• 영어어문교육
• /
• 제11권3호
• /
• pp.89-112
• /
• 2005

This study investigated the effects of collocation-based vocabulary instruction for the experimental group (G2). It was compared to the traditional wordlist-based vocabulary instruction for the control group (G1). This results reflect the development of low level high school EFL learners' vocabulary learning strategy use and the positive change in the affective domain. In the analysis of the survey responses, G1 and G2 did not differ significantly on the first questionnaire. They did, however, differ significantly on the second questionnaire. G2 used more strategies to discover and to consolidate the meaning of the words by means of combining words. In terms of the affective domain, G2 participated more actively in the learning activities, which had a significant effect on vocabulary growth, memory, self-confidence, motivation, and cooperative learning. This is attributable to the fact that G2 was more inquisitive, interested, challenged, participatory, cooperative, and attentive than G1 in performing the vocabulary task activities. Moreover, the data collected from the questionnaire showed that G2 performed more interactive and dynamic activities in solving the given tasks.

• 정보과학회 컴퓨팅의 실제 논문지
• /
• 제23권11호
• /
• pp.611-616
• /
• 2017

정보검색에서 질의확장은 가장 널리 알려진 기술로서 사용자가 입력한 질의에 외부적인 지식을 추가해서 조건에 맞게 질의를 확장시켜 검색도구의 능력을 향상시키는데 많이 사용되어 왔다. 하지만, 질의에 사용되는 단어의 애매모호함은 검색도구가 성능을 낮추기 때문에 이러한 문제는 여전히 풀어야 할 과제로 남아있다. 본 논문에서는 단어의 의미를 나타낼 수 있는 도메인을 사용해서 이러한 문제를 해결하는 방법을 제시한다. 특히 토픽 모델을 이용한 도메인 중심 모델을 사용해서 질의를 확장하는 기술을 제안한다. 실험은 기존 모델들과 비교로 이루어졌고, 그 결과 제시된 방법은 높은 성능을 보이는 것으로 나타났다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제11권5호
• /
• pp.2590-2606
• /
• 2017

Generally, research of classical image classification algorithms assume that training data and testing data are derived from the same domain with the same distribution. Unfortunately, in practical applications, this assumption is rarely met. Aiming at the problem, a domain adaption image classification approach based on multi-sparse representation is proposed in this paper. The existences of intermediate domains are hypothesized between the source and target domains. And each intermediate subspace is modeled through online dictionary learning with target data updating. On the one hand, the reconstruction error of the target data is guaranteed, on the other, the transition from the source domain to the target domain is as smooth as possible. An augmented feature representation produced by invariant sparse codes across the source, intermediate and target domain dictionaries is employed for across domain recognition. Experimental results verify the effectiveness of the proposed algorithm.

• 한국초등과학교육학회지:초등과학교육
• /
• 제40권1호
• /
• pp.22-35
• /
• 2021

In order to investigate the trends in science education research using AR (Augmented Reality) and derive implications for elementary science education, we analyzed 71 research articles on AR application in science education published in both Korea and abroad from 2010 to August 2020. In quantitative aspects, the number of published articles has steadily increased. For domestic researches, the number of papers targeting for elementary school students was higher than that of middle & high school students. In the research method aspects, qualitative methods were most frequently used. In particular, papers regarding the development of AR program and verification of its effectiveness were most frequently published. The researches using mixed method in domestic field were smaller in number than that of the research in abroad. There were similar trends in research targeting elementary school students. In the aspects of the contents, more researches were performed on biology and earth science areas than others. In case of researches for elementary school students, the proportion of researches on biology and earth science was even higher. Domestically the proportion of studies on the convergence of science and non-science subjects was higher than that of foreign studies. The number of researches exploring the effectiveness on 'non-scientific attitude domain', 'cognitive domain', and 'program domain' were relatively higher than that on 'inquiry & practice domain' and 'science-related attitude domain'. For types of AR contents, 'observation manipulation type' was mostly studied, followed by 'experimental activity type', and 'learning guide type'. In case of studies on elementary school students, the ratio of 'observation manipulation type' contents was higher than that of others, whereas studies on 'field problem solving type' were relatively less reported than others. In addition, studies on 'simple interaction' were most frequently reported. Particularly, there were relatively few studies on 'linear and nonlinear interactions' in domestic field. As a result of analyzing key words, we found that the key words related to the characteristics and implementation of AR frequently occurred, and the key words related to elementary education and the merits of AR had many direct connections with other key words.

• 영재교육연구
• /
• 제13권4호
• /
• pp.119-140
• /
• 2003

이 연구의 목적은 초·중·고등학교의 교육현장에서 창의성의 영역성이 어떻게 나타나는가를 실증적으로 검증하는 것이다. 연구대상을 전체학생 집단, 고창의성 집단, 저창의성 집단의 3개 집단으로 구분하여 각 집단에서의 영역성을 비교 규명하는 것이다. ‘능력-분화가설’에 기초하여, 4개 영역간의 상관관계, 영역-일반성의 변인과 영역-특수성의 영역간의 상관관계, 그리고 영역-특수성에 대한 영역-일반성의 상대적 예측력을 분석하였다. 연구결과, 연구가설과는 오히려 반대의 결과가 나타났다. 즉, 저창의성 집단에서는 영역-특수성을 지지하였으나, 전체학생과 고창의성 집단에서 영역-일반성과 영역-특수성의 어느 한쪽을 일방적으로 지지하기 어려운 결과가 나타났다. 오히려 영역-일방성과 영역-특수성이 상호 보완 또는 통합되는 영역-상보설이 지지되었다.

• 한국과학교육학회지
• /
• 제21권1호
• /
• pp.30-37
• /
• 2001

통합적인 과학 교육의 필요성이 부각되고 있으며 통합 방안에 관한 여러 연구들이 이루어지고 있다. 그러나 대부분의 통합에 관한 연구는 학문의 구조와 인식론적인 측면에 그 근거를 두고 이루어지고 있다. 보다 효율적인 통합 과학 학습을 위해서는 학생들의 심리적인 측면에 관한 연구가 이루어져야 한다. 이러한 필요성에 의해 본 연구에서는, 초등학교 6학년 96명을 대상으로 교육과정상의 과학 용어 분류를 통하여 초등학생들의 심리적인 과학 영역과 그 특징을 알아보았다. 연구 결과, 다양한 과학 영역을 형성하고 있는 것으로 나타났으며 특히 '전기', '인체', '지구', '에너지', '식물', '동물', '환경', '생물', '날씨', '꽃'의 빈도가 높게 나타났다. 각 영역에 포함된 과학 용어를 분석한 결과는 다음과 같다. 첫째, 일상 생활의 경험에서 형성된 관련성을 강하게 유지하고 있는 경우가 있었다. 둘째, 가장 포괄적인 영역은 '지구' 영역이었다. 이영역에는 다른 영역에 포함되었던 대부분의 용어들이 관련되고 있었다. 따라서 '지구' 영역을 통합의 중심으로 하는 것은 학생들의 심리적인 측면에도 잘 부합되는 것이라고 보여진다.

• 한국IT서비스학회지
• /
• 제8권1호
• /
• pp.203-215
• /
• 2009

This paper illustrates the application of co-occurrence theory to generate lightweight ontologies semi-automatically. The proposed model includes three steps of a (Semi-) Automatic creation of Ontology; (they are conceptually named as) the Syntactic-based Ontology, the Semantic-based Ontology and the Ontology Refinement. Each of these three steps are designed to interactively work together, so as to generate Lightweight Ontologies. The Syntactic-based Ontology step includes generating Association words using co-occurrence in web documents. The Semantic-based Ontology step includes the Alignment large Association words with small Ontology, through the process of semantic relations by contextual terms. Finally, the Ontology Refinement step includes the domain expert to refine the lightweight Ontologies. We also conducted a case study to generate lightweight ontologies in specific domains(news domain). In this paper, we found two directions including (1) employment co-occurrence theory to generate Syntactic-based Ontology automatically and (2) Alignment large Association words with small Ontology to generate lightweight ontologies semi-automatically. So far as the design and the generation of big Ontology is concerned, the proposed research will offer useful implications to the researchers and practitioners so as to improve the research level to the commercial use.

• Genomics & Informatics
• /
• 제17권2호
• /
• pp.20.1-20.5
• /
• 2019

Entity normalization, or entity linking in the general domain, is an information extraction task that aims to annotate/bind multiple words/expressions in raw text with semantic references, such as concepts of an ontology. An ontology consists minimally of a formally organized vocabulary or hierarchy of terms, which captures knowledge of a domain. Presently, machine-learning methods, often coupled with distributional representations, achieve good performance. However, these require large training datasets, which are not always available, especially for tasks in specialized domains. CONTES (CONcept-TErm System) is a supervised method that addresses entity normalization with ontology concepts using small training datasets. CONTES has some limitations, such as it does not scale well with very large ontologies, it tends to overgeneralize predictions, and it lacks valid representations for the out-of-vocabulary words. Here, we propose to assess different methods to reduce the dimensionality in the representation of the ontology. We also propose to calibrate parameters in order to make the predictions more accurate, and to address the problem of out-of-vocabulary words, with a specific method.

• 한국수학교육학회지시리즈B:순수및응용수학
• /
• 제30권3호
• /
• pp.309-336
• /
• 2023

We establish some common fixed point theorems satisfying weak ψ - ϕ contraction on partially ordered non-Archimedean fuzzy metric spaces. By using this results we show the existence of fixed point on the domain of words and apply this approach to deduce the existence of solution for some recurrence equations associated to the analysis of Quicksort algorithms and divide and Conquer algorithms, respectively and also give an example to show the usefulness of our hypothesis. Our results generalize, extend and improve several well-known results of the existing literature in fixed point theory.

• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 1998년도 하계종합학술대회논문집
• /
• pp.577-580
• /
• 1998

In this paper, we psresent the design strategy of the assistive communication system for the mute and speech disorder to be able to communicate with people under the restricted circumstances. First, it should be used conventiently in daily life and a specific domain should be set accoridng to the circumstance. Second, proper words in each domain should be selected according to the physical and mental ability of users. This paper seeks to highlight some of the issues involved in using semantic compaction in adynamic environment. (e.g. noun and verb explorable system). In additon, symbols are used in this system in order to make users recognize clearly the meaning of a words. The sentences are compounded from symbols. The compounded sentences are shown on the display monitor in letter,s and synthesized naturally in voice in order to be understood easily.