• Journal of Fisheries and Marine Sciences Education
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• v.23 no.1
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• pp.13-22
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• 2011

The purpose of this study was to development and validation of the 'course evaluation' scale for learner-centered in university. The research collected preliminary data from 1,567 university students's responses for item and scale quality analyses, and collected 2,539 university students's for item and scale quality analyses, and 300 university professors's responses for validation. Data were analyzed to obtain item quality, reliability, and validity analysis. The results of the study were as follows; The 'course evaluation' scale for learner-centered in university was defined by 5 factors. The 5 factors were structure and sincerity of lecture, suitability of report and test, level of consulting for student, application of educational media, communication. The results of the confirmatory factor analysis confirmed five sub-scales in the 'course evaluation' scale for learner-centered in university scale. Criterion-related validity evidence was obtained from the correlation analysis as the criterion measures. Cross validity evidence was obtained from the confirmatory factor analysis in university professors.

• International Journal of Advanced Culture Technology
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• v.6 no.4
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• pp.309-316
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• 2018

The main purpose of this study is to understand how cognitive factors influence the way people interact with information/information systems, by conducting comprehensive and in-depth literature reviews and a theoretical synthesis of related research. Adaptive systems have been built around an individual user's characteristics, such as interests, preferences, knowledge and goals. Individual differences in the ability to use new information and communication technology have been an important issue in all fields. Performance differences in utilizing new information and communication technology are sufficiently predictable that we can begin to coordinate them. Therefore, it is necessary to understand cognitive mechanisms to explain differences between individuals as well as the levels of performance. The theoretical synthesis from this study can be applied to design intelligent (i.e., human friendly) systems in our everyday lives. Further research should explore optimization design for user, by integrating user's individual traits (such as emotion and intent) and system modules to improve the interactions of human-system in data-driven environments.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.3
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• pp.102-107
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• 2020

Recently, the number of people visiting the hospital is increasing due to diabetes. According to the Korean Diabetes Association, statistically, 1 in 7 adults over the age of 30 are suffering from diabetes. As such, diabetes is one of the most common diseases among modern people. In this paper, in addition to blood sugar, which is widely used for diabetes awareness, BMI, which is known to be related to diabetes, triglycerides and cholesterol that cause various complications in diabetics it was studied using random forest techniques and decision trees known to be effective for classification. The importance of each element was confirmed using the results and characteristic importance derived using two techniques. Through this, we studied the diabetes-related relationship between BMI, triglyceride, and cholesterol as well as blood sugar, a factor that diabetic patients should pay much attention to.

• Korean Journal of Human Ecology
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• v.13 no.3
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• pp.361-369
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• 2004

The purpose of this research was to delineate the effect of parenting stress of the children's self-esteem. Such variables as the mother's age, her education level and maternal parenting stress were chosen for the analysis. The sample subjects were 659 pairs of fifth/sixth grade of elementary school and first/second grade of middle school and their mothers. The major findings of the research were as follows : First, the children's self-esteem was significantly different to mother's education level but the children's self-esteem not significantly different to mother's age. Second, parenting stress related to temperament, relationship and learning expectation was significantly different to children's self-esteem. Third, the result of stepwise multiple regression analysis on the effects of the maternal variables(mother's age, her education level, parenting stress) to the children's self-esteem indicated that maternal parenting stress related to temperament, relationship and mother education level were the significant contributing factors.

• Knowledge Management Research
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• v.6 no.1
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• pp.33-69
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• 2005

Recently, knowledge management and E-business are very important issues in academic and business fields. Research questions related with these issues are which factors stimulate knowledge management. Another question is whether knowledge management is related to E-business. To answer these questions a research model was proposed. The data were collected from 90 manufacturing firms in Korea. Appropriate research methodologies were employed for analysis. Results found that the degree of firm's internalization, diversity of domestic management activities and learning orientation affect knowledge aquisition and transfer. Knowledge aquisition and transfer facilitate knowledge application, resulting in new product development, cost reduction and technology differentiation. Knowledge management is a kind of process. This result, therefore, confirms what previous literature predicted.

• Knowledge Management Research
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• v.8 no.1
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• pp.15-28
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• 2007

In the age where the Internet changes everything, even the earth has become flat. The boarders between nations, locations, times, and industries are not meaningful, and no single company can do the whole process well. Therefore, various types of 'Value network' and 'Relation web' emerge for moving first and learning fast. Both the relationship maturity model (RMM) proposed and the partnership management initiatives at SKT demonstrate that the concept is important, and that the final goal can be reached only through a series of critical outcome at each phase. In particular, recognizing as core infrastructures various online/offline channels, deep trust, and rich communications is an important finding for a successful relationship management. Also, related literatures suggest the following key factors to be influential in more than two phases: professionalism including expertise, similarity, channel infrastructure, trustful/trustworthy, and absorptive capacity. Based on these findings, future efforts need to be put on the research & development of related measurement and management tools. It is hoped that more dance with their partners through these efforts.

• Korean Journal of Child Studies
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• v.10 no.2
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• pp.19-31
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• 1989

The purpose of this research was to examine the concurrent validity of the Nalongyee children's achievement motivation test by studying its relationship to a children's school readiness test. The subjects were 335 preschool children (171 urban and 164 rural) selected from 8 public and 7 private kindergartens located in two metropolitan areas (Seoul and Pusan) and 5 rural counties in Kyungsang Nam Do. Instruments included the Nalongyee Children's Achievement Motivation Test by the author and the School Readiness "Lest by Unhai Rhee. Data were analyzed by Pearson r and Z-test. Readiness was positively related to the total score and sub-areas of achievement motivation (.10-.43). Sub-areas of the achievement motivation test were related to each of the 4 factors of the readiness test. The correlations ranged from .00-.35 with the personal-social response factor, .00-.26 with the associative vocabulary factor, .05-.31 with the number concept factor, and .03-.37 with the perception factor. Significant differences in correlations were found between urban and rural areas for self-confidence, interest in learning, interest in kindergarten and physical competence.

• Journal of the Korean Regional Science Association
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• v.39 no.2
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• pp.47-61
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• 2023

Satisfaction on the residential environment is a major factor influencing the choice of residence and migration, and is directly related to the quality of life in the city. As online services of real estate increases, people's evaluation on the residential environment can be easily checked and it is possible to analyze their satisfaction and its determining factors based on their evaluation. This means that a larger amount of evaluation can be used more efficiently than previously used methods such as surveys. This study analyzed the residential environment reviews of about 30,000 apartment residents collected from 'Zigbang', an online real estate service in Seoul. The apartment review of Zigbang consists of an evaluation grade on a 5-point scale and the evaluation content directly described by the dweller. At first, this study labeled apartment reviews as positive and negative based on the scores of recommended reviews that include comprehensive evaluation about apartment. Next, to classify them automatically, developed a model by using Bidirectional Encoder Representations from Transformers(BERT), a deep learning-based natural language processing model. After that, by using SHapley Additive exPlanation(SHAP), extract word tokens that play an important role in the classification of reviews, to derive determining factors of the evaluation of the residential environment. Furthermore, by analyzing related keywords using Word2Vec, priority considerations for improving satisfaction on the residential environment were suggested. This study is meaningful that suggested a model that automatically classifies satisfaction on the residential environment into positive and negative by using apartment review big data and deep learning, which are qualitative evaluation data of residents, so that it's determining factors were derived. The result of analysis can be used as elementary data for improving the satisfaction on the residential environment, and can be used in the future evaluation of the residential environment near the apartment complex, and the design and evaluation of new complexes and infrastructure.

• Convergence Security Journal
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• v.18 no.5_1
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• pp.45-51
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• 2018

As data utilization and importance becomes important, data-related accidents and damages are gradually increasing. Especially, insider threats are the most harmful threats. And these insider threats are difficult to detect by traditional security systems, so rule-based abnormal behavior detection method has been widely used. However, it has a lack of adapting flexibly to changes in new attacks and new environments. Therefore, in this paper, we propose an adaptive anomaly movement detection framework based on a statistical Markov model to detect insider threats in advance. This is designed to minimize false positive rate and false negative rate by adopting environment factors that directly influence the behavior, and learning data based on statistical Markov model. In the experimentation, the framework shows good performance with a high F2-score of 0.92 and suspicious behavior detection, which seen as a normal behavior usually. It is also extendable to detect various types of suspicious activities by applying multiple modeling algorithms based on statistical learning and environment factors.

• Information Systems Review
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• v.22 no.1
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• pp.1-16
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• 2020

Blockchain is emerging as a technology that can build trust between users participating in the system. As interest of Blockchain has increased, previous studies have mainly focused on cryptocurrency and application methods related to Blockchain technology. On the other hand, the studies on the stable implementation of Blockchain were rarely conducted. Typically, uncle block in the Blockchain plays an important role in the stable implementation of the Blockhain system, but no study was conducted on this. Drawing on this recognition, this study attempts to predict the uncle block of Blockchain using machine learning method, Blockchain information, and macro-economic factors. The results of artificial neural network and support vector machine analysis, Blockchain information and macro-economic factors contributed to the prediction of uncle block of Blockchain. In addition, artificial neural network using only Blockchain information provided the best performance for predicting the occurrence of uncle block. This study suggests ways to lead and contribute to Blockchain research in information systems filed.