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Методика обучения алгоритмам и структурам данных

Методика обучения алгоритмам и структурам данных

Abstract

Рассмотрена методика обучения студентов основным, часто используемым алгоритмам в процессе практического решения задач на ЭВМ и привития навыков эффективного программирования. Данная методика способствует развитию навыков алгоритмического мышления. Особенностью методики является последовательное изучение основных алгоритмов (сортировка и поиск, элементы теории информации и криптографии, рекурсивные алгоритмы и алгоритмы на графах) без привязки к конкретному языку программирования и последующая реализация пройденных алгоритмов на практике. Данный курс содержит лабораторный практикум, содержащий задания возрастающей трудности. Простые задания требуют от студента заполнения пропусков. Более сложные задания требуют навыков самостоятельной разработки и отладки программ.

The article is devoted to the methods of teaching students the basic often applied algorithms of solving computer problems. The main feature of this methodology is the consistent study of the basic algorithms (sorting and search, information theory and cryptography, recursive algorithms and graph algorithms) implying the use of any programming language and further implementation of the studied algorithms in practice. This course includes laboratory practical tasks. These tasks have the increasing difficulty. At the beginning of the course a simple task demands from the student filling of admissions. More difficult tasks assume independent development and debugging of computer programs.

Keywords

МЕТОДИКА ОБУЧЕНИЯ,METHODS OF TEACHING,АЛГОРИТМИЧЕСКОЕ МЫШЛЕНИЕ,ALGORITHMIC THINKING,АЛГОРИТМЫ И СТРУКТУРЫ ДАННЫХ,ALGORITHMS AND DATA STRUCTURES,СОРТИРОВКА И ПОИСК,РЕКУРСИВНЫЕ АЛГОРИТМЫ,RECURSIVE ALGORITHMS AND GRAPH ALGORITHMS,АЛГОРИТМЫ НА ГРАФАХ,SORT AND SEARCH

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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Average
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