学生解决情境问题的计算思维能力分析

None Muh Hanif Abidi, Hendarto Cahyono, Reni Dwi Susanti
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引用次数: 0

摘要

本研究旨在考察学生在解决双变量线性方程组相关问题时的计算思维能力。这种类型的研究使用描述性定性方法。本研究的研究对象为州立中学八年级学生25名,采用SPLDV (System of Two-Variable Linear Equations)材料。本研究的数据收集技术和工具为书面测试和访谈。数据分析是先对数据进行分类,然后对数据进行展示,最后总结计算思维指标的结果。结果表明,学生计算思维方面即分解方面在良好类别中所占比例为70.30%,模式识别充分类别为58.63%,抽象充分类别为58.30%,思维算法充分类别为50.47%。使学生的计算思维能力被纳入充分范畴。同时,根据高水平学生的分类,他们表现得很好。然而,有几个步骤被遗漏了,也没有写在答题卡上,比如没有正确执行的分解和模式识别方面。对于中等类别,从分解、模式识别、抽象和思维算法开始,计算思维的各个阶段都进行得很好。对于低类别,这个类别还不能很好地进行计算思维的各个阶段。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of Students' Computational Thinking Ability in Solving Contextual Problems
This study aims to examine students' computational thinking skills in solving contextual problems in the matter of a system of two-variable linear equations. This type of research uses descriptive qualitative approach. The subjects used in this study were 25 class VIII students of State Middle School in the 2022/2023 academic year on SPLDV material (System of Two-Variable Linear Equations). Data collection techniques and instruments in this study were written tests and interviews. Data analysis was carried out by first classifying the data, then presenting the data and ending by concluding the results of computational thinking indicators. The results showed that the percentage of students' computational thinking aspects, namely the decomposition aspect, was 70.30% in the good category, pattern recognition 58.63% sufficient category, abstraction 58.30% sufficient category, and thinking algorithm 50.47% sufficient category. So that students' computational thinking skills are included in the sufficient category. Meanwhile, based on the categorization of high-level students they have done well. However, there were several steps that were missed and not written down in the answer sheets, such as the decomposition and pattern recognition aspects which were not carried out properly. For the medium category, all stages of computational thinking have been carried out very well starting from decomposition, pattern recognition, abstraction, and thinking algorithms. For the low category, this category has not been able to carry out the stages of computational thinking properly.
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