• Education of Primary School Mathematics
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• v.26 no.4
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• pp.333-348
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• 2023

Clear analysis and diagnosis of various characteristic factors of individual students is the most important in order to realize individual customized teaching and learning, which is considered the most essential function of math artificial intelligence-based digital textbooks. In this study, analysis factors and tools for individual customized learning diagnosis and construction models for data collection and analysis were derived from mathematical AI digital textbooks. To this end, according to the Ministry of Education's recent plan to apply AI digital textbooks, the demand for AI digital textbooks in mathematics, personalized learning and prior research on data for it, and factors for learner analysis in mathematics digital platforms were reviewed. As a result of the study, the researcher summarized the factors for learning analysis as factors for learning readiness, process and performance, achievement, weakness, and propensity analysis as factors for learning duration, problem solving time, concentration, math learning habits, and emotional analysis as factors for confidence, interest, anxiety, learning motivation, value perception, and attitude analysis as factors for learning analysis. In addition, the researcher proposed noon data on the problem, learning progress rate, screen recording data on student activities, event data, eye tracking device, and self-response questionnaires as data collection tools for these factors. Finally, a data collection model was proposed that time-series these factors before, during, and after learning.

• Education of Primary School Mathematics
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• v.27 no.1
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• pp.39-55
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• 2024

Recently, the 2022 revised mathematics curriculum has established achievement standards for equal sign and equality, and efforts have been made to examine teaching methods and student understanding of relational understanding of equal sign. In this context, this study conducted a lesson that emphasized relational understanding in an introduction to equal sign, and compared and analyzed the understanding of equal sign between the experimental group, which participated in the lesson emphasizing relational understanding and the control group, which participated in the standard lesson. For this purpose, two classes of students participated in this study, and the results were analyzed by administering pre- and post-tests on the understanding of equal sign. The results showed that students in the experimental group had significantly higher average scores than students in the control group in all areas of equation-structure, equal sign-definition, and equation-solving. In addition, when comparing the means of students by item, we found that there was a significant difference between the means of the control group and the experimental group in the items dealing with equal sign in the structure of 'a=b' and 'a+b=c+d', and that most of the students in the experimental group correctly answered 'sameness' as the meaning of equal sign, but there were still many responses that interpreted the equal sign as 'answer'. Based on these results, we discussed the implications for instruction that emphasizes relational understanding in equal sign introduction lessons.

• Education of Primary School Mathematics
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• v.27 no.3
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• pp.227-246
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• 2024

The purposes of this study were to analyze the levels of cognitive demand and questioning types in tasks of 'Data and Chance' presented in elementary mathematics textbooks in Korea, the United States, and Australia. The levels of cognitive demand of textbook tasks were analyzed according to the knowledge and process and thinking types required in the tasks. The tasks were also analyzed for questioning types, answer types, and response types. As a result, in terms of knowledge and process and thinking types in tasks, all three countries had something in common: the percentage of tasks requiring 'representation' and process was the highest, and the percentage of tasks requiring 'basic application of skill/concept' was also the highest. From a thinking types perspective, differences were found between textbook tasks in the three countries in graph and chance learning. The results of analyzing questioning types showed that in all three textbooks, the percentage of observational reasoning questions was highest, followed by the percentage of factual questions. The proportions and characteristics of the constructing questions included in the U.S. and Australian textbooks differed from those in the Korean textbooks. Based on these results, this study presents implications for constructing elementary mathematics textbook tasks in 'Data and Chance.'

• The Mathematical Education
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• v.63 no.3
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• pp.485-503
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• 2024

The purpose of this study is to analyze elementary school teachers' mindsets about students' mathematical ability. For this purpose, we developed a 20-item scale to measure teachers' mindset through a review of the literature. In order to verify the developed scale, a survey was conducted among 158 elementary school teachers, and the structure of the items was analyzed by exploratory factor analysis. As a result, three factors were identified: "growth mindset toward change in mathematical ability", "fixed mindset toward change in mathematical ability", and "mindset toward innate mathematical ability". Four groups were distinguished by latent profile analysis, using the scores on these three factors as variables, to characterize the different groups of teachers based on their mindset. The groups with the most participants in the study were, in order, growth mindset teachers, neutral mindset teachers, strong growth mindset teachers, and fixed mindset teachers. Interviews were also conducted with representative participants from each group to learn more about the characteristics of teachers in each profile. Based on the results of the study, we discussed the implications of mindset in terms of the classification of teachers' mindset about students' mathematical ability, the popularity of growth mindset among elementary school teachers in Korea, and research on teachers' mindset about innate mathematical ability.

• The Mathematical Education
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• v.63 no.3
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• pp.411-436
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• 2024

This study investigated how Korean elementary, middle, and high school students perceive mathematics learning situations to determine whether the mathematics classes provided in schools met the standards of a highquality educational experience. Using a comprehensive survey that considers both formal and implementation aspects of mathematics classes, responses from 15,418 students were analyzed to gain insights into their views on the classroom environment, instructional methods, and overall learning experience. The results indicate that as students advance in grade level, their perceptions of mathematics learning situations become increasingly negative, and mathematics classes are still perceived as being teacher-centered. Additionally, it was found that mathematical manipulatives and technological tools are not being effectively utilized, and that students' learning experiences are influenced by class size and the availability of mathematics subject-exclusive classrooms. Based on these findings, several recommendations were made to improve the quality of mathematics education and enhance students' perceptions: implementing teaching methods that increase student engagement in learnercentered classes, providing opportunities for active and diverse use of teaching aids and technological tools beyond simple calculations, maintaining appropriate class sizes, and expanding the use of mathematics subject-exclusive classrooms. These considerations are crucial for creating a more engaging and effective mathematics learning environment that aligns with evolving educational standards and meets students' needs. The findings of this study provide actionable insights for educators and policymakers aiming to improve the quality of mathematics education in Korea.

• Communications of Mathematical Education
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• v.37 no.2
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• pp.233-256
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• 2023

This study conducted foundational research to derive ways to use ChatGPT in mathematics education by analyzing ChatGPT's responses to questions from the National Assessment of Educational Achievement (NAEA) and the College Scholastic Ability Test (CSAT). ChatGPT, a generative artificial intelligence model, has gained attention in various fields, and there is a growing demand for its use in education as the number of users rapidly increases. To the best of our knowledge, there are very few reported cases of educational studies utilizing ChatGPT. In this study, we analyzed ChatGPT 3.5 responses to questions from the three-year National Assessment of Educational Achievement and the College Scholastic Ability Test, categorizing them based on the percentage of correct answers, the accuracy of the solution process, and types of errors. The correct answer rates for ChatGPT in the National Assessment of Educational Achievement and the College Scholastic Ability Test questions were 37.1% and 15.97%, respectively. The accuracy of ChatGPT's solution process was calculated as 3.44 for the National Assessment of Educational Achievement and 2.49 for the College Scholastic Ability Test. Errors in solving math problems with ChatGPT were classified into procedural and functional errors. Procedural errors referred to mistakes in connecting expressions to the next step or in calculations, while functional errors were related to how ChatGPT recognized, judged, and outputted text. This analysis suggests that relying solely on the percentage of correct answers should not be the criterion for assessing ChatGPT's mathematical performance, but rather a combination of the accuracy of the solution process and types of errors should be considered.