• Educational Technology International
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• 제21권2호
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• pp.193-216
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• 2020

This study investigated university students' perspectives on good class and instructional practices through social network analysis. The subjects were 321 students in the third and fourth academic years in a Korean university. The subjects completed four open-ended questions, asking about experience of good class, good instructors' teaching practice, and their feelings and attitudes when participating in good class. As social network analysis, KrKwic (Korea Key Words in Context) was used to compute word frequencies and analyze semantic network structures and Ucinet Netdraw to assess centrality in the social network, consisting of degree centrality, closeness centrality, and between centrality. The results are as follows. First, students showed 5 keywords to depict what good class is, including 'understanding', 'example', 'video', 'interest', and 'communication'. Second, the characteristics of teaching methods by professors who practice good class indicate 'assignments', 'questions', 'understanding', 'example', and 'feedback'. Third, the top 5 keywords of students' attitudes as participating in good class are 'active', 'participation', 'focus', 'listening', and 'asking'. Last, keywords depicting desirable class that students most wanted to take next time are 'assignments', 'rewards', 'understanding', 'difficulty', and 'interest'. The findings from this study include the meanings of the semantic network structures of words in the text making up messages. Also this study can provide empirical evidence for educators and educational practitioners in higher education to create effective learning environments.

• 한국컴퓨터정보학회논문지
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• 제28권7호
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• pp.39-46
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• 2023

본 연구는 인공지능 소양 능력의 측정을 위한 검사 기준의 설계와 개발을 목적으로 한다. 선행연구와 전문가 FGI를 통해 AI 소양의 핵심 영역을 선정하고 세부 기준을 설계하였다. 검사 기준의 영역은 AI의 개념, 실제와 영향 3가지로 구분하고 세부 항목은 AI의 개념 33문항, AI의 실제 13문항, AI의 영향 15문항으로 구성하였다. 검사 기준의 타당성 확보를 위해 2번에 걸친 전문가 타당도 검사를 실시하여 검사 기준을 수정, 보완하였다. 최종 AI소양 검사 기준은 총 30문항으로 개발하였다. 본 연구에서 개발된 AI소양 검사 기준은 AI소양 능력 측정을 위한 자기 체크리스트나 AI역량 검사 문항을 개발하는 중요한 도구가 되기를 기대한다.

• 약학회지
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• 제56권5호
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• pp.333-345
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• 2012

A product labelling is one of key tools in ensuring that a patient uses drugs safely and effectively in self-care without professional support. This study aimed to explore the readability and comprehensibility of the information contained on two package inserts of medicines. Two package inserts were tested with first year college students. Fifty-one potential consumers underlined words they could not understand and answered 10 scenario questions. Any differences among groups with different characteristics were statistically tested. Secondly, the readability of two package inserts was assessed with comparison to the level of the 6th grade Korean textbooks. As results, more than 80% of participants properly replied to straightforward questions concerning indication, dosage, duplication, use in pregnancy and contraindication, and 73% about formulation. Less than half answered correctly in multiple choice questions about pediatric use (41%) and side effects (35%). Little discrepancy was observed in the comprehensibility between participants' characteristics. Drug inserts contained about 20% more professional-level words than 6th grade textbooks. In conclusion, Korean consumers may face challenges to understand drug information due to professional terminology and outdated expressions in the current package inserts. To secure safe and effective use of over-the-counter agents, greater efforts should be made to develop more consumer friendly labels. In the other hand, educational supports are required to prepare consumers in a proper level of knowledge for the safe use of drugs.

• Human Ecology Research
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• 제60권4호
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• pp.625-643
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• 2022

The purpose of this study was to explore the trends and core keywords of the secondary school home economics teacher selection test using content analysis and text network analysis. The sample comprised texts of the secondary school home economics teacher 1st selection test for the 2017-2022 school years. Determination of frequency of occurrence, generation of word clouds, centrality analysis, and topic modeling were performed using NetMiner 4.4. The key results were as follows. First, content analysis revealed that the number of questions and scores for each subject (field) has remained constant since 2020, unlike before 2020. In terms of subjects, most questions focused on 'theory of home economics education', and among the evaluation content elements, the highest percentage of questions asked was for 'home economics teaching·learning methods and practice'. Second, the network of the secondary school home economics teacher selection test covering the 2017-2022 school years has an extremely weak density. For the 2017-2019 school years, 'learning', 'evaluation', 'instruction', and 'method' appeared as important keywords, and 7 topics were extracted. For the 2020-2022 school years, 'evaluation', 'class', 'learning', 'cycle', and 'model' were influential keywords, and five topics were extracted. This study is meaningful in that it attempted a new research method combining content analysis and text network analysis and prepared basic data for the revision of the evaluation area and evaluation content elements of the secondary school home economics teacher selection test.

• 응용통계연구
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• 제32권2호
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• pp.173-185
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• 2019

과학적 연구에서 핵심적인 연구 주제 또는 가설은 대부분 인과적 질문(causal question)을 포함한다. 예를 들어, 전염병 예방을 위한 치료법의 효과 연구, 특정 정책의 시행으로 인한 효용(utility)의 평가에 대한 연구, 특정 사용자를 대상으로 노출된 광고의 종류에 따른 광고의 효과성에 대한 연구는 모두 인과 관계(causal relationship)의 추론이 요구된다. 이러한 인과 관계를 다루는 통계적 인과 추론(statistical causal inference)의 주요 관심사 중 하나는 모집단에 일종의 개입(정책 혹은 처치)을 적용한 후 개입의 효과를 정확하게 추정하는 것이다. 인과 추론은 임상실험과 정책결정에서 주로 이용되었으나, 이른바 빅데이터 시대의 도래로 가용한 관측자료가 폭발적으로 증가하였고 이로 인하여 인과 추론에 대한 잠재적 응용가치와 수요가 지속적으로 증가하고 있다. 하지만 가용한 대부분의 자료는 임의실험 기반의 자료와 달리 개입이 임의로 분배되지 않은 비실험 관측자료이다. 따라서, 본 논문은 비실험 관측자료로부터 개입의 효과를 추정하기 위한 인과 추론의 핵심 개념과 최근의 연구동향을 소개하고자 한다. 이를 위하여 본문에서는 먼저 개입의 효과를 Neyman-Rubin의 잠재 결과(potential outcome) 모형으로 나타내고, 개입의 효과를 추정하는 여러 접근법 중 특히 성향점수(propensity score) 기반 추정법과 회귀모형 기반 추정법을 중점적으로 소개한다. 최근 연구동향으로는 (1) 평균 효과 크기 추정을 넘어선 개인별 효과 크기의 추정, (2) 효과크기 추정에 있어서 자료 규모의 증대로 인한 차원의 저주가 야기하는 난제들과 이에 대한 해결방안들, (3) 복합적 인과관계를 반영하기 위한 Pearl의 구조적 인과 모형(structural causal model) 및 잠재 결과 모형과의 비교의 3가지 주제로 구분하여 소개한다.

• 한국의류산업학회지
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• 제22권5호
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• pp.551-560
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• 2020

Due to the nature of fashion design that responds quickly and sensitively to changes, accurate forecasting for upcoming fashion trends is an important factor in the performance of fashion product planning. This study analyzed the major phenomena of fashion trends by introducing text mining and a big data analysis method. The research questions were as follows. What is the key term of the 2010SS~2019FW fashion trend? What are the terms that are highly relevant to the key trend term by year? Which terms relevant to the key trend term has shown high frequency in news articles during the same period? Data were collected through the 2010SS~2019FW Pre-Trend data from the leading trend information company in Korea and 45,038 articles searched by "fashion+material" from the News Big Data System. Frequency, correlation coefficient, coefficient of variation and mapping were performed using R-3.5.1. Results showed that the fashion trend information were reflected in the consumer market. The term with the highest frequency in 2010SS~2019FW fashion trend information was material. In trend information, the terms most relevant to material were comfort, compact, look, casual, blend, functional, cotton, processing, metal and functional by year. In the news article, functional, comfort, sports, leather, casual, eco-friendly, classic, padding, culture, and high-quality showed the high frequency. Functional was the only fashion material term derived every year for 10 years. This study helps expand the scope and methods of fashion design research as well as improves the information analysis and forecasting capabilities of the fashion industry.

• 한국초등수학교육학회지
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• 제21권2호
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• pp.263-289
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• 2017

교과서에 대한 의존도가 높은 초등학교 수업 장면을 고려할 때 교과서의 구성 체제가 수학 수업에 미치는 영향은 크다고 할 수 있다. 특히 교사의 수업 계획은 교과서의 단원 및 차시를 토대로 이루어지기 때문에 단원 및 차시 구성 체제는 수학수업과 직결되는 중요한 요소이다. 이에 본 연구는 초등학교 수학 교과서의 단원 및 차시 구성 체제에 대한 종적, 횡적 비교 분석을 실시하고 그로부터 추출한 주요 특징에 대해 초등학교 교사들의 선호도를 조사하였다. 연구 결과는 우리나라 교육과정기별 수학 교과서 및 한국, 일본, 미국, 핀란드 수학 교과서의 구성 체제에는 몇 가지 차이가 있음을 보여주며, 그에 기초하여 구성한 설문 조사 결과, 초등학교 교사들이 선호하는 단원 및 차시 구성 체제를 파악할 수 있었다. 이와 같은 연구결과로부터 교과서 개발 시 구성 체제 측면에 있어서의 몇 가지 시사점을 제안하였다.

• 지식경영연구
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• 제18권4호
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• pp.181-211
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• 2017

Despite a growing literature focusing on technological development as a key driving force behind the economic performance of a firm or a nation's industy, we still fall short of a comprehensive understanding of how each of the elements required of technological developent and innovation fits togther and leads to economic progress and industry change. This paper seeks to fill this gap by bringing together some of key insights from the theory and research on the coevolutionary process of technology, organizations, and industry, and on the role of institutions in this process. By combining a diverse array of research streams, we provide a broad suvey of foundational work on the following two questions: (1) how the creation and diffusion of innovation occurs and gives rise to structural reconfigurations of the industry, (2) how organisations and technology coevolve, and (3) what is the role of institutions in this coevolutionary process? Based on this literature survey, we also offer a synthesis that can serve as a ground that allows a more nuanced understanding of the sources, dynamics and impacts of technological development and innovation, and interrelationships among technology, organizations and industry change.

• Molecules and Cells
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• 제44권2호
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• pp.63-67
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• 2021

The bed nucleus of the stria terminalis (BNST)-a key part of the extended amygdala-has been implicated in the regulation of diverse behavioral states, ranging from anxiety and reward processing to feeding behavior. Among the host of distinct types of neurons within the BNST, recent investigations employing cell type- and projection-specific circuit dissection techniques (such as optogenetics, chemogenetics, deep-brain calcium imaging, and the genetic and viral methods for targeting specific types of cells) have highlighted the key roles of glutamatergic and GABAergic neurons and their axonal projections. As anticipated from their primary roles in excitatory and inhibitory neurotransmission, these studies established that the glutamatergic and GABAergic subpopulations of the BNST oppositely regulate diverse behavioral states. At the same time, these studies have also revealed unexpected functional specificity and heterogeneity within each subpopulation. In this Minireview, we introduce the body of studies that investigated the function of glutamatergic and GABAergic BNST neurons and their circuits. We also discuss unresolved questions and future directions for a more complete understanding of the cellular diversity and functional heterogeneity within the BNST.

• Educational Technology International
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• 제16권2호
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• pp.183-200
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• 2015

This study investigated the effect of learning achievements and cognitive load according to different types of presenting learning materials and epistemological beliefs (EB). Learning achievements in this study were composed by retention and transfer of ill-structured problem. A total of 80 college students participated in the study. Prior to the learning, students were guided to fill out a questionnaire regarding epistemological beliefs and a prior knowledge test. The students of each group studied with a different type of reading material: full text (FT), full text including key questions (KeyFT) and full text including a concept map (CmFT). After a session of study was finished, they were asked to complete the posttest: retention and transfer. The results showed that there was a significant difference in transfer achievements. CmFT outperformed higher scores than the other types. There was no significant difference in retention among the groups. It is strongly believed that the types of presenting learning materials may have affected the understanding of ill-structured problem solving skills. Students with sophisticated EB showed higher achievements on retention and transfer than naive-EB and mixed-EB. Even though the data showed decrease of the cognitive load on the type of materials and EB, there were no significant differences on the cognitive load. We should consider a positive effect of types of presenting learning materials and EB enhancing capabilities of solving ill-structured problems in real life.