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-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.

Abstract licence: CC BY-NC-ND

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