<![CDATA[The low mathematics learning outcomes of elementary school students indicate that the learning process has not yet fully facilitated deep conceptual understanding. The instructional materials and learning tools used by teachers remain predominantly conventional and have not optimally incorporated a Deep Learning Framework to enhance student engagement and learning outcomes. This study aimed to analyze, evaluate, and determine the effectiveness of mathematics instructional tools based on a Deep Learning Framework in improving the learning outcomes of fifth-grade elementary school students. The study employed a quantitative approach using a quasi-experimental One-Group Pretest-Posttest Design. The participants consisted of 28 fifth-grade students, all of whom were selected through a total sampling technique. Data were collected through learning achievement tests administered as pretests and posttests. The instruments were developed based on competency achievement indicators and validated to ensure content validity. Data analysis included descriptive statistics and inferential statistics through prerequisite tests, namely the Kolmogorov-Smirnov and Shapiro-Wilk normality tests and Levene’s test of homogeneity. Hypothesis testing was conducted using a Paired-Samples t-Test with the assistance of SPSS software. The results revealed a significant difference between the pretest and posttest scores, indicating that the mathematics instructional tools based on the Deep Learning Framework were effective in improving students’ learning outcomes. These findings imply that the developed instructional tools support a more structured, meaningful, and student-centered mathematics learning process.]]>
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