Journal of Didactic Mathematics
Vol 6, No 3 (2025): December

Computational thinking obstacles in students’ responses to AKM level 5 problems

Siregar, Ginda Maruli Andi (Unknown)
Hidayat, Hidayat (Unknown)
Sukmawarti, Sukmawarti (Unknown)
Maulida, Aya Shofia (Unknown)



Article Info

Publish Date
31 Dec 2025

Abstract

The objective of this research is to elucidate the impediments encountered by students when attempting to solve Level 5 Minimum Competency Assessment (AKM) problems within the realm of Computational Thinking (CT). Employing a descriptive qualitative approach with a case study design, the research involved eleventh-grade students from a senior high school. Data were gathered through Level 5 AKM tests, in-depth interviews, and the analysis of students’ written responses. These data were subsequently analyzed using open coding, selective coding, and axial coding. The findings reveal that students encounter CT obstacles in several critical domains. Specifically, in the decomposition indicator, students demonstrated difficulties in breaking down graphical information, selectively extracting data without comprehending the interrelationships among values. In pattern recognition, students failed to discern upward-downward trends in harvest data or proportional relationships in probability tasks, thereby hindering their ability to draw comprehensive conclusions. Abstraction challenges emerged when students were unable to discern pertinent information, such as conflating actual frequencies with theoretical probabilities. In algorithmic thinking, students were unable to construct systematic steps in calculations or engage in logical reasoning. Furthermore, logical reasoning and evaluation were deficient, as evidenced by their inability to assess the plausibility of results or validate their answers.

Copyrights © 2025






Journal Info

Abbrev

jdm

Publisher

Subject

Education Mathematics

Description

Journal of Didactic Mathematics is published three times a year, in April, August and December. This journal is providing a platform that welcomes and acknowledges high quality empirical original research papers about mathematics education, mathematical didactic, mathematics learning, and school ...