<![CDATA[This study aims to determine the differences in students' mathematical reasoning abilities between those using the Quizizz-assisted deep learning approach and conventional learning and to determine the improvement in students' mathematical reasoning abilities using the Quizizz-assisted deep learning approach compared to students using conventional learning. This study is a quantitative study with a quasi-experimental method using a pretest-posttest control group design. The population in this study were all grade X students of SMA Santo Yoseph Medan. The sample of this study consisted of two classes, namely class X-3 as the experimental class and class X-2 as the control class, each consisting of 29 students. The research instrument used was a mathematical reasoning ability test that had met the requirements of validity, reliability, discriminating power, and level of difficulty. Data analysis was carried out using the normality test, homogeneity test, t-test, and N-Gain index. The results of this study showed that the average posttest score of the experimental class was 77.59, higher than the control class of 61.72. The t-test results show that t_count = 5.769 and t_table = 2.045 so that t_count>t_table. In addition, the Sig. (2-tailed) value is 0.000 <0.05. These results indicate that there is a difference in mathematical reasoning ability between students who use the quizizz-assisted deep learning approach and students who use conventional learning. The results of the N-Gain analysis show that the average N-Gain of the experimental class is 0.64 and the control class is 0.39, both of which are in the moderate category. Thus, it can be concluded that the quizizz-assisted deep learning approach provides a higher increase in mathematical reasoning ability than conventional learning.]]>
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