The Effect of a Deep Learning-Integrated Problem-Based Learning Model on Critical Thinking and Mathematical Self-Efficacy in Elementary Students

Source abstract

Low critical thinking ability and mathematical self-efficacy among elementary school students remain persistent problems in mathematics education, primarily caused by conventional teacher-centered instruction. This study addresses these challenges by integrating innovative pedagogical practices to foster higher-order thinking skills and academic confidence. This study aims to examine the effect of integrating a Deep Learning approach into the Problem-Based Learning (PBL) model on fifth-grade students' critical thinking skills and mathematical self-efficacy regarding fraction addition. A quantitative pre-experimental design (One-Group Pretest-Posttest Design) was employed with a sample of 28 students selected through purposive sampling. Data were collected using a 5-item essay test for critical thinking and a 24-item questionnaire for self-efficacy. Key results demonstrated a significant improvement in critical thinking skills from a pretest mean of 44.29 to a posttest mean of 80.04, yielding a mean N-Gain of 0.67 in the moderate category. A paired-samples t-test confirmed a significant effect of the Deep Learning-based PBL model (p=0.001<0.05). Furthermore, students achieved high self-efficacy (mean score 68.67), which positively and significantly influenced critical thinking (F=7.753, p=0.010<0.05), accounting for 23% of the variance (R^2=0.230). In conclusion, integrating Deep Learning with the PBL model effectively enhances elementary students' critical thinking skills and self-efficacy. Elementary school teachers are recommended to implement this integrated framework to construct meaningful and engaging mathematics learning environments.