Aulia Nur Rozi, Tasya
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Profiling students' computational thinking in multirepresentational VSEPR problem solving Aulia Nur Rozi, Tasya; Dwiningsih, Kusumawati
Indonesian Journal of Science and Mathematics Education Vol. 9 No. 2 (2026): Indonesian Journal of Science and Mathematics Education
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/ijsme.v9i2.32780

Abstract

Computational thinking (CT) is recognized as an essential competency for solving problems across disciplines, including chemistry, where topics such as Valence Shell Electron Pair Repulsion (VSEPR) theory require students to coordinate representations. Yet, little is known about how CT components manifest during multirepresentational VSEPR problem solving. This study describes students' CT profiles across four components: decomposition, pattern recognition, abstraction, and algorithmic thinking, when solving multirepresentational chemistry problems related to VSEPR theory, and to identify changes in these profiles before and after learning. A descriptive quantitative approach with a single-group pretest-posttest design was employed, involving 27 Grade XI-5 students selected through total sampling. Data were collected using written tests and observation sheets, analyzed descriptively and supported by the Wilcoxon signed-rank test. In the pretest, 81.48% of students were classified as Low or Very Low CT, whereas in the posttest, 59.26% were classified as High or Very High (Z = −4.280, p < 0.001). Decomposition showed the highest achievement (70.37%), whereas pattern recognition and algorithmic thinking showed the lowest scores, indicating uneven development across CT components. The implication is that instruction should explicitly strengthen these two components through targeted representational translation activities, supporting balanced CT development and SDG 4 (Quality Education).