<![CDATA[This study aims to analyze student learning outcomes before and after the implementation of the deep learning approach, as well as its impact on learning outcomes in geography classes for Grade XI students at SMAN 8 Padang. The study employed a quantitative approach using a pre-experimental method and a one-group pretest-posttest design, involving 33 students from class XI F1 selected via purposive sampling. Data were collected using learning outcome tests (pretest and posttest) and subsequently analyzed using descriptive statistics, the Shapiro–Wilk normality test, N-Gain analysis, an analysis of learning indicator achievement, and a paired sample t-test. The results indicate that student learning outcomes were initially low but improved following the implementation of the deep learning approach; this improvement was evidenced by an increase in the number of students achieving mastery (from 9 to 24), an N-Gain score of 0.761 (categorized as high and effective), and high achievement levels across all learning indicators although the indicators regarding concepts and environmental management showed the lowest percentages. The paired sample t-test yielded a Sig. (2-tailed) value of < 0.001, indicating a significant difference between learning outcomes before and after the implementation of the deep learning approach. Thus, the implementation of the deep learning approach has a positive effect on improving student learning outcomes in geography.]]>
Copyrights © 2026
