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Title: Using computational thinking for data practices in high school science.
When conducting a science investigation in biology, chemistry, physics or earth science, students often need to obtain, organize, clean, and analyze the data in order to draw conclusions about a particular phenomenon. It can be difficult to develop lesson plans that provide detailed or explicit instructions about what students need to think about and do to develop a firm conceptual understanding, particularly regarding data analysis. This article demonstrates how computational thinking principles and data practices can be merged to develop more effective science investigation lesson plans. The data practices of creating, collecting, manipulating, visualizing, and analyzing data are merged with the computational thinking practices of decomposition, pattern recognition, abstraction, algorithmic thinking, and automation to create questions for teachers and students that help them think through the underlying processes that happen with data during high school science investigations. The questions can either be used to elaborate lesson plans or embedded into lesson plans for students to consider how they are using computational thinking during their data practices in science.
Authors:
; ; ; ; ; ;
Award ID(s):
1842090
Publication Date:
NSF-PAR ID:
10171527
Journal Name:
The science teacher
Volume:
87
Issue:
6
Page Range or eLocation-ID:
30-36
ISSN:
1943-4871
Sponsoring Org:
National Science Foundation
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