• The Mathematical Education
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• v.63 no.2
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• pp.255-272
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• 2024

This study aims to design mathematics-integrated classes that cultivate artificial intelligence (AI) thinking and to analyze students' AI thinking within these classes. To do this, four classes were designed through the integration of the AI4K12 Initiative's AI Big Ideas with the 2015 revised elementary mathematics curriculum. Implementation of three classes took place with 5th and 6th grade elementary school students. Leveraging the computational thinking taxonomy and the AI thinking components, a comprehensive framework for analyzing of AI thinking was established. Using this framework, analysis of students' AI thinking during these classes was conducted based on classroom discourse and supplementary worksheets. The results of the analysis were peer-reviewed by two researchers. The research findings affirm the potential of mathematics-integrated classes in nurturing students' AI thinking and underscore the viability of AI education for elementary school students. The classes, based on AI Big Ideas, facilitated elementary students' understanding of AI concepts and principles, enhanced their grasp of mathematical content elements, and reinforced mathematical process aspects. Furthermore, through activities that maintain structural consistency with previous problem-solving methods while applying them to new problems, the potential for the transfer of AI thinking was evidenced.

• Journal of Engineering Education Research
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• v.7 no.2
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• pp.5-21
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• 2004

The study aims to propose plans to give credit approval to those who obtain authorized civil qualifications, in accordance with the enforcement regulations under the Clause 7, Article 4 of $\ulcorner$the law on credit approval and others$\lrcorner$. Preceding studies on the grounds and principles of credit approval, analyses on the related references and materials, and surveys asking the managers of authorized civil qualifications their opinion over giving credit approval to authorized civil qualifications were conducted as the methodology of this study. Besides, a conference inviting experts from the relevant fields was held to specifically overview the contents and levels to be examined by qualification items, to conduct a face-to-face survey on directions to take in the credit approval of authorized civil qualifications, and to analyze the level and the degree of the difficulty of questions in the examinations of authorized civil qualifications. The contents and the level of credit approval in this study are as follows. For the authorized civil qualification items unable to formulate criteria in accordance with the principles of credit approval taken in the national technique qualification and other national qualifications, two factors were put under consideration for setting the level of the credit approval. First, the level and scope of work were investigated. Second, the content of qualification was compared with the course work of college. The degree of difficulty in the scope and performance of work was reviewed by specialized qualification and general qualification, respectively. Specialized qualification indicates whether or not the required knowledge and technique are acquired for performing duty in specific work fields. It falls into service fields and qualification items except qualification items on general clerical work of the national technique qualification and other national qualifications. To the contrary, general qualification is to prove the degree of acquisition of knowledge and technique for improving the basic competencies throughout diverse types of occupations. It includes competencies to verify language proficiency, mathematical and statistical capacity, problem settlement, negotiation and communication skills. When the authorized civil qualification came under the specialized qualification, the level of qualification was determined in comparison with the level of work of national qualifications. In the case of the general qualification, the credit to be approved was settled by conducting a comparative analysis on the course work of college.

• School Mathematics
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• v.15 no.4
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• pp.819-832
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• 2013

This study was performed to investigate the pedagogical knowledge of pre-service teachers and to explore the possibility of using Lesson Play in pre-service teacher education. Lesson Play refers to a lesson written in script form, featuring imagined interactions between a teacher and his/her students. The participants of this study were 20 pre-service teachers enrolled in mathematics education at a University in Seoul and they conducted a dialogue between a teacher and students who said that 91 is a prime number and 462 is a multiple number of 4. Conclusions were drawn based on the virtual scripts of pre-service teachers. First, it was found that the teaching strategies of pre-service teachers were not diverse. Second, pre-service teachers mainly explained the mathematical principles and concepts. Third, pre-service teachers could not understand the current state of students. Therefore, Lesson Play is helpful to analyse the pedagogical knowledge of pre-service teachers and is a applicable teaching method that can improve the practical knowledge of pre-service teachers.

• Journal of the Korean Geographical Society
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• v.39 no.5 s.104
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• pp.804-818
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• 2004

As spatial data resources become more abundant, the potential for conflict among them increases. Those conflicts can exist between two or many spatial datasets covering the same area and categories. Therefore, it becomes increasingly important to be able to effectively relate these spatial data sources with others then create new spatial datasets with matching geometry and topology. One extensive spatial dataset is US Census Bureau's TIGER file, which includes census tracts, block groups, and blocks. At present, however, census maps often carry information that conflicts with municipally-maintained detailed spatial information. Therefore, in order to fully utilize census maps and their valuable demographic and economic information, the locational information of the census maps must be reconciled with the more accurate municipally-maintained reference maps and imagery. This paper formulates a conceptual framework and two map models of map conflation to make geometrically and topologically consistent source maps according to the reference maps. The first model is based on the cell model of map in which a map is a cell complex consisting of 0-cells, 1-cells, and 2-cells. The second map model is based on a different set of primitive objects that remain homeomorphic even after map generalization. A new hierarchical based map conflation is also presented to be incorporated with physical, logical, and mathematical boundary and to reduce the complexity and computational load. Map conflation principles with iteration are formulated and census maps are used as a conflation example. They consist of attribute embedding, find meaning node, cartographic 0-cell match, cartographic 1-cell match, and map transformation.

• Smart Media Journal
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• v.9 no.3
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• pp.31-40
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• 2020

Currently, black-box-based machine learning algorithms are used to analyze big data in manufacturing. This algorithm has the advantage of having high analytical consistency, but has the disadvantage that it is difficult to interpret the analysis results. However, in the manufacturing industry, it is important to verify the basis of the results and the validity of deriving the analysis algorithms through analysis based on the manufacturing process principle. To overcome the limitation of explanatory power as a result of this machine learning algorithm, we propose a manufacturing big data analysis method using genetic programming. This algorithm is one of well-known evolutionary algorithms, which repeats evolutionary operators such as selection, crossover, mutation that mimic biological evolution to find the optimal solution. Then, the solution is expressed as a relationship between variables using mathematical symbols, and the solution with the highest explanatory power is finally selected. Through this, input and output variable relations are derived to formulate the results, so it is possible to interpret the intuitive manufacturing mechanism, and it is also possible to derive manufacturing principles that cannot be interpreted based on the relationship between variables represented by formulas. The proposed technique showed equal or superior performance as a result of comparing and analyzing performance with a typical machine learning algorithm. In the future, the possibility of using various manufacturing fields was verified through the technique.

• Journal of Convergence for Information Technology
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• v.12 no.3
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• pp.286-293
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• 2022

Recently, the importance of elemental technologies constituting smart factories is increasing due to the 4th Industrial Revolution, and simulation is widely used as a tool to learn these technologies. In particular, PID control is an automatic control technique used in various fields, and most of them analyze mathematical models in certain situations or research on application development with built-in controllers. In actual educational environment requires PID simulator training as well as PID control principles. In this paper, we propose a model that enables education and practice of various PID controls through 3D simulation. The proposed model implemented virtual balls and Fan and implemented PID control by configuring a system so that the force can be lifted by the air pressure generated in the Fan. At this time, the height of the ball was expressed in a graph according to each gain value of the PID controller and then compared with the actual system, and through this, satisfactory results sufficiently applicable to the actual class were confirmed. Through the proposed model, it is expected that the rapidly increasing elemental technology of smart factories can be used in various ways in a remote classroom environment.