The Effect of Problem-Based Learning with a Deep Learning Approach on Critical Thinking and Speaking Skills

Abstract

The Problem-Based Learning (PBL) model with the Deep Learning approach is oriented toward solving contextual problems through a deep, meaningful, student-centered learning process. The Deep Learning approach encourages active student involvement in understanding concepts, developing critical thinking skills, collaborating, and communicating ideas effectively. This study aims to determine the effect of implementing the Problem-Based Learning model with the Deep Learning approach on the critical thinking and speaking skills of Phase C students in grade V at Wahid Hasyim Sekardangan Islamic Elementary School, Sidoarjo, in the Science material "Advancing Economic Potential in My Region." This study uses a quantitative approach with a pre-experimental one-group pretest-posttest design, with a sample of 28 grade V students from Wahid Hasyim Sekardangan Islamic Elementary School, Sidoarjo, and was carried out on May 18, 2026. The data analysis used a descriptive test, paired-samples t-test, and N-Gain test. The average pretest score is 46.48, and the average posttest score is 76.03. For the paired-samples t test, the Sig. Score (2-tailed) is 0.000 <0.05, so H0 is rejected, and H1 is accepted. In addition, the N-Gain score is 0.3 < 0.5393 < 0.7, so it can be concluded that the Problem-Based Learning model with the Deep Learning approach affects students' critical thinking and speaking skills and has a significant impact. However, the increase is not too drastic. In other words, the Problem-Based Learning model with the Deep Learning approach effectively improves students' critical thinking skills, speaking skills, and understanding through a meaningful problem-solving process. However, the improvements still have room for further development.