• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.24 no.1
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• pp.79-84
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• 2020

In this article, we implement a recently developed fast Monte Carlo simulation (MCS) for pricing equity-linked securities (ELS), which is most commonly issued autocallable structured financial derivative in South Korea, on the mobile platform. The fast MCS is based on Brownian bridge technique. Although mobile platform devices are easy to carry around, mobile platform devices are slow in computation compared to desktop computers. Therefore, it is essential to use a fast algorithm for pricing ELS on the mobile platform. The computational results demonstrate the practicability of Android application implementation for pricing ELS.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.26 no.4
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• pp.343-352
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• 2022

We present the user-friendly graphical user interface design and implementation of Monte Carlo simulation (MCS) for computing option price of the four-underlying asset step-down equity linked securities (ELS) using the Android platform. The ELS has been one of the most important and influential financial products in South Korea. Most ELS products are based on one-, two-, and three-underlying assets. However, currently there is a demand for higher coupon payment from ELS products because of the increased interest rate in financial market. In order to allow the investors to have higher coupon payment, it is necessary to design a multi-asset ELS such as four-asset step-down ELS. We conduct the computational experiments to demonstrate the performance of the Android platform for pricing four-asset step-down ELS. Furthermore, we perform a comparison test with a three-asset step-down ELS.

• 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.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.23 no.3
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• pp.237-251
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• 2019

We extend the previous work [J. Korean Soc. Ind. Appl. Math. 21(3) 181] to two-and three-asset equity-linked securities (ELS). In the real finance market, two-or three-asset ELS is more popular than one-asset ELS. Therefore, we need to develop mobile platform for pricing the two-and three-asset ELS. The mobile implementation of the ELS pricing will be very useful in practice.

• Communications of Mathematical Education
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• v.36 no.3
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• pp.417-438
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• 2022

The purpose of this study is to suggest implications for mathematics teaching and learning when using AI-based educational platforms that support personalized mathematics learning. To this end, we selected five platforms(Knock-knock! Math Expedition, knowre, Khan Academy, MATHia, CENTURY) and analyzed how the AI-based educational platforms for mathematics reflect the three elements(PLP, PLN, PLE) to support personalized learning. The results of this study showed that although the characteristics of PLP, PLN, and PLE implemented on each platform varied, they were designed to form PLEs that allow learners to make their autonomous decisions about learning based on PLP and PLN. The significance of this study can be found in that it has improved the understanding and practicability of personalized mathematics learning with the AI-based educational platforms.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.21 no.3
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• pp.181-202
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• 2017

In this paper, we develop a mobile platform for pricing equity linked securities(ELS) using Monte Carlo simulation. Mobile phone or smartphone is an important part of most people's lives and has become an everyday item at the present day. Moreover, importance of technologies for anytime and anywhere is increasing daily. Thus, we construct a mobile computing environment for pricing ELS instead of desktops or laptop computers. We provide a detailed Java programming code and a process manual to easily follow up all processes of this paper.

• Communications of Mathematical Education
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• v.36 no.1
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• pp.1-21
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• 2022

The purpose of this study is to analyze the current situation of EduTech, which is proposed as a way to build a flexible learning environment regardless of time and place according to the use of digital technology in mathematics subjects. The process of designing classes to use the EduTech platform, which is still in the development introduction stage, in public education is still difficult, and research to observe its effects and characteristics is also in its early stages. However, in the stage of preparing for future education, it is a meaningful process to grasp the current situation and point out the direction in preparation for the future in which EduTech will be actively applied to education. Accordingly, the current situation and utilization trends of EduTech at home and abroad were confirmed, and the functions and roles of EduTech platforms used in mathematics were analyzed. As a result of the analysis, the EduTech platform was pursuing learners' self-directed learning by constructing its functions so that they could be useful for individual learning of learners in hierarchical mathematics education. In addition, we have confirmed that the platform is evolving to be useful for teachers' work reduction, suitable activities, and evaluations learning management. Therefore, it is necessary to implement instructional design and individual customized learning support measures for students that can efficiently utilize these platforms in the future.

• Journal of the Korean Data and Information Science Society
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• v.26 no.2
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• pp.475-486
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• 2015

Mining the microarray data accumulated in the public data repositories can save experimental cost and time and provide valuable biomedical information. Big data analysis pooling multiple data sets increases statistical power, improves the reliability of the results, and reduces the specific bias of the individual study. However, integrating several data sets from different studies is needed to deal with many problems. In this study, I limited the focus to the cross platform classification that the platform of a testing sample is different from the platform of a training set, and suggested a simple classification method based on rank. This method is compared with the diagonal linear discriminant analysis, k nearest neighbor method and support vector machine using the cross platform real example data sets of two cancers.

• East Asian mathematical journal
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• v.39 no.4
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• pp.419-436
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• 2023

In this study, we aimed to develop a teacher-adaptive platform model that enhances teachers' instructional activities and teaching capabilities, allowing them to conduct intended lessons effectively. The platform is designed to support various teaching and learning activities based on the instructional situation, and additionally provides teaching and learning materials, assessment questions, and results. The developed teaching and learning platform utilized Moodle, an open-source-based LMS solution that provides various tools for online learning. The platform was specifically designed for teaching conic sections in high school geometry, and it was constructed to enable teachers to deliver their intended lessons effectively.

• The Mathematical Education
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• v.59 no.4
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• pp.373-387
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• 2020

The purpose of this study is to verify the effects of personalized learning platforms applied with machine learning recommendation modules that upgrade recommended algorithms by themselves through learning big data analysis on students' learning time, self-directed learning ability, mathematics achievement, and attitudes toward mathematics, and the correlation between them. According to the study, customized learning affected learning time, self-directed learning ability and mathematics attitude, while learning time affected self-directed learning ability. Self-directed learning ability has had a significant impact on the attitude of mathematics and mathematical achievements. As a result of the mediated effectiveness test, the indirect impact of customized learning on mathematics attitude and mathematics performance was significant through the medium of learning time and self-directed learning ability.