• The Mathematical Education
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• v.61 no.1
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• pp.47-62
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• 2022

This study investigated the contents related to the plane figures in the geometry domains of Joseon-Sanhak in the late 18th century and focused on changes in explanations and calculation methods related to plane figures, the rigor of mathematical logic in the problem-solving process, and the newly emerged mathematical topics. For this purpose, We analyzed , and written in the late 18th century and and written in the previous period. The results of this study are as follows. First, an explanation that pays attention to the figures as an object of inquiry, not as a measurement object, and a case of additional presentation or replacing the existing solution method was found. Second, descriptions of the validity of calculations in some problems, explanations through diagrams with figure diagrams, clear perceptions of approximations and explanations of more precise approximation were representative examples of pursuing the rigor of mathematical logic. Lastly, the new geometric domain theme in the late 18th century was Palsun corresponding to today's trigonometric functions and example of extending the relationship between the components of the triangle to a general triangle. Joseon-Sanhak cases in the late 18th century are the meaningful materials which explain the gradual acceptance of the theoretical and argumentative style of Western mathematics

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.3
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• pp.357-365
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• 2018

In the 21st century, as the emergence of the age of creative economy is expected, interest in the cultivation of creative talents required in society around the world is newly rising. Sustainable development education should not be limited to school education, but should be promoted and supported at all social education sites for the purpose of lifelong education. Therefore, the purpose of this paper is to consider the relationship between the possibility of formal and informal learning and the development of capacity in higher education. Exploratory and qualitative research based on intensive groups was designed using several groups of formal and informal learning settings. In China, the creation of a creative economy is set as a major national policy direction for the new government. What is required for talented people in the creative economy era and how to educate them is becoming a major policy issue. The development of core competencies requires multiple contexts based on cognitive non-cognitive disposition. By combining the formal and informal learning environment within higher education for the purpose of a new learning culture, it can provide a variety of situations and improve competency development. While this study can identify aspects of formal and informal learning settings, the interdependencies between them are still difficult to grasp. However, practical implications can be seen clearly. In other words, based on the results, you can point out key aspects of competency acquisition that can be a key element in the higher education environment. As a result, this study analyzed implications for formal and informal learning environments for new ways of developing core competencies in higher education.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.189-217
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• 2023

The metaverse is a virtual world where individuals engage in social, economic, and cultural activities using avatars, which represent an alternate version of oneself within the virtual realm. While the metaverse has garnered global attention recently, research exploring the identity manifested through avatars within the metaverse remains limited. This study investigates the influence of four IT artifact characteristics related to avatar usage in the metaverse-avatar representation, avatar copresence, avatar profiling, and avatar-space interaction-on perceived avatar identity verification. A survey was conducted with 196 experienced users of the Zepeto platform, and hypotheses were tested using structural equation modeling. The analysis results indicate that the use of IT artifacts enabling avatar representation, avatar copresence, and avatar-space interaction has a positive impact on perceived avatar identity verification. This achieved self-verification indirectly influences the satisfaction and subsequent intention to continue using the metaverse. This study contributes to the academic field by empirically verifying the metaverse technological factors that influence the projected identity onto avatars within the metaverse. Furthermore, it is expected to provide effective guidelines for metaverse platform companies in designing and implementing the metaverse.

• Journal of the Korea Computer Graphics Society
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• v.29 no.3
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• pp.85-92
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• 2023

Recently, interest in artificial intelligence has increased due to the development of artificial intelligence fields such as ChatGPT and self-driving cars. However, there are still many unknown elements in training process of artificial intelligence, so that optimizing the model requires more time and effort than it needs. Therefore, there is a need for a tool or methodology that can analyze the weight changes during the training process of artificial intelligence and help out understatnding those changes. In this research, I propose a visualization system which helps people to understand the accumulated weight changes. The system calculates the weights for each training period to accumulates weight changes and stores accumulated weight changes to plot them in 3D space. This research will allow us to explore different aspect of artificial intelligence learning process, such as understanding how the model get trained and providing us an indicator on which hyperparameters should be changed for better performance. These attempts are expected to explore better in artificial intelligence learning process that is still considered as unknown and contribute to the development and application of artificial intelligence models.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.11
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• pp.481-492
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• 2023

This study explores how to build a Korean dataset to extract information from text using generative large language models. In modern society, mixed information circulates rapidly, and effectively categorizing and extracting it is crucial to the decision-making process. However, there is still a lack of Korean datasets for training. To overcome this, this study attempts to extract information using text-based zero-shot learning using a generative large language model to build a purposeful Korean dataset. In this study, the language model is instructed to output the desired result through prompt engineering in the form of "system"-"instruction"-"source input"-"output format", and the dataset is built by utilizing the in-context learning characteristics of the language model through input sentences. We validate our approach by comparing the generated dataset with the existing benchmark dataset, and achieve 25.47% higher performance compared to the KLUE-RoBERTa-large model for the relation information extraction task. The results of this study are expected to contribute to AI research by showing the feasibility of extracting knowledge elements from Korean text. Furthermore, this methodology can be utilized for various fields and purposes, and has potential for building various Korean datasets.

• Communications of Mathematical Education
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• v.37 no.4
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• pp.717-736
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• 2023

The purpose of this study is to develop a statistical program using data and artificial intelligence prediction models and apply it to one class in the sixth grade of elementary school to see if it is effective in improving students' statistical literacy. Based on the analysis of problems in today's elementary school statistical education, a total of 15 sessions of the program was developed to encourage elementary students to experience the entire process of statistical problem solving and to make correct predictions by incorporating data, the core in the era of the Fourth Industrial Revolution into AI education. The biggest features of this program are the recognition of the importance of data, which are the key elements of artificial intelligence education, and the collection and analysis activities that take into account context using real-life data provided by public data platforms. In addition, since it consists of activities to predict the future based on data by using engineering tools such as entry and easy statistics, and creating an artificial intelligence prediction model, it is composed of a program focused on the ability to develop communication skills, information processing capabilities, and critical thinking skills. As a result of applying this program, not only did the program positively affect the statistical literacy of elementary school students, but we also observed students' interest, critical inquiry, and mathematical communication in the entire process of statistical problem solving.

• Journal of Korean Elementary Science Education
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• v.42 no.4
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• pp.591-604
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• 2023

This study investigated the impact of elementary science classes using metaverse on the academic achievement, positive experience in science, and digital literacy of elementary school students. In addition, we examined their perceptions. The respondents were derived from two classes in the sixth grade at an elementary school in Gyeonggi-do, who were selected designated as the experimental (n=29 students) and comparative (n=29) groups, respectively. Across five lessons under the "Plant Structure and Function" unit, the experimental group conducted science classes using the metaverse, whereas the comparative group conducted general textbook-based classes. To investigate instructional effects, the study performed ANCOVA using the pre-test score as a covariate, a survey on the perception of students about science classes using metaverse, and conducted interviews with a number of subjects. The result demonstrated that science classes using metaverse exerted no significant effect on scientific academic achievement and digital literacy. However, the study observed a statistically significant effect on science learning emotion which is a sub-element of positive experiences in science. The students were positively aware of science classes using metaverse in terms of interesting and diverse activities, and free expression of inquiry results and perceived the instability of smart devices and network connections as regrettable. Finally, the study posed the implications of the use of metaverse in science classes.

• Journal of The Korean Association For Science Education
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• v.28 no.6
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• pp.592-602
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• 2008

The purpose of this research is to explore types of pedagogical content knowledge (PCK, hereafter) for effective science teaching. In this research, we explored three science teachers' PCK on light, who were effective in teaching the topic with particular students. The data analysis consisted of identifying the three teachers' unique PCK and ways to improve each teaching episode through the teacher meetings. These analyses, which consisted of verbal exchanges among the participants, were identified on the basis of our understanding. Using grounded theory methods, the types of science PCK drawn from this research are: (1) teaching through curriculum reconstruction, (2) teaching to help students build their own explanation models about surrounding nature, (3) teaching for learning the social language of science, (4) teaching to motivate students' learning needs based on relevance of science to students, (5) teaching through lowering students' learning demand by providing scaffolding, (6) teaching based on the teacher's understanding of students, (7) teaching through inquiry with argumentation, (8) teaching through reification of abstract science concepts, and (9) teaching none marginalized science. Common features of science teachers with quality PCK and their professionalism in teaching are discussed.

• Journal of The Korean Association For Science Education
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• v.26 no.6
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• pp.765-774
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• 2006

The purpose of this study was to suggest an instructional direction for improving scientific problem-finding ability. For this purpose, the present study made an in-depth analysis about activity on problem finding tasks of high school students in an ill-structured scientific problem situation. Subjects were divided into two groups (cooperative and individual) and two kinds of problem finding tasks were administered to two groups. Results indicated that a cooperative activity on problem finding happened to a series of steps exploring problem situation, expressing knowledge and experience, discussing provisional problems, creating various problems and selecting the best problem. Besides, a cooperative activity on problem finding depended heavily on prior knowledge and experience, and in the meantime, various scientific concepts turned out to naturally be expressed. As for the problems found out during a cooperative activity, their scores in creativity factors, including the degree of agreement in original problem selection came out to be on the whole, as excellent. In addition, the types of the problems found out in open problem situation showed that they were more various than those found out in closed problem situation. Subjects perceived that activity on problem finding had positive influence on scientific concept and science process skills. Findings of this study have the following educational implications: First, it is needed to prepare for educational environment that enables students to explore various knowledge and information. Second, the offering of various opportunities is needed to enlarge the scope of scientific knowledge and experience. Third, it is needed to prepare for a study atmosphere that lets students express their knowledge and experiences freely.

• The Mathematical Education
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• v.63 no.1
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• pp.1-18
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• 2024

This study aims to analyze low-performing high school students' difficulties in constructed response (CR) mathematics assessments and explore ways to use writing activities to support student learning. The participants took CR assessments, engaged in guided writing activities across 15 lessons, and provided responses to our interviews. The study identified 20 types of student difficulties, which were sorted into two main categories: "mathematical difficulties" and "CR difficulties." The difficult nature of mathematics as a school subject included a lack of understanding of mathematical concepts, students' difficulty with mathematical symbols and notations, and struggles with word problems. Challenges specific to CR assessments included students' difficulties arising from the testing conditions unlike those of multiple-choice items, and included issues related to constructing appropriate responses and psychological barriers. To address these challenges in CR assessments, the study conducted guided writing activities as an intervention, through which six themes were identified: (1) internalization of mathematical concepts, (2) mathematical thinking through relational understanding, (3) diverse problem-solving methods, (4) use of mathematical symbols, (5) reflective thinking, and (6) strategies to overcome psychological barriers.