Earticle

인문학 수업에서 교수와 학생 간에 상호작용은 매우 중요하다. 그러나 많은 학생들이 수강하는 대규모 집합 교육의 경우, 수많은 학생들과 교수가 의견을 교환하기는 어렵다. 본 논문에서는 안드로이드 폰의 앱(app)을 개발하여, 대규모 집합 교육에서 발생할 수 있는 상호작용의 제한성을 극복하고자한다. 본 논문에서 개발한 앱은 스마트 폰의 정보처리 기능과 무선 통신 기능을 활용하였다. 대규모 집합 교육의 보조 기구로 사용하여 대규모 집합 교육의 교육 효과를 높이는데 목적이 있다.

The interactions between a professor and students are very important in humanities classes. A professor could not exchange opinions with students especially in large-scale classes. We have developed a smart phone app. in order to overcome the limit of interaction between a professor and students in large-scale classes. The app we have developed in this paper have exploited smart phone's data processing and wireless communication ability. In this paper, we showed that smart phone could be an useful tool for increasing the education effect of large-scale classes.

Education is about sharing knowledge and using techniques and skills that can person's ability. the goal is to educate and develop people as a whole. In order to achieve this educational purpose efficiently, our society has many educational courses. The educational facility which can be used in a variety of educational methods should be made flexible. It should provide an environment in which ever student can grow. Being creative, using a variety of methods should help to develop character in people. In order to achieve this, the school's facilities should be future-oriented. It is necessary to research systemically about its changes and feed back according to the social demand, the educational purpose, and the changes of educational courses. This study is intended to present basic material which will be need from now on for the facility of the special classes in jeju city. Elementary schools should consider having a reasonable scale and arrangement pattern. The facility for special classes has to find a way to operate flexibly according to the changes of the class number.

좋은 수업은 수업을 구성하는 요소들이 하나의 체제로서 유기적 연관성을 갖는다. 수업의 목표는 학생들이 해당 과목의 교육내용을 충분히 이해한 뒤 이를 실제로 자신의 전문영역에 적용할 수 있는 능력을 함양하는 것이다. 따라서 이상적인 수업을 위해서는 학생들이 필요한 이론을 습득함과 동시에 이를 실질적으로 적용하도록 설계하는 것이 필요하다. 우리는 수업을 진행하면서 늘 스스로 질문하기를 어떻게 하면 학생들을 위한 대단위 수업을 효과적으 로 할 수 있을까를 연구한다. 이는 여러 전공 분야에 걸쳐 개설된 대단위 수업을 담당하는 많은 교수들의 고민이기도 하다. 우리는 이렇게 대단위 수업을 효과적으로 할 수 있는 방안을 모색할 필요가 있는 시점에서 강의, 발제 및 조 편성, 과제 부과, 조별 발표, 교수의 조별 발표지도, 강의 자료의 게시, 질문과 답변, 조별 발제에 대한 학생들의 피드 백, 기말보고서 작성, 성적산출방식과 같은 다양한 요소들을 어떻게 설계하고 실행하는 것이 가장 효과적인지 연구하 였다.

In a good class, the elements that make up the class are organically related as a system. The goal of the class is to foster the ability of students to fully understand the educational content of the subject and then apply it to their professional areas. Therefore, for ideal classes, it is necessary to design students to acquire the necessary theories and apply them practically. The question We always ask ourselves during lectures is how to effectively give large-scale lectures for students. This is also the concern of all professors in charge of large-scale lectures opened across various major fields. Now is the time to find ways to effectively give lectures on a large scale. We studied how it is most effective to design and implement various factors such as lectures, presentation and group organization, assignment, group presentation, professor's group presentation guidance, lecture materials posting, questions and answers, group presentation feedback, final report writing, and grade calculation.

This paper proposes a statistical-based linguistic methodology for automatic mapping between large-scale heterogeneous languages resources for NLP applications in general. As a particular case, it treats automatic mapping between two large-scale heterogeneous Korean language resources: Sejong Semantic Classes (SJSC) in the Sejong Electronic Dictionary (SJD) and nouns in KorLex. KorLex is a large-scale Korean WordNet, but it lacks syntactic information. SJD contains refined semantic-syntactic information, with semantic labels depending on SJSC, but the list of its entry words is much smaller than that of KorLex. The goal of our study is to build a rich language resource by integrating useful information within SJD into KorLex. In this paper, we use both linguistic and statistical methods for constructing an automatic mapping methodology. The linguistic aspect of the methodology focuses on the following three linguistic clues: monosemy/polysemy of word forms, instances (example words), and semantically related words. The statistical aspect of the methodology uses the three statistical formulae ${\chi}^2$, Mutual Information and Information Gain to obtain candidate synsets. Compared with the performance of manual mapping, the automatic mapping based on our proposed statistical linguistic methods shows good performance rates in terms of correctness, specifically giving recall 0.838, precision 0.718, and F1 0.774.