A comparison of computational thinking skills: PBL model vs traditional learning - Erlinawaty Simanjuntak; Sahat Saragih; Elvis Napitupulu (State Islamic University of North Sumatra, 2025)
Computational thinking abilities assist students in solving complex problems, enhancing productivity, and preparing them to face challenges in various fields. The problem-based learning (PBL) model was chosen because it is believed to improve students' computational thinking skills, as well as their critical and creative thinking abilities, which are often difficult to achieve through conventional learning. This research aims to determine the differences in students' computational thinking abilities through the application of problem-based learning and traditional learning methods. The research method was an experiment involving a population of all 2020 Mathematics Education students who took six linear program courses at Medan State University. Sampling was conducted using a random sampling technique, focusing on the PSPM 20B and PSPM 20C classes, totaling 60 students. This study employed a pretest-posttest control group design. Results from previous research indicated that the average computational thinking ability of students in the experimental class was higher than that of the control class, with scores of 82.67 for the experimental class and 69.00 for the control class. From the results of the average difference test, it can be concluded that there is a significant difference in the computational thinking abilities of students taught using the problem-based learning model compared to those taught using the traditional learning model, with PBL being more effective.