• Communications of Mathematical Education
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• v.34 no.3
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• pp.235-256
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• 2020

The purpose of this study was to investigate the experience of pre-service mathematics teachers who attended at a university course combined with teaching practicum based on design thinking process to identify the change of their awareness of its activities. For the research, 8 pre-service mathematics teachers participated in a mathematics major course, consisting of 5 phases of design thinking formed by Stanford d.school. In the end of the course, qualitative data were collected through individual and focus group interviews and the course activities. By data analysis, the results of this study were as follows. Firstly, the participants' perspectives of design thinking activities were changed from the difficulty and ambiguity of its activity in the beginning of the process to positiveness with competence of solving authentic problem in terms of teaching practicum over time. Secondly, the participating pre-service teachers emphasized that design thinking activities helped them prepare well teaching practicum and raise understanding of students they met in the school fields. Thirdly, some research participants went through the difficulty in utilizing their products drawn from 4th phase (prototyping) of design thinking process depending on the acceptance of their guidance teachers. Fourthly, the research participants also pointed out that the design thinking was a significant activity in that they learned how to understand and communicate with their students and how to collaborate with team members and it gave an insight about the preparation for a class. Through these results, this study identified the possibility of using the design thinking process for pre-service mathematics teachers' teaching practicum. In addition, the research put forward some implications for better use of design thinking in teacher education.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.599-600
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• 2023

본 연구는 한국 주식 시장인 KRX 데이터에 중점을 둔 투자 전략의 최적화를 목표로 하였다. 전통적인 기술 분석 방법은 투자자들의 경험에 의존하여 파라미터를 선택하였다. 하지만 이 연구에서는 기존의 경험에 기반한 파라미터 선택 대신 유전 알고리즘을 사용하여 파라미터를 최적화했다. 결과적으로, 이 전략은 상승장과 하락장 모두에서 buy-and-hold 전략보다 더 나은 성과를 보였다. 이는 기술 분석의 파라미터 최적화의 중요성을 강조하며, 더 효과적인 투자 전략 개발의 가능성을 보여준다.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.830-833
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• 2020

콜센터에서 인력 스케줄링은 매우 중요하다. 모든 콜센터에서 인건비는 고정비 성격이 강하여 차지하는 비중이 매우 높아 콜센터의 이익을 좌지우지한다. 그렇기 때문에 콜센터의 적정 인력의 고용과 배치는 인건비 뿐만 아니라 콜 성공률 또한 직결되어 있어 콜센터 운영에서 중요한 사안이라고 할 수 있다. 대부분의 콜센터가 현재까지도 관리자의 경험에 의해 인력배치를 수립하는데, 이러한 방법은 과학적이지 않으며 인원수에 영향을 미치는 모든 변수들을 고려할 수 없다. 과거 수학적 모델을 수립하는 것이었다면, 지금은 모델을 학습시키고, 학습된 모델을 기반으로 미래의 고객과 인원수를 예측해야 한다. 본 논문에서는 수리제약식을 통해 다양한 변수들을 고려하고 비선형 정수 계획법과 딥러닝 기반의 예측 값을 이용하여 비선형 정수계획법을 통해 최적의 인력배치 스케줄링을 수립하였다.

• School Mathematics
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• v.19 no.1
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• pp.95-116
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• 2017

Through the teaching experiments, we investigated a series of processes for obtaining the differential coefficient at x=0 of the exponential function $y=2^x$ based on the process of constructing the natural constant e and the understanding of it. and all of the students who participated in this study were students who had no experience of calculating the derivative of the exponential function. The purpose of this study was not to generalize the responses of students but to suggest implications for mathematical concept mapping related to calculus by analyzing various responses of students participating in experiments. It is expected that the accumulation of research data derived in this kind of research on the way of understanding and composition of learners will be an important basic data for presenting the learning model related to calculus.

• Journal of the Korean School Mathematics Society
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• v.19 no.4
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• pp.373-394
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• 2016

The "Figure Equation" chapter of current high school curriculum prevents students from relating the concept with what they studied in middle school Euclidean geometry. Woo(1998) concerns that the curriculum introduces the concept merely in algebraic ways without providing students with opportunities to relate it with their prior understanding of geometry, which is based on Euclidean one. In the present study, a sequence of GeoGebra-embedded-geometry lessons was designed so that students could be introduced to and solve problems of the Analytic Geometry by triggering their prior understanding of the Euclidean Geometry which they had learnt in middle school. The study contributes to the field of mathematics education by suggesting a sequence of geometry lessons where students could introduce to the coordinate geometry meaningfully and conceptually in high school.

• The Mathematical Education
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• v.61 no.1
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• pp.29-45
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• 2022

This study tried to analyze the problems by critically examining how the chance is taught in relation to the concept of chance and randomness in the Korean elementary school mathematics curriculum. To this end, the concepts of chance and randomness were first examined, and problems were presented in based on this by the literature analysis on mathematics curriculum material and textbooks for elementary school in Korea. As a result, there was a lack of experience in reasoning based on data, and randomness instruction was not performed properly. In addition, as the teaching of the sample space was omitted, contradictory materials were being used. Moreover, it was pointed out that the teaching of chance is focused on a specific grade level. For the improvement of the teaching of chance, a teaching of the probability experiment and the sample space were mainly suggested, and it was also suggested that the contents of the data area be adjusted for the composition focused on a specific grade.

• 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).

• Communications of Mathematical Education
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• v.36 no.2
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• pp.287-311
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• 2022

This study was related to the cases in which pre-service elementary teachers designed math lessons tailored to math underachievers with learning trajectories and universal design for learning. Learning trajectories can be a basis to identify students' current state of understanding and development, and make a lesson plan responsively tailored to underachievers' state. And universal design for learning is a framework that removes potential barriers that may exist in math lessons from the time the lessons are planned, and guides the rich learning environment accessible to all learners. In order to provide an experience of designing math lessons considering the characteristics of math underachievers, this study required pre-service elementary teachers to create learning trajectories and make lesson plans with the principles of universal design for learning. The characteristics of the learning trajectories shown in the lesson plans and the results of applying the principles of universal design for learning were analyzed. By discussing the results, implications were derived regarding the necessity of lesson planning for math underachievers and the development of lesson planning competency of pre-service elementary mathematics teachers in teacher education.

• 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 the Korean School Mathematics Society
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• v.22 no.3
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• pp.241-256
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• 2019

In this paper, we analyzed the types of tasks presented in the 'Probability and Statistics' textbooks and how the cognitive competences required to perform the tasks provide students with opportunity-to-learn. To this end, the analysis of the 9 books of the 'Probability and Statistics' test textbooks according to the 2015 revised mathematics curriculum showed that the context-based tasks(CF type, RE type) ranged from 67.5% to 78.0% of the total number of tasks in each textbook, but the ratio of relevant and essential tasks related to real life is from 0.4% to 2.0%, it was found that most of the context-based tasks presented in the textbooks were disguised as real life materials. The cognitive competences of context-based tasks ranged from 29.6% to 50.0% in reproduction category, from 33.8% to 54.3% in connection category, and from 8.8% to 20.0% in reflection category. As a result, there was not enough opportunity-to-learn for students to experience reflective cognitive processes.