• Education of Primary School Mathematics
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• v.27 no.3
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• pp.261-279
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• 2024

The purpose of this study is to examine the characteristics of AI courseware for mathematics learning based on Choppin et al.'s (2014) digital typology and to derive implications for directions for AI courseware development. For this purpose, 12 types of AI courseware actively used in domestic were selected for analysis, and the characteristics of these AI courseware in terms of program-student interaction, teacher' s lesson design, and evaluation system were analyzed. As a result, each AI courseware provided unique functional features for students, teachers, and evaluation, but the ability to modify and configure teaching and learning was limited. Based on these results, implications for the direction of development of AI courseware in mathematics education were presented.

• 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.

• The Mathematical Education
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• v.63 no.2
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• pp.351-368
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• 2024

One of the important factors for the effective implementation of artificial intelligence (AI) in mathematics education is the perceptions of the teachers who adopt it. This study surveyed 161 elementary school teachers and 157 secondary mathematics teachers on their perceptions of using AI in mathematics education, grouped into four categories: attitude toward using AI, AI for teaching mathematics, AI for learning mathematics, and AI for assessing mathematics. The findings showed that teachers were most positive about using AI for teaching and learning mathematics, whereas their attitudes towards using AI were less favorable. In addition, elementary school teachers demonstrated a higher positive response rate across all categories compared to secondary mathematics teachers, who exhibited more neutral perceptions. Based on the results, we discussed the pedagogical implications for teachers to effectively use AI in mathematics education.

• Journal of Engineering Education Research
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• v.24 no.3
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• pp.50-57
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• 2021

Although the mathematics education process in AI education is a very important issue, little cases are reported in developing effective methods on AI and mathematics education at the university level. The universities cover all fields of mathematics in their curriculums, but they lack in connecting and applying the math knowledge to AI in an efficient manner. Students are hardly interested in taking many math courses and it gets worse for the students in humanities, social sciences and arts. But university education is very slow in adapting to rapidly changing new technologies in the real world. AI is a technology that is changing the paradigm of the century, so every one should be familiar with this technology but it requires fundamental math knowledge. It is not fair for the students to study all math subjects and ride on the AI train. We recognize that three key elements, SW knowledge, mathematical knowledge, and domain knowledge, are required in applying AI technology to the real world problems. This study proposes a modular approach of studying mathematics knowledge while connecting the math to different domain problems using AI techniques. We also show a modular curriculum that is developed for using math for AI-driven autonomous driving.

• Journal of the Korean School Mathematics Society
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• v.25 no.2
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• pp.149-174
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• 2022

The purpose of this study is to explore the teaching and learning method using artificial intelligence (AI) in the mathematics classroom. To this end, to predict the direction of mathematics education using AI in the mathematics classroom, this study investigates the fields where AI is applied to education, and discuss issues to consider when introducing AI through scenario development using AI in middle school statistics. This study is meaningful in that it specifically considered how artificial intelligence can be grafted into the mathematics classroom through the development of scenarios that integrate and apply artificial intelligence that has been developed and used segmentally in the current middle school statistics. Afterwards, based on the contents of this study, implications for using AI in the math classroom were derived.

• Journal of the Korean School Mathematics Society
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• v.23 no.2
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• pp.223-237
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• 2020

Artificial intelligence technology, which represents the era of the 4th Industrial Revolution, is now deeply involved in our lives, and future education places great emphasis on building students' capabilities for the principles and uses of artificial intelligence. Therefore, the purpose of this study is to develop the contents of AI related education in mathematics, which the relationship is closely connected to each other. To this end, I propose establishing two novel AI-related contents in mathematics education. One subject is related to learning the principle of machine learning based on mathematics foundation. In addition, I draw the core math contents dealt in following subject called 'Basic Mathematics for AI and Data Science.'

• Research in Mathematical Education
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• v.27 no.2
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• pp.223-239
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• 2024

The integration of coding and mathematics education, known as coding-integrated mathematics education, has received much attention due to the strength of Artificial Intelligence-based Science, Technology, Engineering, Arts, and Mathematics (AI-based STEAM) education in improving students' affective domain. The present study investigated the effectiveness of coding-integrated mathematics education on students' development of affective mathematics engagement. Participants in this study were 86 middle and high school students who attended the coding-integrated mathematics program. Surveys of students' affective mathematics engagement were administered before and after the intervention period. The results showed that students' affective mathematics engagement was statistically significantly improved through coding-integrated mathematics education. In particular, students exhibited increased positive affective mathematics engagement in terms of mathematical attitude, emotion, and value. These findings indicate the positive influence of coding-integrated mathematics education on students' learning in mathematics.

• East Asian mathematical journal
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• v.35 no.4
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• pp.509-528
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• 2019

As various changes in education in general and learning environment in particular have promoted different needs and expectations for learning at both personal and social levels, the roles that schools and school teachers typically have with respect to their students are being challenged. Especially with the recent, rapid progress of the artificial intelligence(AI) field, AI could serve beyond the way in which it has been used. Based on a review of some of the related literature and the current development of AI, a view on utilizing AI to be a collaborative, complementary partner with an human mathematics teacher in the classroom in order to support both students and teachers will be discussed.

• The Mathematical Education
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• v.63 no.2
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• pp.123-138
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• 2024

This study described the utilization of ChatGPT in teaching and students' learning processes for the course "Introductory Mathematics for Artificial Intelligence (Math4AI)" at 'S' University. We developed a customized ChatGPT and presented a learning model in which students supplement their knowledge of the topic at hand by utilizing this model. More specifically, first, students learn the concepts and questions of the course textbook by themselves. Then, for any question they are unsure of, students may submit any questions (keywords or open problem numbers from the textbook) to our own ChatGPT at https://math4ai.solgitmath.com/ to get help. Notably, we optimized ChatGPT and minimized inaccurate information by fully utilizing various types of data related to the subject, such as textbooks, labs, discussion records, and codes at http://matrix.skku.ac.kr/Math4AI-ChatGPT/. In this model, when students have questions while studying the textbook by themselves, they can ask mathematical concepts, keywords, theorems, examples, and problems in natural language through the ChatGPT interface. Our customized ChatGPT then provides the relevant terms, concepts, and sample answers based on previous students' discussions and/or samples of Python or R code that have been used in the discussion. Furthermore, by providing students with real-time, optimized advice based on their level, we can provide personalized education not only for the Math4AI course, but also for any other courses in college math education. The present study, which incorporates our ChatGPT model into the teaching and learning process in the course, shows promising applicability of AI technology to other college math courses (for instance, calculus, linear algebra, discrete mathematics, engineering mathematics, and basic statistics) and in K-12 math education as well as the Lifespan Learning and Continuing Education.

• Journal of the Korean School Mathematics Society
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• v.24 no.4
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• pp.391-405
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• 2021

In this study, 'data collection', 'data expression', 'data analysis, and 'optimization and decision-making' were selected as the core AI concepts to be dealt with in the mathematics for AI education. Based on this, the degree of reflection of AI core concepts was investigated and analyzed compared to the mathematical core concepts and content of each area of the elective course. In addition, the appropriateness of the content of was examined with a focus on core concepts and related learning contents. The results provided some suggestions for answering the following four critical questions. First, How to set the learning path for ? Second, is it necessary to discuss the redefinition of the nature of ? Third, is it appropriate to select core concepts and terms for ? Last, is it appropriate to present the relevant learning contents of the content system of ?