• Korean Journal of Radiology
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• v.22 no.10
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• pp.1697-1707
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• 2021

The recent introduction of various high-dimensional modeling methods, such as radiomics and deep learning, has created a much greater diversity in modeling approaches for survival prediction (or, more generally, time-to-event prediction). The newness of the recent modeling approaches and unfamiliarity with the model outputs may confuse some researchers and practitioners about the evaluation of the performance of such models. Methodological literacy to critically appraise the performance evaluation of the models and, ideally, the ability to conduct such an evaluation would be needed for those who want to develop models or apply them in practice. This article intends to provide intuitive, conceptual, and practical explanations of the statistical methods for evaluating the performance of survival prediction models with minimal usage of mathematical descriptions. It covers from conventional to deep learning methods, and emphasis has been placed on recent modeling approaches. This review article includes straightforward explanations of C indices (Harrell's C index, etc.), time-dependent receiver operating characteristic curve analysis, calibration plot, other methods for evaluating the calibration performance, and Brier score.

• The Mathematical Education
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• v.62 no.2
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• pp.289-302
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• 2023

In today's digital information society, student knowledge and skills to analyze big data and make informed decisions have become an important goal of school mathematics. Integrating big data statistical projects with digital technologies in high school <Artificial Intelligence> mathematics courses has the potential to provide students with a learning experience of high impact that can develop these essential skills. This paper proposes a set of guidelines for designing effective big data statistical project-based tasks and evaluates the tasks in the artificial intelligence mathematics textbook against these criteria. The proposed guidelines recommend that projects should: (1) align knowledge and skills with the national school mathematics curriculum; (2) use preprocessed massive datasets; (3) employ data scientists' problem-solving methods; (4) encourage decision-making; (5) leverage technological tools; and (6) promote collaborative learning. The findings indicate that few textbooks fully align with these guidelines, with most failing to incorporate elements corresponding to Guideline 2 in their project tasks. In addition, most tasks in the textbooks overlook or omit data preprocessing, either by using smaller datasets or by using big data without any form of preprocessing. This can potentially result in misconceptions among students regarding the nature of big data. Furthermore, this paper discusses the relevant mathematical knowledge and skills necessary for artificial intelligence, as well as the potential benefits and pedagogical considerations associated with integrating technology into big data tasks. This research sheds light on teaching mathematical concepts with machine learning algorithms and the effective use of technology tools in big data education.

• Education of Primary School Mathematics
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• v.20 no.3
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• pp.225-235
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• 2017

The study in this paper considers how elementary school students' interest in mathematics and STEAM literacy could be promoted by conjoining the learning of mathematics with the learning of drone topics. Survey instrument was developed to measure student attitudes toward mathematics and science subjects and to evaluate student beliefs on learning mathematics embedded in science topics. Data were collected from elementary school students by administering pre- and post-tests: students were intervened with examples of math problems embedded in certain science contexts. The findings indicate that elementary school students' experience of solving mathematics problems embedded in science contexts positively affects the promotion of their attitudes toward, beliefs on science subjects and science and engineering career path selection. We hope that the mathematics program using the drone will be used in the classroom for STEAM.

• Korean Journal of Health Education and Promotion
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• v.32 no.3
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• pp.85-96
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• 2015

Objectives: This study aims to identify the influencing factors of using postnatal care among illiteracy women who live in the Democratic Republic of Congo. Methods: Household survey was done from February 1 to 8, 2013 in the Kwango district of Democratic Republic of Congo, and 400 childbearing women who has under 5 years old children and pregnant women was randomly selected and answered through the interview with a questionnaire. For analysis the data, ${\chi}^2$ test and logistic regression analysis were used. Results: Woman who can read, write and mathematical calculation was 195 (47.4%) of total 411 answers and 161 (39.2%) used postnatal care for their latest pregnancy. Age at first marriage (${\chi}^2=18.481$, p<.001), religions (${\chi}^2=11.165$, p=.011), languages (${\chi}^2=35.586$, p<.001), the experience of children death (${\chi}^2=16.507$, p<.001), antenatal care over 4 times (${\chi}^2=15.315$, p<.001), postnatal care (${\chi}^2=15.558$, p<.001) is significantly different from literacy level. Among illiterate women group, who are protestant (OR=.330), using Lingala (OR=.128), took elementary education (OR=.223) and farmer (OR=.040), used less postnatal care. Conclusions: For increasing usage of postnatal care among illiterate women, new approach method should be considered such as a visual communication method and a community health workers' training program for giving an outreach service to pregnant women care.

• Education of Primary School Mathematics
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• v.22 no.3
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• pp.167-180
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• 2019

This study analyzed the effects of the educational contextual variables on fourth grade students' mathematics achievement in five East Asian countries(Singapore, Hong Kong Taiwan, Japan and Korea) using TIMSS 2015 data. There are four findings of this study. The first is that the common student-home-level variables that give significant influence on the mathematics achievement in all 5 countries are 'Home resources for learning' and 'Parents' educational expectations'. But 'Literacy and numeracy activities before entering a school' and 'Parents' attitude for mathematics and science' are not common variables. The second is that 'Students' interest in math learning' gave significant influence on the mathematics achievement of in all 5 countries. The third is that 'Teaching limited by student needs' does not give significant influence on the math achievement in Korea, Taiwan, and Japan but in Singapore and Hong Kong. The fourth is that 'Student economic background' gave more significant influence in Korea, Taiwan, and Japan than Singapore and Hong Kong. Suggestions to improve elementary school mathematics teaching and learning are discussed in the conclusion.

• Communications of Mathematical Education
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• v.36 no.4
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• pp.535-558
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• 2022

In the current society, where statistical literacy is recognized as an important ability, statistical education utilizing the statistical problem solving, a series of processes for performing statistics, is required. The result interpretation stage is especially important because many forms of statistics we encounter in our daily lives are the information from the analysis results. In this study, data on private education were provided to pre-service mathematics teachers, and a project was carried out in which they could experience a statistical problem solving process using the population mean estimation. Therefore, this study analyzed the characteristics shown by pre-service mathematics teachers during the result interpretation stage. First, many pre-service mathematics teachers interpreted results based on the data, but the inference was found to be a level of 2 which is not reasonable. Second, pre-service mathematics teachers in this study made various kinds of decisions related to public education, such as improving classes and after-school classes. In addition, the pre-service mathematics teachers in this study seem to have made decisions based on statistical analysis results, but they made general decisions that teachers could make, rather than specifically. Third, the pre-service mathematics teachers of this study were reflective about the question formulation stage, organizing & reducing data stage, and the result interpretation stage, but no one was reflective about the result interpretation stage.

• Journal of Educational Research in Mathematics
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• v.27 no.2
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• pp.157-170
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• 2017

Mathematics was the main domain of PISA 2012, and both paper-based and computer-based assessment of mathematics (CBAM) were conducted. PISA 2012 was the first large-scale computer-based mathematics assessment in Korea, and it is meaningful in that it evaluated students' mathematical literacy in problem situations using dynamic geometry, graph, and spreadsheet. Although Korea ranked third in CBAM, the use of ICT in mathematics lessons appeared to be low. On the other hand, this study focused on Singapore, which ranked first in CBAM. The Singapore Ministry of Education developed online programs such as AlgeTools and AlgeDisc, and implemented the programs in classes by specifying them in mathematics curriculum and textbooks. Thus, this study investigated influential factors on computer-based assessment of mathematics by comparing the results of Korea and Singapore, and aimed to provide meaningful evidence on the direction of Korea's ICT-based mathematics education. The results showed that ICT use at home for school related tasks, attitudes towards computers as a tool for school learning, and openness and perseverance of problem solving were positively associated with computer-based mathematics performance, whereas the use of ICT in mathematics class by teacher demonstration was negatively related. Efforts are needed to improve computer use and enhance teaching techniques related to ICT use in Korean math classes. Future research is recommended to examine how effectively teachers use ICT in mathematics class in Singapore.

• Journal of Music and Human Behavior
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• v.3 no.1
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• pp.63-76
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• 2006

Melody is defined as adding spatial dimension to the rhythm which is temporal concept. Being able to understand melodic pattern and to reproduce the pattern also requires cognitive skills. Since 1980, there has been much research on the relationship between academic skills and music cognitive skills, and how to transfer the skills learned in music work to the academic learning. The study purported to examine various research outcomes dealing with the correlational and causal relationships between musical and academic skills. The two dominating theories explaining the connection between two skills ares are "neural theory" and "near transfer theory." The theories focus mainly on the transference of spatial and temporal reasoning which are reinforced in the musical learning. The study reviewed the existing meta-analysis studies, which provided evidence for positive correlation between academic and musical skills, and significance of musical learning in academic skills. The study further examined specific skills area that musical learning is correlated, such as mathematics and reading. The research stated that among many mathematical concepts, proportional topics have the strongest correlation with musical skills. Also with reading, temporal processing also has strong relationship with auditory skills and motor skills, and further affect language and literacy ability. The study suggest that skills learned in the musical work can be transferred to other areas of learning and structured music activities may be every efficient for children for facilitating academic concepts.

• Journal of The Korean Association For Science Education
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• v.34 no.2
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• pp.63-78
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• 2014

Integrative STEM education is an engineering design-based learning approach that purposefully integrates the content and process of STEM disciplines and can extend its concept to integration with other school subjects. This study was part of fundamental research to develop an integrative STEM education program based on the science inquiry process. The specific objectives of this study were to review relevant literature related to STEM education, analyze the key elements and value of STEM education, develop an integrative STEM education model based on the science inquiry process, and suggest an exemplary program. This study conducted a systematic literature review to confirm key elements for integrative STEM education and finally constructed the integrative STEM education model through analyzing key inquiry processes extracted from prior studies. This model turned out to be valid because the average CVR value obtained from expert group was 0.78. The integrative STEM education model based on the science inquiry process consisted of two perspectives of the content and inquiry process. The content can contain science, technology, engineering, and liberal arts/artistic topics that students can learn in a real world context/problem. Also, the inquiry process is a problem-solving process that contains design and construction and is based on the science inquiry. It could integrate the technological/engineering problem solving process and/or mathematical problem solving process. Students can improve their interest in STEM subjects by analyzing real world problems, designing possible solutions, and implementing the best design as well as acquire knowledge, inquiry methods, and skills systematically. In addition, the developed programs could be utilized in schools to enhance students' understanding of STEM disciplines and interest in mathematics and science. The programs could be used as a basis for fostering convergence literacy and cultivating integrated and design-based problem-solving ability.

• Education of Primary School Mathematics
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• v.16 no.2
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• pp.123-145
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• 2013

This study was expected to yield the meaningful conclusions from the experimental group who took lessons based on inductive activities using GeoGebra at the beginning of proof learning and the comparison one who took traditional expository lessons based on deductive activities. The purpose of this study is to give some helpful suggestions for teaching proof to mathematically gifted elementary students. To attain the purpose, two research questions are established as follows. 1. Is there a significant difference in proof abilities between the experimental group who took inductive lessons using GeoGebra and comparison one who took traditional expository lessons? 2. Is there a significant difference in proof attitudes between the experimental group who took inductive lessons using GeoGebra and comparison one who took traditional expository lessons? To solve the above two research questions, they were divided into two groups, an experimental group of 10 students and a comparison group of 10 students, considering the results of gift and aptitude test, and the computer literacy among 20 elementary students that took lessons at some education institute for the gifted students located in K province after being selected in the mathematics. Special lesson based on the researcher's own lesson plan was treated to the experimental group while explanation-centered class based on the usual 8th grader's textbook was put into the comparison one. Four kinds of tests were used such as previous proof ability test, previous proof attitude test, subsequent proof ability test, and subsequent proof attitude test. One questionnaire survey was used only for experimental group. In the case of attitude toward proof test, the score of questions was calculated by 5-point Likert scale, and in the case of proof ability test was calculated by proper rating standard. The analysis of materials were performed with t-test using the SPSS V.18 statistical program. The following results have been drawn. First, experimental group who took proof lessons of inductive activities using GeoGebra as precedent activity before proving had better achievement in proof ability than the comparison group who took traditional proof lessons. Second, experimental group who took proof lessons of inductive activities using GeoGebra as precedent activity before proving had better achievement in the belief and attitude toward proof than the comparison group who took traditional proof lessons. Third, the survey about 'the effect of inductive activities using GeoGebra on the proof' shows that 100% of the students said that the activities were helpful for proof learning and that 60% of the reasons were 'because GeoGebra can help verify processes visually'. That means it gives positive effects on proof learning that students research constant character and make proposition by themselves justifying assumption and conclusion by changing figures through the function of estimation and drag in investigative software GeoGebra. In conclusion, this study may provide helpful suggestions in improving geometry education, through leading students to learn positive and active proof, connecting the learning processes such as induction based on activity using GeoGebra, simple deduction from induction(i.e. creating a proposition to distinguish between assumptions and conclusions), and formal deduction(i.e. proving).