Computational Thinking Skills Indicators in Number Patterns

This research aims to examine a) what computational thinking indicators have been developed by researchers, b) what computational thinking indicators can be used in learning mathematics appropriately, and c) how to describe the development of student computational thinking indicators from the answers of computational thinking tests. This research is a qualitative descriptive study through a process of collecting data from literature reviews, integrated computational thinking math tests, and interviews. Data collection instruments used research notes, interview sheets, and CT question sheets. The results showed that a) 20 computational thinking indicators had been studied by researchers, b) computational thinking indicators that could be used in learning mathematics include problem decomposition, abstraction, pattern recognition, procedural algorithms, and generalizations, and c) From the student answers, five proposed computational thinking indicators can be developed even though they were not perfect. The general implication of this research is that there are five indicators of computational thinking skills that can be used in mathematics learning, specifically in number patterns, which include problem decomposition, abstraction, pattern recognition, pattern recognition, procedural algorithm, and generalization. The researchers developed all five computational thinking skills indicators in the instructional designs of not only the number pattern concept but also combination, geometry, combinatorics, etc.