Thinking Skills With Algorithm-Driven Spreadsheeting
title_full_unstemmed Developing Computational Thinking Skills With Algorithm-Driven Spreadsheeting
title_short Developing Computational Thinking Skills With Algorithm-Driven Spreadsheeting
title_sort developing computational thinking skills with algorithm driven spreadsheeting
topic Algorithm-driven spreadsheeting
long lasting knowledge
schema construction
cognitive load
end-user computing
computational thinking
url https://ieeexplore.ieee.org/document/9606871/
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