graduate student
Osh, Kyrgyzstan
doctoral candidate
Osh, Kyrgyzstan
employee
Taldykorgan, Kazakhstan
In the context of contemporary schooling, programming Olympiad problems in the Python language are becoming an important tool for developing students’ algorithmic thinking and preparing them for further engineering and mathematical education. At the same time, when solving such problems, school students display a stable range of errors related both to the specific features of the language itself and to the format of Olympiad contests. This article presents the results of an analysis of solutions to programming Olympiad problems in Python proposed to students of grades 9 at one of the schools in Osh, with the direct involvement of the authors in the process of teaching computer science. The study considers 312 program solutions submitted during training Olympiads and simulated contest rounds. On this basis, a classification of errors is constructed (syntax errors, input–output and formatting errors, type-related errors, logical, algorithmic and problem-comprehension errors), together with statistics on their prevalence and typical situations in which they arise. The authors conclude that, even when using a language with relatively simple syntax, not only technical but also conceptual errors related to algorithm choice and interpretation of problem statements remain predominant, and they propose methodological recommendations for teachers of informatics on how to organize systematic work with students’ errors when preparing them for programming Olympiads in Python.
programming Olympiads, Python language, schoolchildren, typical errors, automatic judging, Olympiad training
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