Improving Students' Computational Skills through the Implementation of Problem-Solving Laboratory Learning Models

Abstract

In the digital era, computational thinking skills are essential for students to succeed in science education, including physics. However, traditional teaching methods often fail to cultivate these skills effectively. This study aimed to evaluate the effectiveness of the problem-solving laboratory learning model in enhancing students' computational thinking skills, specifically in alternating current electricity topics. The research employed a pre-experimental design with a one-group pre-test and post-test approach, involving 35 twelfth-grade students from a public high school in Banjar City, West Java, Indonesia. Data were collected using observation sheets to assess problem-solving laboratory implementation and computational thinking skill tests. The problem-solving laboratory model was implemented effectively, achieving an average implementation success rate of 78.4%. The analysis revealed a significant improvement in students' computational thinking skills, with an average N-gain score of 0.73, categorized as high. Among the computational thinking indicators, abstraction showed the highest improvement, followed by decomposition, data analysis, pattern recognition, and algorithmic thinking. These results suggest that the problem-solving laboratory model provides an effective framework for fostering computational thinking skills through hands-on problem-solving activities and structured learning processes. The study recommends integrating the problem-solving laboratory model into other physics topics and broader educational contexts to enhance students' 21st-century competencies. Future research should consider incorporating control groups and extending the scope to explore long-term impacts across diverse learning environments.