Developing Student’s Comprehensive Knowledge of Physics Concepts by Using Computational Thinking Activities: Effects of a 6-Week Intervention

Abstract

Computational thinking has been identified as an important approach for enabling students’ better comprehension of STEM concepts as well as scientific procedures. Computation solutions are useful in STEM concepts as they are simplifying mathematical problems so that STEM or physics theories can be applied to problems that have mathematically complicated solutions. Visual Python library provides a 3D environment where learners may design 3D objects, encode physics equations, and study the effects of altering parameters. As the environment created uses simple equations (force or momentum dependent) to compute solutions, students are able to grasp hard mathematical concepts and understand their importance in real-life problems. The implementation and outcomes of a 6-week teacher-led computational thinking intervention with groups of 12th graders (n = 60) are described in this study. Two research questions are being addressed using quantitative analysis and a quasi-experimental approach involving a pre and post-test. The participants who received the six-week implementation in the experimental group performed significantly better on points covered by simulations compared to the control group, which received only standard teaching lectures. The results indicated a statistically significant difference in mean scores between the experimental group (M = 24.03, SD = 4.68) and the control group (M = 20.3, SD = 5.38). The findings indicate that implementing computational thinking activities not only improves students’ knowledge of physics concepts but also improves visual thinking, allowing students to comprehend the problem better cognitively.