An analysis of environmental literacy that integrates ethnoscience in sustainable science learning between scientific knowledge and problems in life, as well as the value of local wisdom. This study was aimed to determine the profile of ethnoscience integrated environmental literacy. This research uses a survey method with a sampling technique of cluster random sampling and conducting a Question Test and a Middle School Environmental Literacy Survey (MSELS) to students. The parameters of this study consist of knowledge of ecology, cognitive skills, attitudes and behavior. Descriptive data analysis used average score. Research findings indicate that the ethnoscience integrated environmental literacy of junior high school students obtained an average score of 61 (with a range of 100). The achievement of environmental literacy parameters for ecological knowledge, cognitive skills, attitudes and behavior are 48, 29, 73 and 71, respectively, while the results of the ethnoscience integrated environmental literacy analysis illustrate that the average Junior High School has implemented ethnoscience integration in environmental literacy well. So empowering knowledge and attitudes contribute to environmental literacy students.
Industrial Revolution 4.0 requires individuals to have the ability in the field of technology and use it to solve existing problems. Computational Thinking (CT) is one of the skills needed in dealing with technological developments through a problem-solving process. Many research developments in the field of CT have been carried out, but the theoretical studies presented are still limited to the ability in solving problems using a computer. Whereas in its development, CT theory must be adapted to the scope and purpose of building it. Based on that, new research is needed which aims to test and analyze the truth of these findings and examine the stages of building appropriate CT for science students with state-of-the-art review method. By taking a specific scope that has not been studied by many researchers, namely science education, it is found that CT is the ability in dividing a problem into sub-steps, carry out deeper investigations, analyze and criticize and test the truth of something so that the right solution is obtained. This definition is more specific than the definition of CT in theory because it is adapted to the characteristics of science. Whereas from a state-of-the-art review of the stages of building CT, it was found that the stages of task decomposition, abstraction, generalization, data structures and algorithms were considered to optimalize the CT construction for science students. It is because students could identify tasks or problems and divide the problem into small parts at the task decomposition stage. Therefore, they can be completed one by one.
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