<![CDATA[Improving university students' learning outcomes in mathematics requires instructional approaches that promote active engagement, meaningful learning, and the integration of digital technologies. Python programming has recently gained attention as an educational tool for supporting computational problem-solving and conceptual understanding. This study aimed to examine the effect of integrating Python programming into contextual project learning on university students' learning outcomes. A quasi-experimental research design employing a non-equivalent control group was conducted involving 58 undergraduate students enrolled in the Basic Concepts of Mathematics course at Universitas Muhammadiyah Muara Bungo, Indonesia. The experimental group consisted of 30 students who participated in Python-integrated contextual project learning, while the control group comprised 28 students who received conventional instruction. Students' learning outcomes were measured using pretest and posttest achievement tests. The data were analyzed using descriptive statistics, the Shapiro-Wilk normality test, Levene's homogeneity test, and the Mann-Whitney U test because the posttest scores were not normally distributed. The findings indicated that there was no significant difference in students' initial abilities before the intervention, whereas the posttest results revealed a significant difference between the experimental and control groups in favor of the experimental group (p < .05). The integration of Python programming into contextual project learning enabled students to engage more actively in contextual problem-solving, computational exploration, and collaborative project activities, resulting in improved learning outcomes. These findings suggest that integrating Python programming into contextual project learning provides an effective instructional approach for enhancing university students' mathematics learning outcomes in higher education.]]>
