<![CDATA[Economic literacy is an essential competency that enables students to understand economic phenomena critically and apply economic reasoning in everyday decision-making. However, economic education in many schools still relies heavily on memorization and teacher-centered approaches, which hinder students from developing higher-order thinking skills and meaningful understanding. This study aims to analyze the effectiveness of a deep learning-based learning environment in enhancing the economic literacy of high school students. A quasi-experimental method was employed using a pretest-posttest control group design. The participants consisted of two Grade XI social science classes at a public high school in City Ternate, with one class assigned as the experimental group implementing deep learning strategies and the other as the control group using conventional teaching methods. Data were collected through economic literacy tests and classroom observation sheets. The results indicated a significant improvement in the economic literacy scores of students in the experimental group compared to those in the control group. Students exposed to the deep learning environment demonstrated better conceptual understanding, critical thinking, and the ability to relate economic concepts to real-life situations. The study concludes that deep learning environments are effective in fostering students’ economic literacy and should be considered as a promising alternative to traditional teaching methods in economics education, particularly at the senior high school level.]]>
