Analysis of Students’ Difficulties in Applying Computational Thinking in Numerical Physics Learning
TL;DR
The findings indicate that students face substantial challenges in both understanding and applying computational thinking in numerical physics contexts, and provides an empirical basis for improving instruction.
Abstract
Computational thinking skills are essential for numerical physics learning; however, students’ mastery of these skills remains considerably below expectations. This study aims to analyze the difficulties experienced by Physics Education students in applying computational thinking to numerical physics learning. A survey research design employing a quantitative descriptive approach was used. Data were collected through a 15-item questionnaire administered via Google Forms to 31 students from the 2022 and 2023 cohorts of the Physics Education program, selected using purposive sampling. The questionnaire demonstrated good reliability, with a Cronbach’s alpha coefficient of 0.82, while its content validity was established through expert judgment. Descriptive statistical analysis revealed an overall mean difficulty score of 3.68 on a five-point scale, indicating a relatively high level of difficulty. The highest level of difficulty was found in the conceptual understanding aspect (M = 3.72), particularly in integrating physics theory with computational implementation, whereas the practical application aspect showed a slightly lower mean score (M = 3.63). These findings indicate that students face substantial challenges in both understanding and applying computational thinking in numerical physics contexts. The study provides an empirical basis for improving instruction, particularly through the development of curricula and teaching strategies that more effectively support students’ computational thinking competencies in physics education