• Journal of Digital Convergence
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• v.9 no.6
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• pp.343-354
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• 2011

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 lirnit 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.

• Research in Mathematical Education
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• v.14 no.3
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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).

• Language and Information
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• v.15 no.2
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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.

• Journal of Industrial Technology
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• v.28 no.A
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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.

• Journal of Korea Society of Industrial Information Systems
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• v.11 no.4
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• pp.25-31
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• 2006

With the increasing demand of foreign language education in colleges, an effective testing and study system is also needed especially for large scale classes. In this paper, 1 propose a new online system for running large scale foreign language classes which supports not only testing function but also individually customized studying and diagnosis functions. Using the proposed system enables saving of testing space and helps all students get equally good testing and study environment regardless of class size and lecturers.

• Journal of the Korean Institute of Rural Architecture
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• v.16 no.1
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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.

• Journal of the Korean Home Economics Association
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• v.30 no.2
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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.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.24 no.66
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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.

• International journal of advanced smart convergence
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• v.8 no.4
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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.

• The Journal of the Korea Contents Association
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• v.21 no.7
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• pp.440-447
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• 2021

The purpose of this study is to verify the effectiveness of non-face-to-face lectures conducted at universities in Korea under the influence of COVID-19. So this study analyzed the satisfaction level of the students according to the type of class operation, such as face-to-face classes and remote video classes. To this end, this study compared the differences in class satisfaction by class type and class size for a total of 8,707 courses operated by a university between 2019 and 2020. The study found that the satisfaction level of the remote video class was significantly high. In addition, the combination of remote video classes and face-to-face was more satisfactory than other cases. On the other hand, the satisfaction level of small classes in both face-to-face and remote video classes was higher than that of medium or large classes. This means that even remote video classes are highly satisfactory in small-scale classes. Based on the findings, the study proposes a paradigm for new college classes.