• 제목/요약/키워드: Large classes

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대규모 강의를 위한 안드로이드 폰 앱 개발 (Android phone app. development for large scale classes)

  • 김일민
    • 디지털융복합연구
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    • 제9권6호
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    • pp.343-354
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    • 2011
  • 인문학 수업에서 교수와 학생간에 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 스마트폰의 정보처리 기능과 무선 통신 기능을 활용하였다. 대규모 집합 교육의 보조 기구로 사용하여 대규모 집합 교육의 교육 효과를 높이는데 목적이 있다.

Impact of Inquiry-Based Teaching on Student Attitude toward Mathematics

  • Kim, Taik-H.;Pan, Wei
    • 한국수학교육학회지시리즈D:수학교육연구
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    • 제14권3호
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    • pp.249-262
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    • 2010
  • Large Midwest university faculty members proposed the Science and Technology Enhancement Program Project (STEP) to improve students' learning in the secondary mathematics classroom using modules of inquiry-based teaching. The purpose of this study was to determine the impact of the STEP Project on students' attitude toward mathematics. Hierarchical linear models (HLM) were used to evaluate the impact of the STEP Project. The sample group for the study was 130 ninth grade students enrolled in Integrated Algebra I in a large urban school district. The school was one of eight secondary schools that participated in the STEP Project. The classes in the treatment group were three of five classes ordered in terms of the highest, middle, and lowest mean GPA. The control group consisted of two other middle GPA classes. The classes had an average of 25 students. Teachers who previously had been involved in the STEP Project taught all treatment and control classes. The inquiry-based teaching activities provided by the project were confined to the treatment classes. The survey measuring students' attitudes toward mathematics were obtained for both groups of students. The inquiry-based teaching affected students' attitudes toward mathematics (p < 0.07, ES = 3.07). Especially, students who had preexisting low attitudes toward mathematics were significantly affected by treatment (p < 0.02, ES = 0.02), while the treatment positively affected African American students overall at p < 0.08 (ES = 0.58).

Automatic Mapping Between Large-Scale Heterogeneous Language Resources for NLP Applications: A Case of Sejong Semantic Classes and KorLexNoun for Korean

  • Park, Heum;Yoon, Ae-Sun
    • 한국언어정보학회지:언어와정보
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    • 제15권2호
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    • pp.23-45
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    • 2011
  • 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.

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모델 축소를 위한 그룹 모델 클러스터링 방법에 대한 연구 (Group Model Clustering Method for Model Downsizing)

  • 박미나;하진영
    • 산업기술연구
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    • 제28권A호
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    • pp.185-189
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    • 2008
  • Practical pattern recognition systems should overcome very large class problem. Sometimes it is almost impossible to build every model for every class due to memory and time constraints. For this case, grouping similar models will be helpful. In this paper, we propose GMC(Group Model Clustering) to build a large class Chinese character recognition system. We built hidden Markov models for 10% of total classes, then classify the rest of classes into already trained group classes. Finally group models are trained using group model clustered data. Recognition is performed using only group models, in order to achieve reduced model size and improved recognition speed.

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외국어 과목 운영을 위한 온라인 평가 및 맞춤 학습 시스템의 개발 (Development of Online Testing and Customized Study System for Running Foreign Language Classes)

  • 김병기
    • 한국산업정보학회논문지
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    • 제11권4호
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    • pp.25-31
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    • 2006
  • 대학 교육에서 외국어 교육 중요성의 증대와 아울러 대단위 강좌에 대한 효율적인 온라인 외국어 평가 및 학습시스템의 도입이 절실히 요구된다. 본 논문에서는 대단위 외국어 강좌에 대하여 온라인 평가가 가능할 뿐만 아니라 개인별 능력에 맞춘 학습기능과 진단기능을 갖춘 평가 및 학습 시스템을 제안한다. 제안한 시스템의 사용은 대단위 강좌에서 시험 평가에 따른 시공간의 효율적 활용을 가능하게 하고 강사와 분반에 관계없이 모든 학생들에게 동일한 수준의 교과 진행을 가능하게 하여 강의의 질 향상에도 기여한다.

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제주시 대규모 초등학교의 특별교실 실태에 관한 연구 (A Study on the Actual Conditions of Special Classes for the Large-scale Elementary schools in jeju)

  • 이은경;박정근
    • 한국농촌건축학회논문집
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    • 제16권1호
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    • pp.43-52
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    • 2014
  • 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.

도시신혼기가계의 경제구조, 주거실태 및 선호에 관한 연구 (A Study on the Family Economic Structures, Housing States, and Housing Preferences of Urban Establishing Families)

  • 이기춘
    • 대한가정학회지
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    • 제30권2호
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    • pp.113-137
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    • 1992
  • The purpose of this study was to figure out the urban establishing families' economic structures(income, expenditure, assets, first-present-future housing cost etc.), the states of first-present housing, the future housing plans, and the housing preferences. For this purpose 274 establishing families in Seoul and its metro-politan area were interviewed through the standardized questionnares. Finally 264 questionnares were analyzed. The major findings were as follows; 1. The important source of their monthly incomes was the labor income. But there was often the transfer income from their parents. And the important items of monthly expenditures were savings and foods. In higher income classes, the traffic cost was important relatively. 2. It was found that the urban establishing families were very dependent on their parents for their first-present housing costs. The dependency was stronger in high education classes compared to the low. This was the case in future housing costs. 3. The states and changes of first-present housing showed the demands for an apartment, homeowership, and privacy. These tendencies were higher in high education classes compared to low education classes, but the demands for future housing were according to the monthly income. The present locations were determined majorly by the distance from office and parents. 4. Their housing preferences were different from the present housing states. Furnished rental housing, open living space, large common spaces, and common using of unusual appliances etc. were more preferred by high education classes compared to low education classes.

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Smalltalk 패러다임을 이용한 객체지향 시뮬레이션기반 전문가시스템 (Object-Oriented Simulation-Based Expert System Using a Smalltalk Paradigm)

  • 김선욱;양문희
    • 산업경영시스템학회지
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    • 제24권66호
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    • pp.1-10
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    • 2001
  • Simulation-Based Expert System(SIMBES) is a very effective tool to solve complex antral hard problems. The SIMBES model includes a simulator, a feature extractor, a machine learning system, a performance evaluator, and a Knowledge-Based Expert System(KBES). Since SIMBES depends on Problem domains, a schedule-based material requirements planning problem, which is NP-hard, was selected to exemplify the SIMBES model. To implement the SIMBES application in Smalltalk paradigm, a system class hierarchy was constructed. The hierarchy consists of five large classes such as Job Generator, Job Scheduler, Job Evaluator, Inference Engine, and Executive System. Several classes inside these classes were identified. Additionally, instance protocols about all classes have been described in terms of messages and pseudo methods. These protocols can be implemented easily by any other object-oriented languages. Furthermore, these results may be used as a skeletal system to develop a new SIMBES efficiently, especially when the application is related to other scheduling problems.

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Learning Deep Representation by Increasing ConvNets Depth for Few Shot Learning

  • Fabian, H.S. Tan;Kang, Dae-Ki
    • International journal of advanced smart convergence
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    • 제8권4호
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    • pp.75-81
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    • 2019
  • Though recent advancement of deep learning methods have provided satisfactory results from large data domain, somehow yield poor performance on few-shot classification tasks. In order to train a model with strong performance, i.e. deep convolutional neural network, it depends heavily on huge dataset and the labeled classes of the dataset can be extremely humongous. The cost of human annotation and scarcity of the data among the classes have drastically limited the capability of current image classification model. On the contrary, humans are excellent in terms of learning or recognizing new unseen classes with merely small set of labeled examples. Few-shot learning aims to train a classification model with limited labeled samples to recognize new classes that have neverseen during training process. In this paper, we increase the backbone depth of the embedding network in orderto learn the variation between the intra-class. By increasing the network depth of the embedding module, we are able to achieve competitive performance due to the minimized intra-class variation.

대학의 원격화상수업과 대면수업의 만족도 비교 연구 (A Comparative Study on the Class Satisfaction between Remote Video Class and Face-to-face Class)

  • 이한샘;서은희
    • 한국콘텐츠학회논문지
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    • 제21권7호
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    • pp.440-447
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    • 2021
  • 본 연구의 목적은 코로나 19의 영향으로 국내 대학에서 시행된 비대면 강의의 효과성을 검증하는 데에 있다. 특히 비대면 수업의 여러 유형 중에서도 원격화상수업은 실시간 양방향 소통이 가능하기 때문에 기존의 대면 수업을 대체할 수 있는 수업 모델이다. 이에 본 연구는 대면 수업과 원격화상수업 등 수업운영 형태에 따른 학생들의 수업만족도를 분석하였다. 이를 위하여 수도권 소재 종합대학의 2019-2020년도에 운영된 총 8707개 강좌를 대상으로 수업유형 및 수업규모별 수업만족도의 차이를 비교하였다. 연구결과 원격화상수업의 만족도가 대면수업보다 유의하게 높은 것으로 밝혀졌다. 또한 원격화상수업과 대면이 병행된 수업이 단일형태의 수업보다 높은 만족도를 보였는데, 이는 각 수업형태가 가지는 한계점을 극복함으로써 학생들의 만족도를 높인 것으로 분석된다. 한편, 수업규모에 따른 수업만족도에서는 대면수업과 원격화상수업 모두 소규모 수업의 만족도가 중형 또는 대형 수업보다 높은 것으로 나타났다. 이는 원격화상수업이더라도 소규모 수업에서 높은 만족도를 보이고 있음을 보여준다. 본 연구 결과를 바탕으로 새로운 대학 수업의 패러다임을 확립해 나갈 필요성을 제안하였다.