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This research aims to explore how the transformation of environmental education in the primary school curriculum can contribute to dealing with the climate crisis. The design of this study uses a qualitative approach with analysis units in elementary schools that have integrated environmental education into their curriculum. The data sources were obtained from interviews with teachers, school principals, and an analysis of applied educational curriculum documents. Data collection techniques include in-depth interviews, classroom observations, and document analysis related to the environmental curriculum. Data analysis was carried out using a thematic analysis approach to identify how environmental education can affect students' understanding of the issue of the climate crisis. The findings of the study show that despite efforts to integrate environmental education in the basic curriculum, its implementation is still limited and inconsistent across schools. The contribution of this research is to provide recommendations on how the basic curriculum can be updated to teach more deeply about the climate crisis, so as to increase awareness and positive actions from the younger generation in protecting the environment.

This study aims to explore the progress of the education evaluation system in improving accountability in Indonesian schools. This study uses a qualitative approach with the analysis units of school principals, teachers, and education supervisors. The research design used is a case study with primary data sources obtained through in-depth interviews and observations. The data collection technique involves semi-structured interviews and documentation, while the data analysis is carried out using thematic analysis techniques. The findings of the study show that the progress of the education evaluation system in Indonesian schools has increased accountability, although there are still challenges in its implementation evenly across regions. The contribution of this research is to provide a deeper understanding of the role of educational evaluation in increasing accountability and to provide recommendations for the development of a more effective evaluation system in Indonesia.

This research aims to explore changes in social education in Indonesian schools and their impact on improving students' social awareness. This study uses a qualitative design with an analysis unit on social education policies, teachers, and students in several elementary and secondary schools. Data sources were obtained through interviews with principals, social education teachers, and students, as well as direct observations in the classroom. Data collection techniques were carried out by semi-structured interviews, observations, and documentation studies, while data analysis used a thematic analysis approach to identify key themes related to the influence of social education on students' social awareness. The findings of the study suggest that although social education curriculum changes aim to increase social awareness, their implementation is constrained by a lack of training for teachers and limited resources. The contribution of this research is to provide insight into the importance of social education in shaping students' social awareness, as well as offer recommendations for improving social education policies in Indonesian schools.

This study aims to examine the application of artificial intelligence (AI)--based education management in improving personalized philosophy learning. This study uses a qualitative approach with case study methods in several educational institutions that apply artificial intelligence-based educational technology. Data were collected through in-depth interviews with educators, focus group interviews with students, and observations on the implementation of artificial intelligence systems in philosophy learning. Data analysis was carried out using thematic analysis techniques to identify patterns of the use of educational technology in facilitating more personalized learning. The results of the study show that artificial intelligence-based education management can increase student involvement and deeper understanding of philosophy materials. The contribution of this research is to provide insight into how artificial intelligence technology can optimize the philosophy learning process with a more personalized and effective approach.

This study aims to analyze the implementation of data-based management in improving the effectiveness of education in AI-assisted learning at the high school level. The analysis units in this study are data management systems and AI learning strategies in schools. The research design used is a qualitative study with a descriptive approach. The main data sources consist of principals, teachers, and high school students involved in the use of AI in learning. Data collection techniques include in-depth interviews, observations, and document analysis. The data is analyzed using thematic analysis techniques to identify patterns in the implementation of data-based management. The results show that the optimal use of data-based management can increase the effectiveness of AI-assisted learning through adaptive and evidence-based strategies. The main contribution of this research is to provide insights into how systematic data management can support technology-based educational innovation in the school environment.

This study aims to analyze the role of school-based management in the integration of educational technology with ChatGPT to support instructional strategies in language learning for junior high school students. This study uses a qualitative approach with a case study method, where data is collected through in-depth interviews with principals, teachers, and students, as well as observation of learning activities and analysis of school policy documents. The research subjects were selected purposively to obtain relevant information regarding the implementation of technology-based instructional strategies. Data analysis was carried out by data reduction techniques, data presentation, and conclusion drawing to identify patterns in school management that support or hinder the integration of technology in language learning. The results of the study show that the success of technology integration in language learning depends on systematic school management policies, teacher readiness, and infrastructure support. This research contributes to providing insight for schools in designing more effective technology-based policies to improve the quality of language learning at the junior high school level.

This study aims to analyze the strategy of using artificial intelligence using ChatGPT to improve the efficiency of education management in the era of technological transformation. This research uses qualitative methods, especially using a case study approach that focuses on educational institutions that have integrated artificial intelligence technology. Data was collected through comprehensive interviews with relevant stakeholders, observations related to technology implementation, and analysis of documentation related to managerial policies and practices. Techniques for data analysis are carried out thematically to distinguish patterns in innovative strategies in digital education. The findings show that the application of artificial intelligence through ChatGPT significantly improves management efficiency by automating administrative tasks, facilitating data-driven decision-making, and encouraging increased adaptive interaction in learning environments. This research offers valuable insights for education administrators in formulating innovation strategies based on artificial intelligence to accelerate technological transformation in the education sector.