Analysis of Elementary School Students' Computational Thinking in Learning with Artificial Intelligence-Assisted Mathematical Activities - Salisa Rizky Candra; Rina Dyah Rahmawati (Jurnal Profesi Keguruan, 2026)
This study aims to analyze elementary school students' computational thinking abilities in mathematics activities assisted by artificial intelligence. This research is motivated by the low level of students' numeracy literacy and the limited use of AI in mathematics learning that requires analytical skills from students. This interpretive qualitative research was conducted on sixth-grade students at an elementary school in Bantul, focusing on the surface area of composite geometric shapes. Data were collected through observations, tests, and interviews to describe students' thinking processes. Data validity was tested using triangulation. The results showed differences in students' computational thinking (CT) abilities in the high, medium, and low categories in meeting the indicators of decomposition, abstraction, algorithms, debugging, and generalization. AI-assisted mathematics activities helped students understand concepts and develop CT, especially in identifying and correcting AI errors. Therefore, AI needs to be used as a learning support medium to optimize students' CT abilities. These errors encourage the development of computational thinking abilities in students so that students are able to think critically to correct errors made by AI. Overall, this study confirms that AI-assisted mathematics activities are a strategic tool in developing elementary school students' computational thinking skills, as long as AI is positioned as a learning support medium and not as a substitute for students' thinking processes.