• Journal of The Korean Association For Science Education
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• v.27 no.3
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• pp.242-252
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• 2007

This study analyzed the science texts covering 'air pressure' and 'wind' in common with every curriculum from the syllabus period to the $7^{th}$ curriculum in terms of Systemic Functional Linguistics. Important findings revealed in this study were as follows: In the aspect of ideational metafunction, the texts including much scientific information were reduced by curriculum revision. Most forms of information were 'definition' and 'fact' rather than 'principle'. In the aspect of interpersonal metafunction, the gap between students and texts were getting closer and the social position of students were concerned gradually by curriculum revisions. In the aspect of textual metafunction, the ratios of technical terminology and notation were reduced, however the amount of texts in science textbooks were reduced as well. While the subject was presented in the early texts, it was omitted as time went on. The consistency of subject and theme were reduced in the $7^{th}$ curriculum remarkably.

• Journal of Korean Elementary Science Education
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• v.35 no.1
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• pp.26-38
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• 2016

The purpose of this study was to grasp the characteristics of composition regarding the material-centered integrated unit of environmental and natural studies, a science subject in Finland, to investigate a need for applying the material-centered integrated unit to the science curriculum of Korea. For the purpose, the study made an analysis on contents, inquiry activities, and visual materials (the most important in the elementary science curriculum and textbook composition), and it brought following results: First, as a result of analyzing the area of contents, the bicycle material-centered integrated unit comprised a large proportion of 44 pages (25.3%) of the whole 174 pages from the environmental and natural studies textbook for the third grade. The contents included such various concepts as traffic rules, safety, environmental protection and pollution, recycling and separate collection, tubes and triangular structures, wedges and screws, leverage, wheels, axles, gears, elasticity (spring), friction, and so on. Second, as a result of analyzing contents related to the thinking ability of inquiry activities, "expecting or confirming expectations" and "application" are included in every lesson, and one lesson is composed in such a way that students can study on bicycles as a practical material for their daily life and they can improve various thinking abilities. Third, as a result of analyzing the circumstances of inquiry activities, daily circumstances made up eight lessons (80.0%) and technical and social circumstances made up two lessons (20.0%) by focusing on bicycles, a material related to students' daily life. Fourth, as a result of analyzing visual materials, the percentage of pictures and photos was high at 53.4% and 45.2% respectively. As a result of analyzing the role of visual materials, the percentage of the illustrative role and explanatory-complementary role was high at 52.1% and 47.9% respectively. Lastly, as a result of analyzing from the epistemological view to interpret the relation between visual materials and students and the position of visual materials, the visual textbook materials were provided toward a way that students can decrease their feeling of epistemological separation in the three fields of ideational metafunction, interpersonal metafunction, and textual metafunction.

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.192-198
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• 2023

Cyberbullying is a growing problem among adolescents and can have serious psychological and emotional consequences for the victims. In recent years, machine learning techniques have emerged as promising approach for detecting instances of cyberbullying in online communication. This research paper focuses on developing a machine learning models that are able to detect cyberbullying including support vector machines, naïve bayes, and random forests. The study uses a dataset of real-world examples of cyberbullying collected from Twitter and extracts features that represents the ideational metafunction, then evaluates the performance of each algorithm before and after considering the theory of systemic functional linguistics in terms of precision, recall, and F1-score. The result indicates that all three algorithms are effective at detecting cyberbullying with 92% for naïve bayes and an accuracy of 93% for both SVM and random forests. However, the study also highlights the challenges of accurately detecting cyberbullying, particularly given the nuanced and context-dependent nature of online communication. This paper concludes by discussing the implications of these findings for future research and the development of practical tool for cyberbullying prevention and intervention.