<![CDATA[Conventional learning methods in dealing with the complexity of dynamic and multidimensional global issues in learning global citizenship education are still ineffective, this can be seen from the low understanding and awareness of students in solving global issues that occur. This research aims to develop and test learning innovations by integrating deep learning approaches to improve students' understanding and participation in the context of global citizenship. The research method used was quantitative research with an experimental approach. The research subjects consisted of senior high school students in a sample school. The research instruments included questionnaires, comprehension tests, and observations used to measure the effectiveness of learning before and after the application of the deep learning approach. The collected data were analyzed using descriptive and inferential statistics to assess the improvement of learning outcomes. The results showed that the integration of deep learning approach in global citizenship education significantly improved students' concept understanding, critical thinking skills, and learning motivation. Students become more active and able to connect civic education materials with contemporary global issues more deeply. The implication of this research finding is that the application of deep learning technology can be an effective innovative strategy in developing global citizenship education that is adaptive and responsive to the challenges of the times. This encourages educators to utilize artificial intelligence technology in the learning process to create a more interactive and meaningful learning experience.]]>
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