• Journal of Educational Research in Mathematics
• /
• v.26 no.2
• /
• pp.205-224
• /
• 2016

Nowadays technological instruments are advanced to measure brain waves called EEG. Also, it is important to find some facts that cause students to have mathematic anxiety (MA) and to provide remedy programs to lessen their MA in order to help students cure MA that could contribute to negative self-efficacy toward mathematics and mathematical learning. To find how they change the MA level, a small group of 11 high school students in Suwon city participated for ten weeks at the remedy program based on students' levels of MA diagnosed by MASS instrument (Ko, & Yi, 2011) and proofread by 8 advisors who worked in related research areas. The results showed that the remedy program was effective to lessen students' MA and it should provide a long term period since some negative experiences were accumulated for a long time of his or her past schooling by others such as teachers, peers, and parents. EEG showed that students got better scores on a percent of correct answers and a reaction time and some student' EEG from a group HMA became smaller heights and width in comparison of the other groups.

• Education of Primary School Mathematics
• /
• v.13 no.2
• /
• pp.85-97
• /
• 2010

The purpose of this study is to develop a teaching program in consideration of the geometrical thinking levels of students to make a contribution to teaching figures effectively. To do this, we checked the geometrical thinking levels of fourth-graders, developed a teaching program based on van Hiele's theory, and investigated its effect on their geometrical thinking levels. The teaching program based on van Hiele's theory put emphasis on group member interaction and specific activities through offering various geometrical experiences. It contributed to actualizing activity-centered, student-oriented, inquiry-oriented and inductive instruction instead of sticking to expository, teacher-led and deductive instruction. And it consequently served to improving their geometrical thinking levels, even though some students didn't show any improvement and one student was rather degraded in that regard - but in the former case they made partial progress though there was little marked improvement, and in the latter case she needs to be considered in relation to her affective aspects above all. The findings of the study suggest that individual variances in thinking level should be recognized by teachers. Students who are at a lower level should be given easier tasks, and more challenging tasks should be assigned to those who are at an intermediate level in order for them to have a positive self-concept about mathematics learning and ultimately to foster their thinking levels.

• Journal of the Korean School Mathematics Society
• /
• v.22 no.3
• /
• pp.329-350
• /
• 2019

Productive struggle is a student's persevering effort to understand mathematical concepts and solve challenging problems that are not easily solved, but the problem can lead to curiosity. Productive struggle is a key component of students' learning mathematics with a conceptual understanding, and supporting it in learning mathematics is one of the most effective mathematics teaching practices. In comparison to research on students' productive struggles, there is little research on preservice mathematics teachers' productive struggles. Thus, this study focused on the productive struggles that preservice mathematics teachers face in solving a non-routine mathematics problem. Polya's four-step problem-solving process was used to analyze the collected data. Examples of preservice teachers' productive struggles were analyzed in terms of each stage of the problem-solving process. The analysis showed that limited prior knowledge of the preservice teachers caused productive struggle in the stages of understanding, planning, and carrying out, and it had a significant influence on the problem-solving process overall. Moreover, preservice teachers' experiences of the pleasure of learning by going through productive struggle in solving problems encouraged them to support the use of productive struggle for effective mathematics learning for students, in the future. Therefore, the study's results are expected to help preservice teachers develop their professional expertise by taking the opportunity to engage in learning mathematics through productive struggle.

• Asia pacific journal of information systems
• /
• v.24 no.2
• /
• pp.233-253
• /
• 2014

Can the stock market really be predicted? Stock market prediction has attracted much attention from many fields including business, economics, statistics, and mathematics. Early research on stock market prediction was based on random walk theory (RWT) and the efficient market hypothesis (EMH). According to the EMH, stock market are largely driven by new information rather than present and past prices. Since it is unpredictable, stock market will follow a random walk. Even though these theories, Schumaker [2010] asserted that people keep trying to predict the stock market by using artificial intelligence, statistical estimates, and mathematical models. Mathematical approaches include Percolation Methods, Log-Periodic Oscillations and Wavelet Transforms to model future prices. Examples of artificial intelligence approaches that deals with optimization and machine learning are Genetic Algorithms, Support Vector Machines (SVM) and Neural Networks. Statistical approaches typically predicts the future by using past stock market data. Recently, financial engineers have started to predict the stock prices movement pattern by using the SNS data. SNS is the place where peoples opinions and ideas are freely flow and affect others' beliefs on certain things. Through word-of-mouth in SNS, people share product usage experiences, subjective feelings, and commonly accompanying sentiment or mood with others. An increasing number of empirical analyses of sentiment and mood are based on textual collections of public user generated data on the web. The Opinion mining is one domain of the data mining fields extracting public opinions exposed in SNS by utilizing data mining. There have been many studies on the issues of opinion mining from Web sources such as product reviews, forum posts and blogs. In relation to this literatures, we are trying to understand the effects of SNS exposures of firms on stock prices in Korea. Similarly to Bollen et al. [2011], we empirically analyze the impact of SNS exposures on stock return rates. We use Social Metrics by Daum Soft, an SNS big data analysis company in Korea. Social Metrics provides trends and public opinions in Twitter and blogs by using natural language process and analysis tools. It collects the sentences circulated in the Twitter in real time, and breaks down these sentences into the word units and then extracts keywords. In this study, we classify firms' exposures in SNS into two groups: positive and negative. To test the correlation and causation relationship between SNS exposures and stock price returns, we first collect 252 firms' stock prices and KRX100 index in the Korea Stock Exchange (KRX) from May 25, 2012 to September 1, 2012. We also gather the public attitudes (positive, negative) about these firms from Social Metrics over the same period of time. We conduct regression analysis between stock prices and the number of SNS exposures. Having checked the correlation between the two variables, we perform Granger causality test to see the causation direction between the two variables. The research result is that the number of total SNS exposures is positively related with stock market returns. The number of positive mentions of has also positive relationship with stock market returns. Contrarily, the number of negative mentions has negative relationship with stock market returns, but this relationship is statistically not significant. This means that the impact of positive mentions is statistically bigger than the impact of negative mentions. We also investigate whether the impacts are moderated by industry type and firm's size. We find that the SNS exposures impacts are bigger for IT firms than for non-IT firms, and bigger for small sized firms than for large sized firms. The results of Granger causality test shows change of stock price return is caused by SNS exposures, while the causation of the other way round is not significant. Therefore the correlation relationship between SNS exposures and stock prices has uni-direction causality. The more a firm is exposed in SNS, the more is the stock price likely to increase, while stock price changes may not cause more SNS mentions.

• Communications of Mathematical Education
• /
• v.27 no.1
• /
• pp.63-80
• /
• 2013

Reflecting the recent trends and needs of gifted education, this study set out to compare and analyze mathematically gifted elementary students and common students in self-efficacy and career attitude maturity, understand the characteristics of the former, and provide assistance for career education for both the groups. The subjects include 237 mathematically gifted elementary students and 221 common students in D Metropolitan City. The research findings were as follows: First, mathematically gifted elementary students turned out to have higher self-efficacy than common students at the significance level of .01 in the three self-efficacy subfactors, namely confidence, self-regulated efficacy, and task difficulty preference. The findings indicate that mathematically gifted elementary students have much confidence in themselves and strong faith in themselves, thus forming a habit of preferring a relatively high-level task by taking self-management and task difficulty into proper consideration. Second, mathematically gifted elementary students showed higher overall career attitude maturity than common students. There was significant difference at the significance level of .01 in decisiveness and preparedness between the two groups and significant difference at the significance level of .05 in assertiveness. However, there was no statistically significant difference in purposefulness and independence between the two groups. Finally, there were positive correlations at the significance level of .01 between all the subfactors of self-efficacy and those of career attitude maturity in all the subjects except for self-regulated efficacy and purposefulness, between which there were positive correlations at the significance level of .05. The mathematically gifted elementary students showed positive correlations between more subfactors of self-efficacy and career attitude maturity than common students. Given those findings, it is necessary to take differences in self-efficacy and career attitude maturity between mathematically gifted elementary students and common students into account when organizing and running a curriculum. The findings confirm the importance of providing students with various experiences fit for them and point to a need for helping mathematically gifted elementary students maintain a high level of self-efficacy and guiding them through career education with more appropriate career attitude maturity improvement programs.

• Journal of Korean Elementary Science Education
• /
• v.41 no.4
• /
• pp.740-753
• /
• 2022

This study was conducted to develop and apply an out-of-school STEAM program model based on Social-Emotional Learning (SEL) for underprivileged students in the lower grades. To this end, a STEAM program based on SEL was developed, with the following characteristics. First, by integrating traditional STEAM learning elements and SEL elements, a structured program was designed with consistent stages, including mindfulness meditation→present an authentic situation→creative design→emotional experiences→reflection. Second, the program was structured so that elementary school students could develop mathematical thinking and scientific inquiry skills in problem-solving situations in daily life. Third, the detailed themes for each STEAM program involved storytelling-based problem situations, as well as activities centered on play and sympathy to reflect the educational needs of underprivileged students. From these characteristics, a total of five programs were developed and applied to 16 teachers and 354 lower-grade elementary school students in 16 community children centers nationwide. The results were as follows. First, while students' satisfaction with the STEAM program was 4.16, there were no significant differences in STEAM satisfaction according to gender. Second, while all students' interest and self-efficacy, which was one of sub factors of STEAM attitude, were significantly improved, no significant difference was seen in STEAM attitudes according to gender. Third, although students' SEL competencies were not significantly improved, relationship skills, which were among the sub factors of SEL competencies, were significantly improved, and there were no significant differences in SEL competencies according to gender. From these results, a discussion on the effect of the out-of-school STEAM program for underprivileged students and directions for follow-up studies was suggested.