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All Journal Jurnal Riset Pendidikan dan Inovasi Pembelajaran Matematika (JRPIPM)
Azizah, Yuliana Amanda Nur
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Education Mathematics Social Sciences

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Students’ Computational Thinking Skills in PISA Problem Solving: Insights from Multiple Intelligences Theory Azizah, Yuliana Amanda Nur; Swastika, Annisa; Sari, Christina Kartika
Jurnal Riset Pendidikan dan Inovasi Pembelajaran Matematika Vol. 9 No. 1 (2025): JRPIPM SEPTEMBER 2025
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jrpipm.v9n1.p1-17

Abstract

Computational thinking (CT) has become one of the essential skills in responding to the dynamic and rapid advancement of technology, as it enables individuals to solve problems effectively, efficiently, and optimally. Various studies have examined CT in mathematics education, but few have considered students' cognitive diversity, particularly the theory of multiple intelligences. The connection between CT and multiple intelligences theory has not been widely explored, even though this theory offers a holistic approach to cognitive potential. This study aims to describe students’ computational thinking abilities in solving PISA questions on space and shape content from the perspective of multiple intelligences. The method used in this study is descriptive qualitative. The research instruments include a computational thinking test, interview guidelines, and a multiple intelligences test. The research subjects consist of three students from SMP Muhammadiyah 2 Surakarta who were selected based on their dominant type of intelligence to represent each intelligence category, namely Linguistic-Verbal (LV), Logical-Mathematical (LM), and Visual-Spatial (VS). The research findings show that students with LV intelligence were able to fulfill all indicators of CT, namely decomposition, pattern recognition, abstraction, and algorithm. Students with LM intelligence demonstrated competence in decomposition, pattern recognition, and algorithm. Students with VS intelligence fulfilled pattern recognition and abstraction.
Co-Authors Annisa Swastika Christina Kartika Sari, Christina Kartika