• Journal of Digital Convergence
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• v.17 no.7
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• pp.285-292
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• 2019

With the popularization of PC, SNS and IoT, a lot of data is generated and the amount is increasing exponentially. Artificial neural network learning is a topic that attracts attention in many fields in recent years by using huge amounts of data. Artificial neural network learning has shown tremendous potential in speech recognition and image recognition, and is widely applied to a variety of complex areas such as medical diagnosis, artificial intelligence games, and face recognition. The results of artificial neural networks are accurate enough to surpass real human beings. Despite these many advantages, privacy problems still exist in artificial neural network learning. Learning data for artificial neural network learning includes various information including personal sensitive information, so that privacy can be exposed due to malicious attackers. There is a privacy risk that occurs when an attacker interferes with learning and degrades learning or attacks a model that has completed learning. In this paper, we analyze the attack method of the recently proposed neural network model and its privacy protection method.

• Journal for History of Mathematics
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• v.32 no.2
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• pp.47-59
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• 2019

Hua Loo-Keng(华罗庚, 1910-1985) is one of well-known prominent Chinese mathematicians. While Waring problem is one of his research interests, he made lots of contributions on various mathematical fields including skew fields, geometry of matrices, harmonic analysis, partial differential equations and even numerical analysis and applied mathematics, as well as number theory. He also had devoted his last 20 years to the popularization of mathematics in China. We look at his personal and mathematical life, and consider the meaning of his activity of popularizing mathematics from the cultural perspective to understand the recent rapid developments of China in sciences including mathematics and artificial intelligence.

• The Mathematical Education
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• v.63 no.2
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• pp.209-231
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• 2024

The education sector is undergoing significant changes due to the Fourth Industrial Revolution and the advancement of artificial intelligence. Particularly, the importance of education based on artificial intelligence is being emphasized. Accordingly, the purpose of this study is to develop a statistics education program using deep learning prediction in high school mathematics and to examine the impact of such statistically problem-solvingcentered statistics education programs on high school students' statistical literacy and computational thinking. To achieve this goal, a statistics education program using deep learning prediction applicable to high school mathematics was developed. The analysis revealed that students' understanding of context improved through experiencing how data was generated and collected. Additionally, they enhanced their comprehension of data variability while exploring and analyzing various datasets. Moreover, they demonstrated the ability to critically analyze data during the process of validating its reliability. In order to analyze the impact of the statistics education program on high school students' computational thinking, a paired sample t-test was conducted, confirming a statistically significant difference in computational thinking between before and after classes (t=-11.657, p<0.001).

• Education of Primary School Mathematics
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• v.26 no.3
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• pp.163-180
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• 2023

This study aimed to investigate the factors influencing the intentions of elementary school teachers to use artificial intelligence (AI) in mathematics lessons and to identify the essential prerequisites for the effective implementation of AI in mathematics education. To achieve this purpose, we examined the structural relationship between elementary school teachers' TPACK(Technological Pedagogical Content Knowledge) and the TAM(Technology Acceptance Model) using structural equation model. The findings of the study indicated that elementary school teachers' TPACK regarding the use of AI in mathematics instruction had a direct and significant impact on their perceived ease of use and perceived usefulness of AI. In other words, when teachers possessed a higher level of TPACK competency in utilizing AI in mathematics classes, they found it easier to incorporate AI technology and recognized it as a valuable tool to enhance students' mathematics learning experience. In addition, perceived ease of use and perceived usefulness directly influenced the attitudes of elementary school teachers towards the integration of AI in mathematics education. When teachers perceived AI as easy to use in their mathematics lessons, they were more likely to recognize its usefulness and develop a positive attitude towards its application in the classroom. Perceived ease of use, perceived usefulness, and attitude towards AI integration in mathematics classes had a direct impact on the intentions of elementary school teachers to use AI in their mathematics instruction. As teachers perceived AI as easy to use, valuable, and developed a positive attitude towards its incorporation, their intention to utilize AI in mathematics education increased. In conclusion, this study shed light on the factors influencing elementary school teachers' intentions to use AI in mathematics classes. It revealed that teachers' TPACK plays a crucial role in facilitating the integration of AI in mathematics education. Additionally, the study emphasized the significance of enhancing teachers' awareness of the advantages and convenience of using AI in mathematics instruction to foster positive attitudes and intentions towards its implementation. By understanding these factors, educational stakeholders can develop strategies to effectively promote the utilization of AI in mathematics education, ultimately enhancing students' learning outcomes.

• East Asian mathematical journal
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• v.38 no.4
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• pp.415-437
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• 2022

Recently, various platforms of education technology (Edu-Tech) that use artificial intelligence have been developed in the field of mathematics education. The case study in this paper reports the learning experience of a high school student who was directed to learn mathematics through the self-directed learning process provided by a mathematics learning platform using Edu-Tech with the intervention of mentoring provided by his teacher. The study found that the mentoring intervention could make an effective contribution to student's mathematics learning by playing the role of an auxiliary tool for the self-directed learning over time. In this paper, we explain the nature of the challenges that the student encountered in the process of self-directed learning and the roles that the teacher mentoring has played in this process.

• Korean Journal of Mathematics
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• v.28 no.2
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• pp.343-359
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• 2020

The paper aim is to resolve the issue of ranking to the fuzzy numbers in decision analysis, artificial intelligence and optimization. In the literature lot of ideologies have been established for ranking to the fuzzy numbers, that ideologies have some restrictions and limitations. In this paper, we proposed a method based on cubic picture fuzzy information's, for ranking to defeat the existing restrictions. Further introduced some cubic picture fuzzy algebraic and cubic picture fuzzy algebraic^* aggregated operators for aggregated the information. Finally, a multi-attribute decision making problem is assumed as a practical application to establish the appropriateness and suitability of the proposed ranking approach.

• Communications of Mathematical Education
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• v.32 no.3
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• pp.245-255
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• 2018

In this paper, we discuss efforts that has been made by mathematics departments in Korea to meet the need of the 4th industrial revolution era. First of all, we introduce various industrial mathematics programs that some universities in Korea started to provide in order to nurture math/math education graduate to be prepared for the demand of the society. We also introduced a mathematics for Big Data course that we did offer recently which can be shared.

• Journal of the Korea Convergence Society
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• v.7 no.4
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• pp.123-131
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• 2016

In this paper, we discussed learner's capability enhancement education suitable for the age of artificial intelligence (AI) using game analysis and archival research based on the 2016 Google Deepmind Challenge match between AI that possessed the finest deep neural networks and the master Baduk player that represented the best of the human minds. AlphaGo was a brilliant move that transcended the conventional wisdom of Baduk and introduced a new paradigm of Baduk. Lee Sedol defeated AlphaGo via the 'divine move and Great idea' that even AlphaGo could not have calculated. This was the triumph of human intuition and insights, which are deeply embedded in human nature as well as human courage and strength. Convergence science education that cultivates student abilities that can help them control machines in the age of AI must be in the direction of developing diverse human insights and positive spirits embedded in human nature not possessed by AI via implementing hearts-on experience and topophilia education obtained from the nature.

• Communications of Mathematical Education
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• v.34 no.3
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• pp.215-234
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• 2020

With the advent of the AI, the need to use AI in the field of education is widely recognized. The purpose of this study is to shed light on how prospective mathematics teachers perceive the need for AI and the role of teachers in future mathematics education. As a result, with regard to teaching, prospective teachers recognized that the use of AI in school mathematics is a demand of a new era, that various types of lesson can be implemented, and that accurate knowledge and information can be delivered. On the other hand, they recognized that AI has limitations in having cognitive and emotional interactions with students. As for mathematics learning, the prospective teachers recognized that AI can provide individualized learning, be used for supplementary learning outside of school, and stimulate students' interest in learning. However, they also said that learning through AI could undermine students' ability to think on their own. With regard to assessment, the prospective teachers recognized that AI is objective, fair and can reduce teachers' workload, but they also said that AI has limitations in evaluating students' abilities in constructed-response items and in process-focused assessment. The roles of teachers that the prospective teachers think were to conduct a lesson, emotional interaction, unstructured assessment, and counseling, and those of AI were individualized learning, rote learning, structured assessment, and administrative works.

• The Mathematical Education
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• v.62 no.2
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• pp.269-287
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• 2023

Matrix theory is widely used not only in mathematics, natural sciences, and engineering, but also in social sciences and artificial intelligence. In the 2009 revised mathematics curriculum, matrices were removed from high school math education to reduce the burden on students, but in anticipation of the age of artificial intelligence, they will be reintegrated into the 2022 revised education curriculum. Therefore, there is a need to analyze the matrix content covered in other countries to suggest a meaningful direction for matrix education and to derive implications for textbook composition. In this study, we analyzed the German mathematics curriculum and standard education curriculum, as well as the matrix units in the German Hesse state mathematics curriculum and textbook, and identified the characteristics of their content elements and development methods. As a result of our analysis, it was found that the German textbooks cover matrices in three categories: matrices for solving linear equations, matrices for explaining linear transformations, and matrices for explaining transition processes. It was also found that the emphasis was on mathematical reasoning and modeling when learning matrices. Based on these findings, we suggest that if matrices are to be reintegrated into school mathematics, the curriculum should focus on deep conceptual understanding, mathematical reasoning, and mathematical modeling in textbook composition.