This study investigates the possibility of assessing the newly introduced topics of matrices and population proportion on the College Scholastic Ability Test (CSAT) as the 2022 revised mathematics curriculum is implemented in high schools.The analysis focuses on curricular changes and achievement standards related to these topics, and considers their assessability through the development of items aligned with the structure and requirements of the CSAT mathematics section.The results show that matrices may be assessed both as an independent component of 'Common Mathematics1' and through items that integrate matrix-related ideas within broader mathematical contexts.Population proportion can likewise be assessed in Probability and Statistics through tasks that require students to engage in reasoning and interpretation.The study also identifies several limitations in fully reflecting the educational intentions of these topics within the constraints of the CSAT assessment framework.Accordingly, this study suggests that, in order for the aims and intentions of the 2022 revised mathematics curriculum to be faithfully reflected in assessment, consistent national-level guidelines are needed that expand the interpretation of achievement standards, diversify assessment methods, and broaden the range of item contexts, so that instruction and assessment within the CSAT can be more organically aligned.

In the rapidly evolving era of digital education, generative Artificial Intelligence (genAI) tools have become significant resources for students seeking assistance in various subjects, including mathematics (Baidoo-Anu & Ansah, 2023).These tools provide instantaneous and personalized assistance, offering a new tool to

This study conducted a scoping review of 19 studies on math chatbots conducted in South Korea.The study analyzed key research themes and types, mathematical content and its selection criteria, research methods, roles and design principles of chatbots, technologies employed in chatbots, and the roles of teachers and students in math chatbot research.Through this analysis, the current landscape and growth potential of the math chatbot research ecosystem were identified, leading to several directions for future research.First, 'studies on AI and convergence' , 'exploratory research' , 'research on geometry content' , and 'literature reviews' should be expanded.Second, further studies should establish a consensus on the safety of personalized instructional chatbots and then develop technical solutions for their implementation.Third, additional studies are needed on teachers' roles as ethical supervisors and students' roles as ethical adherents regarding AI and chatbots.Fourth, future research should allocate adequate research resources to studies on teachers' noticing and specialized content knowledge (SCK) in chatbot-based teaching and learning environments, as well as the impact of chatbots on students' thinking processes.Finally, three research topics for a systematic literature review, which should be conducted once sufficient chatbot research has been accumulated, were suggested.The study provided specific directions to ensure the systematic and continuous growth of the math chatbot research ecosystem in South Korea through this analysis.

This study aimed to examine trends in research on the geometry domain of mathematics education in Korea through keyword network analysis.To achieve this, keywords from research papers related to mathematics education and geometry published in domestic journals from 2000 to May 2024 were collected, totaling 323 papers.The network analysis was conducted by dividing the data into the entire research period and specific curriculum revision periods.The results of the analysis showed that, first, the keyword with the highest frequency of occurrence, degree centrality, and closeness centrality was 'middle school' , while 'justification' showed high centrality despite a lower frequency ranking.Second, sub-network analysis using modularity and ego network analysis identified characteristics of research across different school levels, studies on mathematical giftedness, and comparative analyses of textbooks following curriculum revisions.Third, the research keywords during curriculum revision periods indicated a shift from studies focusing on the logical structure and reasoning of Euclidean geometry to those emphasizing intuitive thinking, practicality, and real-life problem-solving, aligning with the revised curriculum's focus.By categorizing and analyzing the research subjects in various ways, the study identified the core and connections of research topics in the geometry domain of mathematics education, aiding in the understanding of research trends and providing implications for future research.

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This study explored the factors that influence elementary school teachers' intention to use an artificial intelligence (AI) math learning system and analyzed the interactions and relationships among these factors.Based on the technology acceptance model, perceived usefulness for math learning, perceived ease of use of AI, and attitude toward using AI were analyzed as the main variables.Data collected from a survey of 215 elementary school teachers was used to analyze the relationships between the variables using structural equation modeling.The results of the study showed that perceived usefulness for math learning and perceived ease of use of AI significantly influenced teachers' positive attitudes toward AI math learning systems, and positive attitudes significantly influenced their intention to use AI.These results suggest that it is important to positively change teachers' perceptions of the effectiveness of using AI technology in mathematics instruction and their attitudes toward AI technology in order to effectively adopt and utilize AI-based mathematics education tools in the future.

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.

Measurement is an imperative content area of early elementary mathematics, but it is reported that students' understanding of units in measurement situations is insufficient despite its importance.Therefore, this study examined lower-grade elementary students' quantitative reasoning of units in length measurement by identifying the levels of reasoning of units.For this purpose, we collected and analyzed the responses of second-grade elementary school students who engaged in a set of length measurement tasks using an open number line in terms of unitizing, iterating, and partitioning.As a result of the study, we categorized students' quantitative reasoning of unit levels into four levels: Iterating unit one, Iterating a given unit, Relating units, and Transforming units.The most prevalent level was Relating units, which is the level of recognizing relationships between units to measure length.Each level was illustrated with distinct features and examples of unit reasoning.Based on the results of this study, a personalized plan to the level of unit reasoning of students is required, and the need for additional guidance or the use of customized interventions for students with incomplete unit reasoning skills is necessary.

The value that students consider important in math learning may vary depending on the student's socio-cultural background and personal experience.Although socio-cultural backgrounds are very diverse, I considered overseas vs domestic Koreans, and secondary school levels as variables in terms of students' educational experiences.Overseas students had a lower perception of the value in mathematics than domestic students, especially about understanding mathematics knowledge and the value of the latest teaching and learning methods.Middle school students perceived the value of mathematics as an activity higher than that of high school students, and high school students perceived student agency as a higher value than middle school students.In addition, I considered meta-affect as one of the individual students' experiences, finally meta-affect was a variable that could explain value perception in math learning, and in particular, affective awareness of achievement, affective evaluation of value, and affective using were significant.From the results, I suggested that research on ways to improve the value and the meta-affect in math learning, test to measure the value of students in math learning, the expansion of research subjects to investigate the value in math learning, and a teacher who teaches overseas Koreans are needed.

This study examined the effect and structural relationship of math teachers' teaching ability and class activity types on learners' value perception, confidence, and interest of mathematics at the student level and teacher level.To this end, data from 2nd graders of korea middle school in TIMSS 2019 were applied to the multilevel structural equation model.As a result of the analysis, the teaching ability of math teachers had a positive effect on value perception, confidence, and interest of mathematics at the student level and teacher level.Also, math value perception and math confidence had a positive effect on math interest.and it was confirmed that the teaching ability of math teachers indirectly had a positive effect on math interest by mediating math value perception and math confidence.In addition, the math class activity of applying what was learned to problems had a positive effect on math value perception, but it had a negative effect on math interest.and the class activity of the same ability group had a positive effect on math confidence and math interest.This study presents meaningful implications for math classes in the school field through a multilevel analysis of the student level and the teacher level.