<![CDATA[Mathematics learning in elementary schools is frequently characterized by low student motivation due to teacher-centered instructional practices and limited opportunities for meaningful engagement. This study aimed to examine the effect of the Deep Learning instructional approach on fourth-grade students' motivation to learn mathematics at SDK Santo Yoseph 4 Kupang. A quantitative approach employing a quasi-experimental method with a One-Group Pretest–Posttest Design was adopted. The participants consisted of 29 fourth-grade students selected through total sampling. Data were collected using a 20-item mathematics learning motivation questionnaire based on six indicators of learning motivation and analyzed using descriptive and inferential statistics with IBM SPSS Statistics version 22. The descriptive findings revealed that the mean motivation score increased from 56.66 on the pretest to 71.55 on the posttest, indicating an improvement from the "Good" category to the "Very Good" category. Furthermore, the posttest results demonstrated a more homogeneous distribution of students' motivation scores than the pretest. Inferential analysis confirmed a statistically significant difference between the pretest and posttest scores, indicating that the implementation of the Deep Learning approach had a positive and significant effect on students' mathematics learning motivation. These findings suggest that the Deep Learning approach promotes active engagement, meaningful learning experiences, and higher learning motivation among elementary school students. Therefore, this instructional approach can be considered an effective alternative for improving mathematics learning motivation in primary education.]]>
