• The Journal of Information Systems
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• v.17 no.4
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• pp.31-49
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• 2008

As the development of information technology, the biggest change in educational paradigm is apparent in the shift that the emphasis of education is layed on from teachers to learners. E-learning education service through the internet is less restricted in the respect of time and places in comparison with off-line education. Therefore e-Learning is spreaded rapidly and the educational effectiveness of that is needed to be investigated. In this study theoretical research was performed firstly and framework of the study was constructed. After establishment of hypotheses the survey data were collected by the learners of e-Learning and the hypotheses were verified by the SPSS version 12.0. The results are as follows : First, the quality of e-Learning service influences significantly to the technology acceptance of users. Secondly, perceived usability and perceived easiness of technology acceptance model influences significantly to the intention of reuse of users of e-Learning services. Lastly, the playfulness of the Flow theory influences significantly to the intention of reuse of users of e-Learning services. Although there are some limitations in the respect of the numbers of variables, parameters, or samples, this study will contribute for enhancing the effectiveness of education in e-Learning service by providing the acceptance factors of e-learners.

• Journal of The Korean Association of Information Education
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• v.13 no.1
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• pp.77-84
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• 2009

Along with developments of information and communication technologies, internet has spread not only all over the society, but also our everyday life deeply. Also requirements for e-learning using internet in the educational aspect have a great influence on the changes of school educations. The benefits of e-learning are many, including cost-effectiveness, enhanced responsiveness to change, consistency, and timely contents. Therefore, the e-learning has been introduced to the universities. However, the e-learning is operated inefficiently because of introduction to the university with no definite idea about effects of education and economy in the university. Therefore, in this paper we analysed the category of e-learning based the curriculum operation forms in the university, surveyed tests about students preference and the studied what is desirable e-learning operation forms.

• Smart Media Journal
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• v.12 no.10
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• pp.93-101
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• 2023

Climate change has emerged as a global problem, with frequent temperature increases, droughts, and floods, and it is predicted that it will have a great impact on the characteristics and productivity of crops. Cnidium officinale is used not only as traditionally used herbal medicines, but also as various industrial raw materials such as health functional foods, natural medicines, and living materials, but productivity is decreasing due to threats such as continuous crop damage and climate change. Therefore, this paper proposes a model that can predict the physiologically active ingredient index according to the climate change scenario of Cnidium officinale, a representative medicinal crop vulnerable to climate change. In this paper, data was first augmented using the CTGAN algorithm to solve the problem of data imbalance in the collection of environment information, physiological reactions, and physiological active ingredient information. Column Shape and Column Pair Trends were used to measure augmented data quality, and overall quality of 88% was achieved on average. In addition, five models RF, SVR, XGBoost, AdaBoost, and LightBGM were used to predict phenol and flavonoid content by dividing them into ground and underground using augmented data. As a result of model evaluation, the XGBoost model showed the best performance in predicting the physiological active ingredients of the sacrum, and it was confirmed to be about twice as accurate as the SVR model.

• Journal of Korean Home Economics Education Association
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• v.34 no.3
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• pp.67-83
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• 2022

This study was designed to develop a sustainable clothing life education program for middle school students and to analyze the effects of the developed program on the "Change-maker" characteristics of adolescents. This study proceeded following the ADDIE teaching design model. The learning activities in the middle school Technology and Home Economics textbooks were analyzed according to the steps of the Change-maker education program. Based on the analyzed results, the sustainable clothing life education program entitled 'Clothes for us, actions for the earth' which includes ten teaching and learning process plans, 17 individual learning activity sheets, and seven group learning activity sheets was developed. The developed program was implemented on 285 first-year students in K middle School in Ulsan. After the class, the level of Change-maker characteristics of the students increased from 3.87(SD=.54) to 4.59(SD=.64). From the interviews of the students, it was also found that the developed program influenced the values and behaviors of the students. Therefore it was confirmed that the Education for Sustainable Development(ESD) program on clothing life in middle school Home Economics developed based on the Change-maker education program stage was effective in cultivating the Change-maker characteristics of adolescents.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.2
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• pp.391-396
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• 2018

A variety of experiments are being conducted with the advent of Learning Model for flipped-learning. In order to apply flipped-learning as a method of teaching, most of them require a pre-prepared learning video. In this case, there is the burden to create the samples of a 13 weeks, except for the mid term and the final exam in college. These systems also make it difficult to change learning content. In this paper, we suggest using blogs to improve the characteristics that existing flippling systems are less adaptable to environmental changes. A blog can be a good thing for learners who are comfortable with the Internet, In this study, we experiment with flipped-learning, which applies blog to one subject. As a result, we would like to evaluate the meaningful learning effects of this study.

• Journal of Science Education
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• v.36 no.2
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• pp.167-185
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• 2012

This study aimed at finding points of improvement in teaching expertise by analyzing the question patterns that appeared during teaching demonstrations which applied science teaching models prepared by a pre-service biology teacher. The question analysis frame for analyzing question types were categorized largely into the question types of Category 1 (questions in cognitive domain, questions with research function, questions in affective domain), Category 2 (repeated questions, questions for narrowing the range, practice questions), and Category 3 (questions on student activity progress, memory questions, and thinking questions). The results of analyzing question patterns from five different science teaching models revealed a high frequency of questions in the fields of cognition and memory. For the circular learning model, questions from the cognitive field appeared the most often, while, student activity progressive questions in particular were used mostly in the 'preliminary concept introduction stage' of the circular learning model and the 'secondary exploratory stage', in which experiments were conducted, and displayed the characteristics of these stages. The discovery learning model combined the courses of observation, measurement, classification and generalization, but, during teaching demonstrations, memory questions turned up the most, while the portion of inquisitive function questions was low. There were many questions from the inquisitive learning model, and, compared to other learning models, many exploratory function questions turned up during the 'experiment planning stage' and 'experiment stage'. Definitional questions and thought questions for the STS learning model turned up more than other learning models. During the change of concept learning model, the five concepts of students were stimulated and the modification of scientific concepts was very much aided by using many memory questions.

• Journal of the Korean Operations Research and Management Science Society
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• v.37 no.4
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• pp.73-93
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• 2012

In recent years, service delivery systems employing a self-service approach have been rapidly spreading. Since a self-service system provides a lower product price, it attracts more customers. However, some system managers are still hesitant to accept a self-service system, because there is no systematic model to predict its performance. Therefore, this research attempts to provide a systematic and quantitative model to predict the performance of a self-service system, focused specifically on a self-service gas station. Under this model, the traditional queuing theory was adopted to describe the general self-service process, but it is also assumed that some changes occur in both the customer arrival rate and the service performance rate. In particular, the price elasticity was introduced to capture the change in the customer arrival rate, and the existence of learning effect and helpers were assumed to design the changed service performance rate. Under these assumptions, a simulation model for a self-service gas station is established, and three performance measurements, such as average number of customers, average waiting time, and Utilization are observed, depending on the changes in price difference and helper-operating time. In this research, the optimal operation strategy for price differentiation and helper-operating time is proposed in accordance with the level of the customer learning rate. Although this research confines the scope of the study to the self-service gas station model, the results of this research can be applied to any type of self-service system.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1023-1035
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• 2021

The electricity cost of a desalination facility was also predicted and reviewed, which allowed the proposed model to be incorporated into the future design of such facilities. Input data from 2003 to 2014 of the Korea Hydrographic and Oceanographic Agency (KHOA) were used, and the structure of the model was determined using the trial and error method to analyze as well as hyperparameters such as salinity and seawater temperature. The future seawater quality was estimated by optimizing the prediction model based on machine learning. Results indicated that the seawater temperature would be similar to the existing pattern, and salinity showed a gradual decrease in the maximum value from the past measurement data. Therefore, it was reviewed that the electricity cost for seawater desalination decreased by approximately 0.80% and a process configuration was determined to be necessary. This study aimed at establishing a machine-learning-based prediction model to predict future water quality changes, reviewed the impact on the scale of seawater desalination facilities, and suggested alternatives.

• Journal of The Korean Association For Science Education
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• v.17 no.3
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• pp.323-332
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• 1997

In order to use analog more systematically in science class, an instructional model was designed on the basis of analogical reasoning processes (encoding, inference, mapping, application, and response) in the Sternberg's component process theory. The model has five phases (introducing target context, cue retrieval of analog context, mapping similarity and drawing target concept, application, and elaboration), and the instructional effects of using the model upon students' comprehension of science concepts and motivation level of learning were investigated. The treatment and control groups (1 class each) were selected from 8th-grade classes and taught about chemical change and chemical reaction for the period of 10 class hours. The treatment group was taught with the materials based on the model, while the control group was taught in traditional instruction without using analog. Before the instructions, modified versions of the Patterns of Adaptive Learning Survey and the Group Assessment of Logical Thinking were administered, and their scores were used as covariates for students' conceptions and motivational level of learning, respectively. Analogical reasoning ability test was also administered, and its score was used as a blocking variable. After the instructions, students' conceptions were measured by a researcher-made science conception test, and their motivational level of learning was measured by a modified version of the Instructional Materials Motivation Scale. The results indicated that the adjusted mean score of the conception test for the treatment group was significantly higher than that of the control group at .01 level of significance. No significant interaction between the instruction and the analogical reasoning ability was found. Although the motivational level of learning for the treatment group was higher than that for the control group, the difference was found to be statistically insignificant. Educational implications are discussed.

• Journal of Korean Society for Quality Management
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• v.49 no.4
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• pp.581-594
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• 2021

Purpose: The purpose of this study is to compare machine learning models for anomaly detection of mechanical facility equipment and suggest an anomaly detection system for mechanical facility equipment in subway stations. It helps to predict failures and plan the maintenance of facility. Ultimately it aims to improve the quality of facility equipment. Methods: The data collected from Daejeon Metropolitan Rapid Transit Corporation was used in this experiment. The experiment was performed using Python, Scikit-learn, tensorflow 2.0 for preprocessing and machine learning. Also it was conducted in two failure states of the equipment. We compared and analyzed five unsupervised machine learning models focused on model Long Short-Term Memory Variational Autoencoder(LSTM-VAE). Results: In both experiments, change in vibration and current data was observed when there is a defect. When the rotating body failure was happened, the magnitude of vibration has increased but current has decreased. In situation of axis alignment failure, both of vibration and current have increased. In addition, model LSTM-VAE showed superior accuracy than the other four base-line models. Conclusion: According to the results, model LSTM-VAE showed outstanding performance with more than 97% of accuracy in the experiments. Thus, the quality of mechanical facility equipment will be improved if the proposed anomaly detection system is established with this model used.