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Title: Understanding Students' Computational Thinking through Cognitive Interviews: A Learning Trajectory-based Analysis
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' 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' 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' 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.''  more » « less
Award ID(s):
1932920
NSF-PAR ID:
10178448
Author(s) / Creator(s):
; ; ; ; ;
Date Published:
Journal Name:
Proceedings of the 51st Association for Computing Machinery (ACM) Technical Symposium on Computer Science Education
Page Range / eLocation ID:
919 to 925
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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