• Communications of Mathematical Education
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• v.35 no.3
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• pp.233-255
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• 2021

The purpose of this study is to develop math anxiety scale for middle school students for planning and implementing math anxiety treatment programs. In this study, we describe the process of developing and validating math anxiety scale for middle school students and detailing exploratory factor analysis and confirmatory factor analysis to verify construct validity. As a result of the study, we developed the Math Anxiety Scale for Middle School Students (MASS-M) of 30 items with four factors: mathematical curriculum content, mathematical attitude, mathematical test, and environment. As a math anxiety factor for middle school students, MASS-M was developed, which includes mathematical anxiety factors such as mathematical test factor and environmental factor, especially mathematical curriculum content factor describing mathematical treatment, and mathematical attitude factor describing psychological treatment. MASS-M, derived from this study, is a standardized scale for measuring math anxiety in middle school students and is expected to serve as the basis for maintaining consistency in research on math anxiety in middle school students and developing programs to treat math anxiety in middle school students.

• Journal of the Korean School Mathematics Society
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• v.13 no.3
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• pp.443-458
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• 2010

This study is about how differ math anxiety according to the features of brain preference. In order to solve questions, BPI test and math anxiety test were done to high school students in the second grade. The test sheets were analyzed by ANOVA and MANOVA using SPSS 14.0. The result was found out that math anxiety was high in the order of left-brain preferences, both-brain preferences, and right-brain preferences. High level of math anxiety among students with right-brain preferences seem to be influenced by the right brain which prefers emotional features. Therefore, students need to stimulate their left brain by writing and reading something a lot when they solve math questions. Also, teachers can lessen math anxiety of students by give them opportunities to solve step-by-step questions, using various visual teaching materials promoting students' reasoning ability which can help them solve questions in a systematic and analytic way.

• Communications of Mathematical Education
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• v.33 no.1
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• pp.21-34
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• 2019

The purpose of this paper is to investigate the differences of the mathematics anxiety and mathematical achievement of high school students according to math socialization, and to find out which mathematics anxiety causes have more influence on mathematical achievement and how much it is. For this purposes, the problem of this study as follows: firstly, are there any relationship among mathematical grades, mathematics anxiety, interest and math socialization? secondly, are there any math socialization mathematics predict to mathematical grades, mathematics anxiety, interest? lastly, are there any differences in the mathematical grades, mathematics anxiety, interest according to math socialization level? The subjects of this study consist of 479 students selected for a class of unit, in high schools located in Seoul and metropolitan area, Korea. In this study, for students math socialization, Jung(2002)'s scale was used. Mathematical anxiety & interest, Huh(1996)'s Mathematics Anxiety Scale was used. The collected data were analyzed by using the 24.0 SPSS program. The data were also tested by using the t-test, pearson correlation and multiple regression. The major results of this study were as follows: firstly, math socialization, mathematics anxiety, interest and mathematical grades have significantly related each other, secondly, the multiple regression analyses demonstrated that sub factors of math socialization were the significant predictors of mathematical grades, mathematics anxiety and interest, lastly, mathematics grades, and mathematical anxiety and interest have significant differences depending on math socialization.

• Research in Mathematical Education
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• v.17 no.3
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• pp.199-220
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• 2013

The main objective of this study is to explore the relationship between psychological factors (i.e. math anxiety, attention, attitude, Working Memory Capacity (WMC), and Field dependency) and students' mathematics problem solving based on Revised Bloom Taxonomy. A sample of 169 K11 school girls were tested on (1) The Witkin's cognitive style (Group Embedded Figure Test). (2) Digit Span Backwards Test. (3) Mathematics Anxiety Rating Scale (MARS). (4) Modified Fennema-Sherman Attitude Scales. (5) Mathematics Attention Test (MAT), and (6) Mathematics questions based on Revised Bloom Taxonomy (RBT). Results obtained indicate that the effect of these items on students mathematical problem solving is different in each cognitive process and level of knowledge dimension.

• Journal for History of Mathematics
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• v.34 no.1
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• pp.21-37
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• 2021

The purpose of the present study is to compare the differences in levels per group of high school students regarding the self-regulated learning factors for mathematics. For this purpose, a self-regulated learning measurement tool was developed and surveys were conducted. And the statistical analysis was completed using the frequency analysis, Kolmogorov-Smirnov normality test, Mann-Whitney U test and the Kruskal-Wallis H test. As a result, it is found that self-efficacy is of statistically significant differences in self-regulated learning levels regardless of the group classifications but test anxiety does not show statistically significant differences in self-regulated learning levels regardless of the group classifications.

• Communications of Mathematical Education
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• v.36 no.2
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• pp.201-227
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• 2022

The purpose of this study was to develop an instrument measuring mathematics anxiety suitable for Korean High school students. In order to achieve this study purpose, the study was conducted according to the procedure of setting components of mathematics anxiety, developing questions, and verifying validity and reliability. First, in order to set the components of mathematic anxiety, previous studies on mathematic anxiety. Through this, six factors of mathematic anxiety were derived. Next, new questions were developed for each of the six constituent factors. The 122 questions were revised and supplemented through two content validity tests, and the final instrument for mathematics anxiety consisted of 49 questions of 6 factors. Finally, to verify the validity and reliability of the measurement instrument for mathematics anxiety, a survey was conducted on 1,848 students from 16 universities in Seoul and the metropolitan area. Next, a validity analysis was conducted with the 1,645 responses, excluding students who answered that there was no mathematics anxiety. As a result of exploratory factor analysis, 15 out of 49 questions were removed. Six factors were named individual characteristics, pressure on achievement, abstraction in mathematics, teaching and learning style, parental attitudes, and cumulative mathematics subjects. As a result of confirmatory factor analysis, the model fit was found to be appropriate, and the convergence validity and discriminant validity were found to be good.

• Journal of the Korean School Mathematics Society
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• v.23 no.4
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• pp.469-489
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• 2020

Middle school students are known to have high levels of math anxiety. According to the need for test tools that reflect the characteristics of today's middle school students, it was intended to develop a mathematical anxiety test for middle school students. Sub-factors of mathematical anxiety were established based on prior research and questions corresponding to each factor were produced. The suitability and validity of the questions were analyzed through two pilot tests. Then some of the questions were revised. This test was conducted on 255 middle school students using the revised questions, and the validity and reliability of the test tools were analyzed on 246 student responses. The final developed test tool consisted of 6 sub-factors and a total of 36 questions, and was intended to provide students, teachers, and parents with information about students' mathematical anxiety by providing criteria for the degree of anxiety.

• Journal of Fisheries and Marine Sciences Education
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• v.29 no.1
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• pp.315-324
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• 2017

The purpose of this study is to help with education by applying the learning clinic program to the maladjusted children to improve the emotional stability and academic achievement. In order to find the components of the learning clinic program, we have classified self efficacy, learning motivation, anxiety, and academic stress as emotional factors and the results of Korean language, mathematics, sociology and science as academic achievement factors to examine the effects of the program. The results obtained in this study are followings. Firstly, there was significant difference in self efficacy and anxiety between boys and girls among emotional factors, and there was significant difference in math between boys and girls among academic achievement factors. Secondly, after applying the learning clinic program, significant difference is found in all factors such as self efficacy, learning motivation, anxiety and academic stress, and there was also a significant difference in Korean language, mathematics, sociology and science among academic achievement factors. In conclusion, the learning clinic program was helpful to maladjusted children by improving emotional stability and academic achievement.

• Communications of Mathematical Education
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• v.29 no.4
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• pp.723-743
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• 2015

In this research, The objective of the present study was to develop a preliminary diagnostic worksheet for use in consultations for learning mathematics. In order to achieve this, the worksheet was constructed with questions designed to assess the students. Through standardization, diagnostic worksheets for primary school students in grades 5 and 6 and secondary school students in grades 7 and 8 were produced. The diagnostic worksheet was divided into three sections, consisting of the psychology of learning mathematics in section 1, the methodology in learning mathematics in section 2, and personal preferences in learning mathematics in section 3. The psychology of learning mathematics was composed of questions on factors such as, "confidence in math learning ability," "math anxiety," and "attitude in learning mathematics." Moreover, factors in methodology in learning mathematics were "self-management in learning mathematics" and "math learning strategies." Those for personal preferences in learning mathematics asked about "motivation" and "preferences" with questions about "math learning habits" and "management methods for learning math." This diagnostic worksheet can be used as basic material in consulting students on learning mathematics.

• The Mathematical Education
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• v.61 no.2
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• pp.257-271
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• 2022

As information and communication technologies are being developed so rapidly, education research is actively conducted to provide optimal learning for each student using big data and artificial intelligence technology. In this study, using the mathematics learning data of elementary school 5th to 6th graders conducting blended mathematics classes, we tried to find out what factors predict mathematics academic achievement and developed an artificial intelligence model that predicts mathematics academic performance using the results. Math learning propensity, LMS data, and evaluation results of 205 elementary school students had analyzed with a random forest model. Confidence, anxiety, interest, self-management, and confidence in math learning strategy were included as mathematics learning disposition. The progress rate, number of learning times, and learning time of the e-learning site were collected as LMS data. For evaluation data, results of diagnostic test and unit test were used. As a result of the analysis it was found that the mathematics learning strategy was the most important factor in predicting low-achieving students among mathematics learning propensities. The LMS training data had a negligible effect on the prediction. This study suggests that an AI model can predict low-achieving students with learning data generated in a blended math class. In addition, it is expected that the results of the analysis will provide specific information for teachers to evaluate and give feedback to students.