• Education of Primary School Mathematics
• /
• v.27 no.1
• /
• pp.19-38
• /
• 2024

This study aims to analyze the characteristics of students' understanding of artificial intelligence and mathematical concepts by developing and applying an artificial intelligence education program for mathematics convergence using robots. To this end, we analyzed the content standards of elementary artificial intelligence education to extract conceptual elements of artificial intelligence and identified mathematics achievement standards that can effectively integrate them. In particular, a five-session (15 classes in total) program was developed by selecting the units 'angle' and 'quadrilateral' suitable for utilizing the robot's movement and reorganizing the lesson to integrate the mathematics achievement standard with the artificial intelligence content elements. As a result of applying this to 22 fourth grade elementary school students over five months and analyzing the students' understanding revealed by topic of artificial intelligence content, the artificial intelligence education program for mathematics convergence using robots was helpful in students' understanding artificial intelligence principles and mathematical concepts. In addition, the use of robots was confirmed to improve students' understanding of artificial intelligence and mathematics as well as their participation in class by making them visually check a series of performing procedures.

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

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

• The Mathematical Education
• /
• v.63 no.2
• /
• pp.387-392
• /
• 2024

The use of artificial intelligence (AI) in mathematics education has advanced as a means for promoting understanding of mathematical concepts, academic achievement, computational thinking, and problem-solving. From a total of 13 studies in this special issue, this editorial reveals threads of potential and future directions to advance mathematics education with the integration of AI. We generated five themes as follows: (1) using ChatGPT for learning mathematical content, (2) automated grading systems, (3) statistical literacy and computational thinking, (4) integration of AI and digital technology into mathematics lessons and resources, and (5) teachers' perceptions of AI education. These themes elaborate on the benefits and opportunities of integrating AI in teaching and learning mathematics. In addition, the themes suggest practical implementations of AI for developing students' computational thinking and teachers' expertise.

• Communications of Mathematical Education
• /
• v.37 no.3
• /
• pp.443-465
• /
• 2023

This study examines the content of vectors and matrices in Artificial Intelligence Mathematics textbooks (AIMTs) from the 2015 revised mathematics curriculum. We analyzed the implementation of foundational mathematical concepts, specifically definitions and related sub-concepts of vectors and matrices, in these textbooks, given their importance for understanding AI. The findings reveal significant variations in the presentation of vector-related concepts, definitions, sub-concepts, and levels of contextual information and descriptions such as vector size, distance between vectors, and mathematical interpretation. While there are few discrepancies in the presentation of fundamental matrix concepts, differences emerge in the subtypes of matrices used and the matrix operations applied in image data processing across textbooks. There is also variation in how textbooks emphasize the interconnectedness of mathematics for explaining vector-related concepts versus the textbooks place more emphasis on AI-related knowledge than on mathematical concepts and principles. The implications for future curriculum development and textbook design are discussed, providing insights into improving AI mathematics education.

• The Mathematical Education
• /
• v.63 no.2
• /
• pp.369-385
• /
• 2024

With the advancement of digital technology, a variety of digital materials are being utilized in education. For their appropriate use of digital resources, teachers need to be able to evaluate the quality of digital resource and determine the suitability for teaching. This study explored how preservice teachers evaluate TocToc-Math, an Artificial Intelligence (AI)-based math support system. Based on an evaluation framework developed through prior research, preservice teachers evaluated TocToc-Math with evidence-based criteria, including content quality, pedagogy, technology use, and mathematics curriculum alignment. The findings shows that preservice teachers positively evaluated TocToc-Math overall. The evaluation tendencies of preservice teachers were classified into three groups, and the specific characteristics of each factor differed depending on the group. Based on the research results, we suggest implications for improving preservice teachers' evaluation abilities regarding the use of digital technology and AI in mathematics education.

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

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

• The Journal of Korean Association of Computer Education
• /
• v.23 no.4
• /
• pp.1-11
• /
• 2020

The purpose of this study is to propose the direction of AI education in K-12 education through investigating and analyzing aspects of the purpose, content, and methods of AI education as the curriculum and teacher training factors. We collected and analyzed 9 papers as the primary literature and 11 domestic and foreign policy reports as the secondary literature. The collected literatures were analyzed by applying a descriptive reviews, and the implications were derived by analyzing the curriculum components and TPACK elements for multi-dimensional analysis. As a result of this study, AI education targets were divided into three steps: AI users, utilizer, and developers. In K-12 education, the user and utilizer stages are appropriate, and artificial intelligence literacy must be included for user education. Based on the current computing thinking ability and coding ability for utilizer education, the implication was derived that it is necessary to target the ability to create creative output by applying the functions of artificial intelligence. In addition to the pedagogical knowledge and the ability to use the platform, The teacher training is necessary because teachers need content knowledge such as problem-solving, reasoning, learning, perception, and some applied mathematics, cognitive / psychological / ethical of AI.

• The Mathematical Education
• /
• v.58 no.2
• /
• pp.187-223
• /
• 2019

This study aims to investigate the aspects of revision in the external and internal structure of curriculum and documentation in Korea and Japan and to propose the direction and task to enhance the current framework of the national curriculum. Japan has been selected for comparison in that it explicitly prepared social changes such as the dramatic evolution of artificial intelligence and population aging in its new curriculum. Therefore, various aspects of revision were analyzed the 2009 & 2015 revised mathematics curriculum of Korea and the 2008 & 2017 mathematics curriculum of Japan respectively in the elementary, middle, and high school grade bands. Then, the differences between the two countries were identified through comparison. First, the structure of the mathematics curriculum in Japan was connected with the general guidelines more tightly than Korea, and the external structure of the mathematics curriculum stayed consistently after the revision. Second, contrary to Korea, which pursued the appropriateness and reduction of mathematical content, Japanese mathematics curriculum has been pursuing detailed contents both quantitatively and qualitatively. Lastly, Japan emphasized statistical problem-solving ability. Based on this, we suggested considering of consistency in the structure curriculum documentation, detailing contents of the curriculum, and strengthening of statistical education.