<![CDATA[This study aims to describe the effectiveness of flipped learning with a deep learning framework based on multiple representations in buffer solutions to improve higher-order thinking skills. The population in this study were all grade XI IPA students of SMA Perintis 2 in Bandar Lampung for the 2025/2026 academic year, consisting of three classes and a total of 204 students. Based on the population, the research sample was determined using a porposive sampling technique, with class XI IPA 1 serving as the experimental class and class XI IPA 7 as the control class. The experimental class was taught using flipped learning with a deep learning framework based on multiple representations, while the controll class received conventional instruction. This study employed a quasi experimental method with a nonequivalent pretest postest control group design. The research instruments consisted of pretest and posttest questions and an observation sheet to assess students' learning activities. The data were analyzed using an independent samples t-test. The results of the independent samples t-test indicated that the mean n-gain score of higher-order thinking skills in the experimental class was 0.71, which was categorized as high, and that the mean n gain score was significantly higher than that of the control class. Therefore, it was concluded that flipped learning with a deep learning framework based on multiple representations on the buffer solution topic was effective in improving students' higher-order thinking skills.]]>
