• Journal of The Korean Association For Science Education
• /
• v.15 no.2
• /
• pp.158-163
• /
• 1995

The 40th Annual Southern Arizona Regional Science and Engineering Fair was analyzed in terms of contents of exhibits and research methods. Elementary school students like to choose first, biology; secondly. physics; thirdly, chemistry; fourthly. consumer science; fifthly, S.T.S; sixthly. earth science area topics. Chemistry area topics are 20 %, which are much more than rates appeared in American elementary science textbooks. Elementary school students like topics such as pollutions, energy saving materials and characteristics/selection of products required in every-day life. In the most preferential area, biology, students do experiments or survey about plants growth, microbiology, learning/behavior of animals, health/exercise, which are reconcile with the analysis of American elementary science contents.

• Journal of the Korean Society of Earth Science Education
• /
• v.5 no.2
• /
• pp.158-165
• /
• 2012

With five gifted and nine average elementary school students, this study attempted to make a comparative analysis on the characteristics of their scientific writings for earth science-related topics. The analysis found that all of the gifted students showed higher scores than the average in the writing sections of scientific nature, logical nature and creativity. Compared to the average scores, their creativity scores were far higher. By comparing and analyzing the predicates in the writings two groups wrote, I found that the gifted students used more sentences per topic than the average students. Both groups wrote the most numbers of sentences for Volcano-related topics. In the meantime, the gifted children used the least numbers of sentences for the related topics to atmospheric pollution and the average students did so for the related topics to fossils. By the analysis on the patterns of predicate, it was observed that both groups used material predicates most and verbal predicates least. As far as the second most used predicates are concerned, the gifted children used relational predicates and the average students used mental predicates.

• Journal of The Korean Association For Science Education
• /
• v.35 no.1
• /
• pp.15-25
• /
• 2015

This study examined pre-service secondary physics teachers' epistemological beliefs about scientific knowledge, science learning, and science teaching in two different science content topics, Lamarckism and the impetus theory. Two sets of open-ended questionnaires, for each of the topics respectively, were developed in the same format. The pre-service teachers completed the questionnaires at one month intervals. The beliefs were analyzed in two dimensions, knowledge justification and knowledge change for each belief area. The findings show that the majority of pre-service teachers held sophisticated epistemological beliefs about scientific knowledge regardless of content topics. On the other hand, more pre-service teachers exhibited sophisticated beliefs about science learning in the context impetus theory than Lamarckism. In the area of science teaching, the majority of pre-service teachers demonstrated a sophisticated view in knowledge justification but a naive view in knowledge change. When consistency across science topics and belief areas were examined, few pre-service teachers held consistent epistemological beliefs across all topics and areas. The difference in the levels of sophistication in belief areas showed that the pre-service teachers did not connect their epistemological beliefs about science knowledge to their ideas about science teaching and learning. This disconnection seems to make the consistency across topics and areas complicated. The difference in epistemological beliefs about science learning and teaching between two science topics need further inquiry. Implications for teacher education are offered.

• Journal of Creative Information Culture
• /
• v.6 no.2
• /
• pp.57-64
• /
• 2020

As the information society gradually advances, various opinions overflow and their complexity increases. As the results, it was made more difficult to derive important issues and properly respond to those problems. Accordingly, it is necessary to get a handle on emerging problems in education in addition to existing discourses and issues. This study aimed at examining the issues of education by analyzing the petitions posted under 'parenting and education' category on National Petition board. In order to offer objective and detailed results, we employed the topic modeling based LDA algorithm, which is an effective method to extract topics in multiple documents. Nine topics were derived as the result of the analysis and the relationship among those topics was visualized. The values of this study exist in that the derived topics represent important issues that reflect the public opinions.

• Journal of the Korean Society for Library and Information Science
• /
• v.53 no.3
• /
• pp.273-289
• /
• 2019

The goal of this study is to analyze topics discussed in academic papers on multiculture in Korea to figure out research trends in the field. In order to do topic analysis, LDA (Latent Dirichlet Allocation)-based topic modeling methods are employed. Through the analysis, it is possible to track topic changes in the field and it is found that topics related to 'social integration' and 'multicultural education in schools' are hot topics, and topics related to 'cultural identity and nationalism' are cold topics among top five topics in the field.

• Journal of Engineering Education Research
• /
• v.16 no.2
• /
• pp.37-49
• /
• 2013

In this paper, articles in full body of JEER in Korea and JEE in U.S. were classified into two categories- Research area and Key words-to endeavor a comparative study of the engineering education research(EER) topics and their temporal changes. In the recent 4 year term, 'Accreditation of Engineering Education' and 'Courses & Curriculum' were the most common key words appearing in JEER and 'Researches on EER' and 'Learner's Factor' in JEE. If we put curriculum/teaching materials/teaching as the input elements and learning/assessment as the output elements for education achievement, JEE demonstrates that many of the research topics have shifted from input to output in the recent years, while JEER research is in the transient stage.

• The Journal of the Convergence on Culture Technology
• /
• v.9 no.5
• /
• pp.237-244
• /
• 2023

The aim of this study was to explore the satisfaction and needs of 119 paramedics with regard to continuing education and to develop and implement a continuing education program that can enhance their competence in accordance with the purpose of continuing education. The differences in satisfaction with continuing education according to general characteristics were significantly different depending on age, qualification, and clinical experience, and in terms of continuing education topic needs, 'Advanced Trauma Life Support' was the highest need among all groups, and additional desired continuing education topics were the management of mentally ill patients and various field case-based education, indicating a high preference for practical topics that are helpful in emergency patient care work. Therefore, it is believed that efforts should be made to improve the operation of continuing education from various angles, taking into account the general characteristics of continuing education recipients, and improving the quality of continuing education by reflecting the needs of continuing education recipients and selecting practical topics for continuing education.

• The Mathematical Education
• /
• v.59 no.1
• /
• pp.63-80
• /
• 2020

This study analyzed 3,114 articles published in KCI journals and 1,636 articles published in SSCI journals from 2000 to 2019 in order to compare domestic and international research trends of mathematics education using a topic modeling method. Results indicated that there were 16 similar research topics in domestic and international mathematics education journals: algebra/algebraic thinking, fraction, function/representation, statistics, geometry, problem-solving, model/modeling, proof, achievement effect/difference, affective factor, preservice teacher, teaching practice, textbook/curriculum, task analysis, assessment, and theory. Also, there were 7 distinct research topics in domestic and international mathematics education journals. Topics such as affective/cognitive domain and research trends, mathematics concept, class activity, number/operation, creativity/STEAM, proportional reasoning, and college/technology were identified from the domestic journals, whereas discourse/interaction, professional development, identity/equity, child thinking, semiotics/embodied cognition, intervention effect, and design/technology were the topics identified from the international journals. The topic related to preservice teacher was the most frequently addressed topic in both domestic and international research. The topic related to in-service teachers' professional development was the second most popular topic in international research, whereas it was not identified in domestic research. Domestic research in mathematics education tended to pay attention to the topics concerned with the mathematical competency, but it focused more on problem-solving and creativity/STEAM than other mathematical competencies. Rather, international research highlighted the topic related to equity and social justice.

• Journal of the Korean Society of School Health
• /
• v.10 no.2
• /
• pp.137-156
• /
• 1997

Most education materials on sexuality developed in the past 10 years have not been thoroughly evaluated. This study provides results from a content analysis of 5 education materials for primary, middle and high school student. The results of this study were as follows: The Analysis Framework was developed to measure content in the education materials. It was organized into six domains. They are "Human Development", "Relationship", "Personal Skills", "Sexual Behavior", "Sexual Health", "Society and Culture". Each was associated topics and age appropriate developmental guides. The standard for analysis was the developmental guide suggested by the analysis framework. Each education material was assessed for developemtal guidance and its appropriateness for primary, middle and high school students. The total number of "being" responses to each developmental guidance equaled the score the material earned. These scores then were judged as to how well each education materials was comprehensive. 3 of 5 education materials were addressed as less than half the developmental guidline. Certain education materials were less comprehensive than others. I want to know 'Sexuality' covered the fewest developmental guidliness (34.6%). Interstingly, certain domains received much more coverage across all education materials than others. Most education materials provided instruction concerning "Human Development" (62.6%), "Sexual Health" (61.0%). However, topics such as "Personal Skills" (16.2%), "Relationship" (44.1%), "Sexual Behavior" (46.8%), "Society and Culture" (48.6%) were rarely addressed. Three topic, "negotiation", "sexual fantasy", "sexual dysfunction", were never addressed by most of the materials. Because several of the education material contained gender and sexual orientation biases. Certain topics such as "sexual identity and orientation" and "Gender role" were not adequately addressed by most of the material. Unfortunately, the overall findings of this study revealed that most of the education materials were considered insufficient for students. Because this study focused on whether or not the education materials addressed the developmental guidlines, further research is recommended to evaluate and addressed each developmental guidline.

• Korean Medical Education Review
• /
• v.19 no.3
• /
• pp.158-168
• /
• 2017

There is a more urgent call for educational methods of machine learning in medical education, and therefore, new approaches of teaching and researching machine learning in medicine are needed. This paper presents a case using machine learning through text analysis. Topic modeling of news articles with the keyword 'asbestos' were examined. Two hypotheses were tested using this method, and the process of machine learning of texts is illustrated through this example. Using an automated text analysis method, all the news articles published from January 1, 1990 to November 15, 2016 in South Korea which included 'asbestos' in the title and the body were collected by web scraping. Differences in topics were analyzed by structured topic modelling (STM) and compared by press companies and periods. More articles were found in liberal media outlets. Differences were found in the number and types of topics in the articles according to the partisanship and period. STM showed that the conservative press views asbestos as a personal problem, while the progressive press views asbestos as a social problem. A divergence in the perspective for emphasizing the issues of asbestos between the conservative press and progressive press was also found. Social perspective influences the main topics of news stories. Thus, the patients' uneasiness and pain are not presented by both sources of media. In addition, topics differ between news media sources based on partisanship, and therefore cause divergence in readers' framing. The method of text analysis and its strengths and weaknesses are explained, and an application for the teaching and researching of machine learning in medical education using the methodology of text analysis is considered. An educational method of machine learning in medical education is urgent for future generations.