• Journal of The Korean Association For Science Education
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• v.40 no.2
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• pp.227-236
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• 2020

This study examines the change in students' science attitude and the growth of their core competencies through science classes emphasizing digital literacy. To this end, we conducted a study on 116 first graders in C middle school in the C region, and entered a science class that emphasized digital literacy of 35 classes. First, as a result of examining the effect on science attitude, a statistically significant change (p<.05) was observed. The effect size for each subregion ranged from 0.67 to 1.52. Second, there were no differences in the overall frequency of growth perception according to the type of class that emphasized digital literacy. However, in the analysis of core competencies, Web-based classes did not show a large difference in frequency by core competencies, whereas high-tech classes were slightly different by core competencies. This is an implication for science education, and it is necessary to increase the utilization of science classes that emphasize digital literacy.

• Journal of Science Education
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• v.37 no.1
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• pp.233-243
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• 2013

The purpose of this study is to develop the syringe experiment device which is able to analyze the relationship between the length of the air pillar and resonance frequencies quantitatively for the education of sound resonance. We made an air pillar resonance device with a 'Head', which is used by the disposable syringe and the plastic sphere for constructing molecular models. We also assembled PC experiment equipment which is used by commercial software. As a result, it appears this equipment can be used instead of the current device used by experts. It was proved that this syringe device is not the 'pipe' but the 'Helmholtz resonator'. It appears that data through resonance experiments can prove the sound resonance phenomenon. In conclusion, this syringe resonator is the experiment device that can be used in the gifted education for middle-high school students and acoustic experiments for university students.

• Journal of Elementary Mathematics Education in Korea
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• v.18 no.2
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• pp.341-355
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• 2014

The purpose of this study was to analyze the research trends of elementary mathematics education in Japan. For this purpose, 192 papers published by Japan Society of Mathematics Education for the last 10 years(2004-2013) were analyzed according to there criteria. First, as for research topics, the frequent topics in order were instructional design and methods (36.7%), analysis of curriculum and textbook, general studies, learners' perspectives and abilities, evaluation, teacher education, education engineering and parish. Second, the contents were researched by the order of number and operations (47.4%), geometry, regularity, measurement and probability and statistics. Finally, research subjects of this study were researched by the order of students(39.3%), teachers. Papers dealing with lower graders as well as pre-service teachers were rare. And article dealing with low-achievers and gifted students were not founded. On the basis of this result, we hope it will provide the follow-up and the idea of the elementary mathematics education in Korea and also help various and balanced development.

• Journal of The Korean Association of Information Education
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• v.24 no.3
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• pp.243-254
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• 2020

In order to cultivate AI(artificial intelligence) manpower, major countries are making efforts to apply AI education from elementary school. In order to introduce AI education in elementary school, it is necessary to have a curriculum and educational content for elementary school level. This study developed educational contents to experience the principle of AI learning at the unplugged level for the purpose of AI education for elementary school students. The educational content developed was selected as an AI that evaluates the emotion of sentences. In addition, to solve the problem, data attributes were derived and collected, and the process of AI learning was simulated to solve the problem. As a result of the study, the attitude of elementary school students to AI increased post than before. In addition, the task performance rate was averaged at 85%, showing that the proposed AI education content has educational significance.

• The Journal of Korean Association of Computer Education
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• v.18 no.4
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• pp.1-9
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• 2015

Problem solving is essential skill for all students in the $21^{st}$ century. In particular, as the computing system ensures the effectiveness of problem solving in the various disciplines and real life, interest in learning algorithms to design a problem solving process is increasing. In order to improve problem solving skill, students should not only understand algorithm design skills but also apply appropriate skills to solve faced problem. In terms of these the puzzle can be considered a preferred learning tools to improve problem solving skill. Therefore, in this study we designed puzzled based algorithm learning and analyzed the impact of puzzle based algorithm learning on problem solving skills of leaners. As the results of research, we confirmed that the puzzled based algorithm learning took positive effect on enhancing problem solving skills of the learners.

• Journal of Educational Research in Mathematics
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• v.22 no.1
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• pp.101-115
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• 2012

Analogy, a plausible reasoning on the basis of similarity, is one of the thinking strategy for concept formation, problem solving, and new discovery in many disciplines. Statistics educators argue that analogy can be used as an useful thinking strategy in statistics as well. This study investigated the characteristics of students' analogical thinking in statistics. The mathematically gifted were asked to construct similar problems to a base problem which is a statistical problem having a statistical context. From the analysis of the problems, students' new problems were classified into five types on the basis of the preservation of the statistical context and that of the basic structure of the base problem. From the result, researchers provide some implications. In statistics, the problems, which failed to preserve the statistical context of base problem, have no meaning in statistics. However, the problems which preserved the statistical context can give possibilities for reconceptualization of the statistical concept even though the basic structure of the problem were changed.

• Journal of Creative Information Culture
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• v.5 no.3
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• pp.237-243
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• 2019

The ability of problem-solving, communicating, and collaborating with computing technology is considered as core competencies for future society. In order to improve those competences, the algorithm and programming ability was set as the important goal of the Information curriculum of Korea. Algorithmic thinking is a key component of computing thinking, and it is known to play a very important role in designing and programming algorithms. It is used to set goals of Information curriculum and to measure student achievement. Therefore, in this study, developed a test to measure algorithmic thinking of students in elementary, middle and high schools, and applied the test to measure the levels of algorithmic thinking. As a result of the analysis, the higher the school level, the better the algorithmic thinking. And no difference was found between genders. This study is expected to provide a guide for constructing measures or setting the difficulty level for algorithmic thinking.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.167-173
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• 2021

The purpose of this study is to discuss the types of algorithms and data categories in AI education for elementary school students. The study surveyed 11 pre-elementary teachers after providing education and practice on various data, artificial intelligence algorithm, and AI education platform for 15 weeks. The categories of data and algorithms considering the elementary school level, and educational tools were presented, and their suitability was analyzed. Through the questionnaire, it was concluded that it is most suitable for the teacher to select and preprocess data in advance according to the purpose of the class, and the classification and prediction algorithms are suitable for elementary AI education. In addition, it was confirmed that Entry is most suitable as an AI educational tool, and materials that explain mathematical knowledge are needed to educate the concept of learning of AI. This study is meaningful in that it specifically presents the categories of algorithms and data with in AI education for elementary school students, and analyzes the need for related mathematics education and appropriate AI educational tools.

• The Mathematical Education
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• v.55 no.2
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• pp.147-169
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• 2016

This study analyzes the mathematical creativity test as an illustrative example with scoring domains of fluency, flexibility and originality in order to make suggestions for obtaining maximum reliability based on a composite score depending on combinations of each scoring domain weights. This is done by performing a multivariate generalizability analysis on the test scores, which were allowed to access publicly, of 30 mathematically gifted elementary school students, and therefore error variances, generalizability coefficients, and effective weights have been calculated. The main results were as follows. First, the optimal weights should adjust to .5, .4, and .1 based on the maximum generalizability coefficient even though the original weights in the mathematical creativity test were equal for each scoring domain with fluency, flexibility and originality. Second, the mathematical creativity test using the three scoring domains of fluency, flexibility, and originality showed higher reliability than using one scoring domain such as fluency. These results are limited to the mathematical creativity test used in this study. However, the methodology applied in this study can help determine the optimal weights depending on each scoring domain when the tests constructed in various researchers or educational fields are composed of multiple scoring domains.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06b
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• pp.292-297
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• 2008

본 논문은 FPGA 기반 설계에서 주변보다 급격한 온도 변화를 보이는 hotspot들을 탐지하기 위한 열 감지 센서 수를 정하고, 센서의 놓여야 할 배치 장소를 결정하는 알고리즘을 제안한다. 열 감지 센서로는 동적으로 설계가 가능한 ring oscillator 센서 기술을 사용한다는 가정 하에, 센서의 사용 개수를 최소화함과 동시에 최적의 센서 배치 위치 찾는다. 기존의 연구의 단점은 센서가 감지하는 영역 범위를 적당한 크기의 정사각형으로 간주하였기에, 실제 원형의 관측 범위를 보이는 센서 감지 영역의 현실을 올바로 반영하지 못하였으며, 또한 잘 알려진 회로 분할(partition) 기법에 의존한 휴리스틱으로 최적의 결과를 보장하지는 못하였다. 이와는 달리 본 연구에서는 센서의 관측 범위를 원형으로 할 수도 있게 함과 동시에 최적의 해를 보장하는 센서 할당 및 배치 알고리즘을 제안한다. 구체적으로 본 제안 알고즘에서는 소위 “Candidate Coloring 기법”을 통해 센서가 놓여야 할 모든 후보 영역을 표시하며, “Candidate Filtering 기법”을 통해 불필요한 후보 영역들을 완전히 삭제하여 탐색 공간을 줄이게 되며 (해의 최적 해는 항상 유지 되도록 하면서), 마지막으로 Branch-and-Bound 알고리즘을 적용해 최적의 센서 할당 및 배치 결과를 찾아내었다.