• Information Systems Review
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• v.20 no.2
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• pp.39-62
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• 2018

Thanks to the growth of computing power and the recent development of data analytics, researchers have started to work on the data produced by users through the Internet or social media. This study is in line with these recent research trends and attempts to adopt data analytical techniques. We focus on the impact of "internal marketing" factors on firm performance, which is typically studied through survey methodologies. We looked into the job review platform Jobplanet (www.jobplanet.co.kr), which is a website where employees and former employees anonymously review companies and their management. With web crawling processes, we collected over 40K data points and performed morphological analysis to classify employees' reviews for internal marketing data. We then implemented econometric analysis to see the relationship between internal marketing and market capitalization. Contrary to the findings of extant survey studies, internal marketing is positively related to a firm's market capitalization only within a limited area. In most of the areas, the relationships are negative. Particularly, female-friendly environment and human resource development (HRD) are the areas exhibiting positive relations with market capitalization in the manufacturing industry. In the service industry, most of the areas, such as employ welfare and work-life balance, are negatively related with market capitalization. When firm size is small (or the history is short), female-friendly environment positively affect firm performance. On the contrary, when firm size is big (or the history is long), most of the internal marketing factors are either negative or insignificant. We explain the theoretical contributions and managerial implications with these results.

• Journal of vocational education research
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• v.37 no.6
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• pp.1-15
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• 2018

The objective of this study is to provide the basic data for the efficient operation of industry-academia partnership apprenticeship school, by analyzing the interest in the relevant policy, targeting the interested parties of school and corporation as the two main subjects operating the industry-academia partnership apprenticeship school. Using the Concerns-Based Adoption Model(CBAM) used for understanding the interested parties' interest in the adoption of a certain new changing. In the results of analysis, first, currently, the operating subjects of industry-academia partnership apprenticeship school showed the similar interest with the pattern of nonusers. In other words, currently, based on the curiosity about the relevant policy, they are interested in which roles they should perform for the successful operation. Second, when dividing the operating subjects of industry-academia partnership apprenticeship school into school parties and corporate parties, the results of examining the differences in the interest of each subject are as follows. First, in the stages except for the Stage 0(indifference), the interest of school parties was relatively higher than the one of corporate parties. It might be because the school's role is bigger in the operation of industry-academia partnership apprenticeship school, contrary to the advanced countries. In other words, in case of school parties, the overall and general understanding of the relevant policy is premised, so that their interest of each stage is higher than the one of corporate parties. Especially, the Stage 5(cooperative interest) showed the biggest differences. As the cooperation between industry and academia is the success factor of the relevant policy, it would be necessary to implant the concrete measures for industry-academia cooperation in school parties, and also to implant the importance of industry-academia cooperation in corporate parties. Next, both operating subjects showed the lowest intensity in the Stage 4(consequential interest). It means that the operating subjects' interest in the evaluation of apprenticeship students is relatively low.

• The Journal of the Korea Contents Association
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• v.16 no.2
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• pp.287-294
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• 2016

The whole design process drawing outputs from design planning is based on designers' intuitive ideas and differences in technical ability. However, every design professional agrees to the fact that such design process is filled with individuals' implicit acts or inherent intuition rather than following directions in a certain defined frame. If the design process based on such intuition and experience can start from the rational and scientific process, it would be possible to move more systematic design process to the next step. This study aims to examine what system of thinking are used by designers to conduct the design information process, by using the protocol analysis which is the representative qualitative study method of cognitive science, on designers' cognitive behaviors like the contents of the design sketch process which is the initial step of the kitchenware development process, in order to understand professionals' and non-professionals' design application direction. Thus, the scope of this paper would be limited to "the initial protocol analysis on kitchenware" and "encoding of the analysis on thinking" in the qualitative study that can be the most basic to understand the design cognitive science. As a procedure to solve this study question, it aimed to seek for the product development flow and the educational effect by considering the preceding researches and also re-interpreting cognitive thinking in systematic methods.

• Journal of Korea Port Economic Association
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• v.26 no.4
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• pp.147-167
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• 2010

The purpose of this study is to analyze the components and verify the relationship among service quality, customer satisfaction and relationship quality in liner shipping company. In order to achieve the purpose of this study, literature survey related to service quality, customer satisfaction, relationship quality was carried out and took an empirical analysis by the use of questionnaire method for employees in international freight forwarders. The final results are as follows; First, correlations between service quality and customer satisfaction are found to be positive. But service quality component of tangibles and responsiveness with customer satisfaction are not to be positive. Second, as the other study on the similar logistics industries, the correlation between customer satisfaction and relationship quality is found to be positive in this study.

• Journal of Music and Human Behavior
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• v.18 no.2
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• pp.45-66
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• 2021

This study aimed to develop a group rap making program and examine its applicability to improve communication skills of adolescents with mild intellectual disabilities (ID). Three adolescents with ID participated in a total of six 50-minute group sessions over 4 weeks. The group rap making program included three stages: understanding the context of communication, learning how to communicate with others, and applying the communicative behaviors in a group setting. To examine changes in the participants' communication skills, the rap lyrics constructed by participants were analyzed and communicative behaviors were observed during sessions and analyzed in terms of asking questions and providing information to others. Also, a social communication skills checklist was rated by the participant's caregivers. The analysis of rap lyrics showed that the expressions included in the rap were diversified as the session proceeded. Changes in observed behaviors supported that participants became to engage in communication with others more actively in order to complete the group rap. While the social communication skills checklist tended to increase, there was a difference in degree of change depending on the level of language communication skills. These results indicate that a group rap making can be an effective option for these adolescents to learn how to communicate with their peers, which presents implications for how rap making can be used for therapeutic purpose with more diversified population.

• The Journal of the Korea Contents Association
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• v.19 no.8
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• pp.316-322
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• 2019

The purpose of this study is to investigate the opinions of non-health science college students of Korean dental hygienists in the category of medical personnel. A self-reported questionnaire was conducted on 265 non-health science major students without information about a health and medical service personnel. The collected data were analyzed using frequency, percentage, descriptive statistics, chi squared and multinomial logistic regression analysis. About 40% of the respondents answered that dental hygienists should be medical personnel, while 17.7% think that they should not distinguish health and medical service personnel between medical personnel and medical service technologist. As the respondents' oral health management ability improved, they approves the Korean dental hygienists in the category of medical personnel(p=.022). As the longer the period of dental regular visits, they answered that dental hygienists should be medical service technologist. Presence or absence of dental regular visits, scaling experience, oral health education did not no significant difference on the opinions of Korean dental hygienists in the category of medical personnel of the pros and cons. This study can be used as a basic data for establishing the policy of medical personnel for dental hygienists.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.1-19
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• 2019

Artificial intelligence (AI) is one of the main driving forces leading the Fourth Industrial Revolution. The technologies associated with AI have already shown superior abilities that are equal to or better than people in many fields including image and speech recognition. Particularly, many efforts have been actively given to identify the current technology trends and analyze development directions of it, because AI technologies can be utilized in a wide range of fields including medical, financial, manufacturing, service, and education fields. Major platforms that can develop complex AI algorithms for learning, reasoning, and recognition have been open to the public as open source projects. As a result, technologies and services that utilize them have increased rapidly. It has been confirmed as one of the major reasons for the fast development of AI technologies. Additionally, the spread of the technology is greatly in debt to open source software, developed by major global companies, supporting natural language recognition, speech recognition, and image recognition. Therefore, this study aimed to identify the practical trend of AI technology development by analyzing OSS projects associated with AI, which have been developed by the online collaboration of many parties. This study searched and collected a list of major projects related to AI, which were generated from 2000 to July 2018 on Github. This study confirmed the development trends of major technologies in detail by applying text mining technique targeting topic information, which indicates the characteristics of the collected projects and technical fields. The results of the analysis showed that the number of software development projects by year was less than 100 projects per year until 2013. However, it increased to 229 projects in 2014 and 597 projects in 2015. Particularly, the number of open source projects related to AI increased rapidly in 2016 (2,559 OSS projects). It was confirmed that the number of projects initiated in 2017 was 14,213, which is almost four-folds of the number of total projects generated from 2009 to 2016 (3,555 projects). The number of projects initiated from Jan to Jul 2018 was 8,737. The development trend of AI-related technologies was evaluated by dividing the study period into three phases. The appearance frequency of topics indicate the technology trends of AI-related OSS projects. The results showed that the natural language processing technology has continued to be at the top in all years. It implied that OSS had been developed continuously. Until 2015, Python, C ++, and Java, programming languages, were listed as the top ten frequently appeared topics. However, after 2016, programming languages other than Python disappeared from the top ten topics. Instead of them, platforms supporting the development of AI algorithms, such as TensorFlow and Keras, are showing high appearance frequency. Additionally, reinforcement learning algorithms and convolutional neural networks, which have been used in various fields, were frequently appeared topics. The results of topic network analysis showed that the most important topics of degree centrality were similar to those of appearance frequency. The main difference was that visualization and medical imaging topics were found at the top of the list, although they were not in the top of the list from 2009 to 2012. The results indicated that OSS was developed in the medical field in order to utilize the AI technology. Moreover, although the computer vision was in the top 10 of the appearance frequency list from 2013 to 2015, they were not in the top 10 of the degree centrality. The topics at the top of the degree centrality list were similar to those at the top of the appearance frequency list. It was found that the ranks of the composite neural network and reinforcement learning were changed slightly. The trend of technology development was examined using the appearance frequency of topics and degree centrality. The results showed that machine learning revealed the highest frequency and the highest degree centrality in all years. Moreover, it is noteworthy that, although the deep learning topic showed a low frequency and a low degree centrality between 2009 and 2012, their ranks abruptly increased between 2013 and 2015. It was confirmed that in recent years both technologies had high appearance frequency and degree centrality. TensorFlow first appeared during the phase of 2013-2015, and the appearance frequency and degree centrality of it soared between 2016 and 2018 to be at the top of the lists after deep learning, python. Computer vision and reinforcement learning did not show an abrupt increase or decrease, and they had relatively low appearance frequency and degree centrality compared with the above-mentioned topics. Based on these analysis results, it is possible to identify the fields in which AI technologies are actively developed. The results of this study can be used as a baseline dataset for more empirical analysis on future technology trends that can be converged.

• Korean Journal of Cognitive Science
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• v.28 no.4
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• pp.315-328
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• 2017

Even though assessment using information and communication technology will most likely lead the future of educational assessment, there is little domestic research on this topic. Computerized assessment will not only cut costs but also measure students' performance in ways not possible before. In this context, this study introduces a tool which can overcome the problems of multiple choice tests, which are most widely used type of assessment in current Korean educational setting. Multiple-choice tests, in which options are presented with the questions, are efficient in that grading can be automated; however, they allow for students who don't know the answer, to find the correct answer from the options. Park(2005) has developed a modified multiple-choice testing system (CMMT) using the interactivity of computers, that presents questions first, and options later for a short time when the student requests for them. The present study was conducted to find out if penalizing wrong answers could lower the possibility of students choosing an answer among the options when they don't know the correct answer. 116 students were tested with the directions that they will be penalized for wrong answers, but not for no response. There were 4 experimental conditions: 2 conditions of high or low percentage of penalizing, each in traditional multiple-choice or CMMT format. The results were analyzed using a two-way ANOVA for the number of no response, the test score and self-report score. Analysis showed that the number of no response was significantly higher for the CMMT format and that test scores were significantly lower when the penalizing percentage was high. The possibility of applying CMMT format tests while penalizing wrong answers in actual testing settings was addressed. In addition, the need for further research in the cognitive sciences to develop computerized assessment tools, was discussed.

• Journal of The Korean Association For Science Education
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• v.38 no.2
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• pp.203-217
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• 2018

The research objective of this study is to analyze the aspects of small group decision-making process based on reading news reports in the context of the socio-scientific issues (SSI) activity related to climate change. Twenty-two high school students from Gyeonggi Province, South Korea, were asked to read two news reports on the UN climate change conferences and take a stance on joining the Paris Agreement both as an individual and as a small group. The news reports were analyzed in terms of genre, discourse, and style adapting the critical discourse analysis (CDA) and the decision-making processes of the small groups were examined on recognizing a problem and evaluating alternatives and decisions. The results from analyzing the news reports denoted that the Paris agreement is not only related to finding ideal solutions to climate change, but rather, connected to political or economic interests and power relationship. In the stage of recognizing a problem, meanwhile, different frames which students recognize the Paris agreement and discourses in the foreground of the news reports were the critical causes in terms of identifying the problem. In the stage of evaluating alternatives and decisions, the equity and fairness were the criteria for the small group discussions. This study implies the necessity of the scientific literacy instruction to develop the ability to critical reading in the context of the SSI.

• Research in Plant Disease
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• v.8 no.2
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• pp.84-91
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• 2002

Disease forecasting in Korea was first studied in the Department of Fundamental Research, in the Central Agricultural Technology Institute in Suwon in 1947, where the dispersal of air-borne conidia of blast and brown spot pathogens in rice was examined. Disease forecasting system in Korea is operated based on information obtained from 200 main forecasting plots scattered around country (rice 150, economic crops 50) and 1,403 supplementary observational plots (rice 1,050, others 353) maintained by Korean government. Total number of target crops and diseases in both forecasting plots amount to 30 crops and 104 diseases. Disease development in the forecasting plots is examined by two extension agents specialized in disease forecasting, working in the national Agricul-tural Technology Service Center(ATSC) founded in each city and prefecture. The data obtained by the extension agents are transferred to a central organization, Rural Development Administration (RDA) through an internet-web system for analysis in a nation-wide forecasting program, and forwarded far the Central Forecasting Council consisted of 12 members from administration, university, research institution, meteorology station, and mass media to discuss present situation of disease development and subsequent progress. The council issues a forecasting information message, as a result of analysis, that is announced in public via mass media to 245 agencies including ATSC, who informs to local administration, the related agencies and farmers for implementation of disease control activity. However, in future successful performance of plant disease forecasting system is thought to be securing of excellent extension agents specialized in disease forecasting, elevation of their forecasting ability through continuous trainings, and furnishing of prominent forecasting equipments. Researches in plant disease forecasting in Korea have been concentrated on rice blast, where much information is available, but are substan-tially limited in other diseases. Most of the forecasting researches failed to achieve the continuity of researches on specialized topic, ignoring steady improvement towards practical use. Since disease forecasting loses its value without practicality, more efforts are needed to improve the practicality of the forecasting method in both spatial and temporal aspects. Since significance of disease forecasting is directly related to economic profit, further fore-casting researches should be planned and propelled in relation to fungicide spray scheduling or decision-making of control activities.