Understanding Students' Computational Thinking through Cognitive Interviews: A Learning Trajectory-based Analysis
Understanding Students' Computational Thinking through Cognitive Interviews: A Learning Trajectory-based Analysis
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通过认知访谈了解学生的计算思维:基于学习轨迹的分析
DOI:
10.1145/3328778.3366845
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发表时间:
2020
期刊:
影响因子:
--
通讯作者:
Hampton, John
中科院分区:
文献类型:
--
作者:
Luo, Feiya;Israel, Maya;Liu, Ruohan;Yan, Wei;Gane, Brian;Hampton, John
For K-8 computer science (CS) education to continue to expand, it is essential that we understand how students develop and demonstrate computational thinking (CT). One approach to gaining this insight is by having students articulate their understanding of CT through cognitive interviews. This study presents findings of a cognitive interview study with 13 fourth-grade students (who had previously engaged in integrated CT and mathematics instruction) working on CT assessment items. The items assessed four CT concepts: sequence, repetition, conditionals, and decomposition. This study analyzed students\textquotesingle articulated understanding of the four CT concepts and the correspondence between that understanding and hypothesized learning trajectories (LTs). We found that 1) all students articulated an understanding of sequence that matched the intermediate level of the Sequence LT; 2) a majority of students\textquotesingle responses demonstrated the level of understanding that the repetition and decomposition items were designed to solicit (8 of 9 responses were correct for repetition and 4 of 6 were correct for decomposition); and 3) less than half of students\textquotesingle responses articulated an understanding of conditionals that was intended by the items (4 of 9 responses were correct). The results also suggested questioning the directional relationships of two statements in the existing Conditionals LT. For example, unlike the LT, this study revealed that students could understand "A conditional connects a condition to an outcome'' before "A condition is something that can be true or false.''
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发表时间:
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发表时间:
2020
期刊:
Proceedings of the 2020 AERA Annual Meeting
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