<![CDATA[The problem of students' low critical thinking skills has prompted innovation in learning strategies, one of which is the use of the Quantum Learning model with a Deep Learning approach. This study aims to determine the effectiveness of the Quantum Learning model based on the Deep Learning approach on students' critical thinking skills in solving mathematical problems. This study used a combinational research approach, applying an exploratory sequential mixed methods approach. The sampling technique used was purposive sampling. The sample consisted of classes X-7 as the experimental class and X-8 as the control class, with six students serving as subjects for the qualitative analysis. Data collection techniques used included tests, documentation, and interviews. While paired t-tests were used to examine the data in the quantitative section, three phases of analysis were used to assess the data in the qualitative section: data reduction, data presentation, and conclusions. Triangulation methods, including interviews and documentation, were used in this study. Students' critical thinking skills improved significantly, according to the results of the paired t-test. The results of the hypothesis test showed a sig value (2-tailed) of 0.000. Based on the decision-making criteria, since the sig value (2-tailed) <0.05, is rejected and is accepted, so it can be concluded that there is a significant difference between the critical thinking abilities of the experimental class and the control class after the Quantum Learning model with the Deep Learning approach was implemented. In addition, according to the qualitative analysis: There was a shift in the achievement of students' critical thinking ability indicators: (1) students with high critical thinking abilities changed from two indicators in the pretest to four indicators in the posttest; (2) students with moderate critical thinking abilities changed to three indicators in the posttest; (3) students with low critical thinking abilities did not change, only meeting one indicator in the posttest.]]>
Copyrights © 2026
