• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.179-192
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• 2014

Keeping in line with the recent changes in the information technology environment, the online learning environment that supports multiple users' participation such as MOOC (Massive Open Online Courses) has become important. One of the largest professional associations in Information Technology, IEEE Computer Society, announced that "Supporting New Learning Styles" is a crucial trend in 2014. Popular MOOC services, CourseRa and edX, have continued to build active learning environment with a large number of lectures accessible anywhere using smart devices, and have been used by an increasing number of users. In addition, collaborative web services (e.g., blogs and Wikipedia) also support the creation of various user-uploaded learning materials, resulting in a vast amount of new lectures and learning materials being created every day in the online space. However, it is difficult for an online educational system to keep a learner' motivation as learning occurs remotely, with limited capability to share knowledge among the learners. Thus, it is essential to understand which materials are needed for each learner and how to motivate learners to actively participate in online learning system. To overcome these issues, leveraging the constructivism theory and collective intelligence, we have developed a social bookmarking system called WeStudy, which supports learning material sharing among the users and provides personalized learning material recommendations. Constructivism theory argues that knowledge is being constructed while learners interact with the world. Collective intelligence can be separated into two types: (1) collaborative collective intelligence, which can be built on the basis of direct collaboration among the participants (e.g., Wikipedia), and (2) integrative collective intelligence, which produces new forms of knowledge by combining independent and distributed information through highly advanced technologies and algorithms (e.g., Google PageRank, Recommender systems). Recommender system, one of the examples of integrative collective intelligence, is to utilize online activities of the users and recommend what users may be interested in. Our system included both collaborative collective intelligence functions and integrative collective intelligence functions. We analyzed well-known Web services based on collective intelligence such as Wikipedia, Slideshare, and Videolectures to identify main design factors that support collective intelligence. Based on this analysis, in addition to sharing online resources through social bookmarking, we selected three essential functions for our system: 1) multimodal visualization of learning materials through two forms (e.g., list and graph), 2) personalized recommendation of learning materials, and 3) explicit designation of learners of their interest. After developing web-based WeStudy system, we conducted usability testing through the heuristic evaluation method that included seven heuristic indices: features and functionality, cognitive page, navigation, search and filtering, control and feedback, forms, context and text. We recruited 10 experts who majored in Human Computer Interaction and worked in the same field, and requested both quantitative and qualitative evaluation of the system. The evaluation results show that, relative to the other functions evaluated, the list/graph page produced higher scores on all indices except for contexts & text. In case of contexts & text, learning material page produced the best score, compared with the other functions. In general, the explicit designation of learners of their interests, one of the distinctive functions, received lower scores on all usability indices because of its unfamiliar functionality to the users. In summary, the evaluation results show that our system has achieved high usability with good performance with some minor issues, which need to be fully addressed before the public release of the system to large-scale users. The study findings provide practical guidelines for the design and development of various systems that utilize collective intelligence.

• Cartoon and Animation Studies
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• s.36
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• pp.469-491
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• 2014

Webtoon has developed the method that makes it possible to express sound visually. Also we can also hear sound in webtoon through the development of web technology. It is natural that we analyze the sound that we can hear, but we can also analyze the sound that we can not hear. This study is based on 'dual code' in cognitive psychology. Cartoonists can make visual expression on the basis of auditive impression and memory, and readers can recall the sound through the process of memory and memory-retrieval. This study analyzes both audible sound and inaudable sound. Concise analysis owes the method to film sound theory. Three main factor, Volume, pitch, and tone are recognized by frequency in acoustics. On the other hand they are expressed by the thickness and site of line and image of sound source. The visual expression of in screen sound and off screen sound is related to the frame of comics. Generally the outside of frame means off sound, but some off sound is in the frame. In addition, horror comics use much sound for the effect of genre like horror film. When analyzing comics sound using this kinds of the method film sound analysis, we can find that webtoon has developed creative expression method comparing with simple ones of early comics. Especially arranging frames and expressing sound following and vertical moving are new ones in webtoon. Also types and arrangement of frame has been varied. BGM is the first in using audible sound and recently BGM composed mixing sound effect is being used. In addition, the program which makes it possible for readers to hear sound according to scroll moving. Especially horror genre raise the genre effects using this technology. Various methods of visualizing sound are being created, and the change shows that webtoon could be the model of convergence in contents.

• Korean Journal of Psychosomatic Medicine
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• v.23 no.1
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• pp.26-35
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• 2015

Objectives:The purpose of this study was to evaluate reliability and validity of the Korean version of the Postconcussional Syndrome Questionnaire(KPCSQ) which was originally developed in 1992 by Lees-Haley. Methods:Patients with traumatic brain injury were recruited from April 2009 to December 2011 from the Korean University Ansan Hospital. We selected patients that met the ICD-10 diagnostic criteria of postconcussional syndrome and organic mental disorder including organic mood disorder, organic emotionally labile disorder, organic anxiety disorder and organic personality disorder. The KPCSQ, Trait and State Anxiety Inventory(STAI-I, II), and Center for Epidemiologic Studies Depression Scale(CESD) were administered to all subjects. Factor analysis of the items were performed and test-retest correlation were evaluated. Internal consistency of the KPCSQ and its subscales was assessed with Cronbach's alpha. External validity of the KPCSQ were examined by correlation coefficient with the STAI-I, II, and CESD. Results:The Cronbach's alpha coefficient of the total PCSQ was 0.956. The test-retest reliability coefficient was 0.845. The PCSQ showed significant correlation with STAI-I, II and CESD. The factor analysis of the PCSQ yielded 4 factors model. Factor 1 represented 'affective and cognitive symptoms', factor 2 represented 'somatic symptoms', factor 3 represented 'infrequent symptoms' and factor 4 represented 'exaggeration or inattentive response'. There was no significant difference between the PCS group and the organic mental disorder group in the score on each measure. The scores on KPCSQ and its subscales in the subjects that had scored 5 or more in 'exaggeration or inattentive response' are significantly higher than those in the subjects had scored 4 in 'exaggeration or inattentive response'. Conclusions:This study suggests that the Korean version of PCSQ is a valid and reliable tool for assessing psychiatric symptomatology of patients with traumatic brain injury. Further investigations with greater numbers of subjects are necessary to assess the clinical usefulness of the KPCSQ.

• Journal of the Korean earth science society
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• v.42 no.2
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• pp.201-220
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• 2021

The objective of this study is to increase awareness and interest regarding polar science and thereby aid in establishing the concept and future direction of polar literacy. To analyze the current status, textbooks based on the common school curriculum pertaining to polar topics were reviewed. Six countries that actively conduct polar science, namely Korea, France, Japan, Germany, the United States, and the United Kingdom, were chosen. Subsequently, 402 cases in 110 science and social studies (geography) textbooks of these countries were analyzed through both quantitative and qualitative methods. Based on the obtained results, the importance of polar research in geoscience education and the need for spreading awareness regarding polar research as an indicator of global environmental changes were examined. It was found that the primary polar topics described in the textbooks are polar glaciers, polar volcanism, solid geophysics, polar infrastructure, and preservation of geological resources and heritage. This demonstrates that the polar region is a field of research with important clues to Earth's past, present, and future environments and is also a good teaching subject for geological education. However, an educational approach is needed for systematically laying emphasis on polar research. The implications of this study are manifold, such as the establishment of a cooperative system between polar scientists and educators, extraction of core concepts for polar literacy and content reconstruction, discovery of new polar topics associated with the curriculum, diversification of forms of presentation in textbooks, and development of an affective image that is based on correct cognitive understanding. Furthermore, through the continuance of polar topics in textbooks, students can improve their awareness regarding polar literacy and polar science culture, which in turn will serve as the driving force for sustainable polar research in the future.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.43-61
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• 2019

Development of technologies in artificial intelligence has been rapidly increasing with the Fourth Industrial Revolution, and researches related to AI have been actively conducted in a variety of fields such as autonomous vehicles, natural language processing, and robotics. These researches have been focused on solving cognitive problems such as learning and problem solving related to human intelligence from the 1950s. The field of artificial intelligence has achieved more technological advance than ever, due to recent interest in technology and research on various algorithms. The knowledge-based system is a sub-domain of artificial intelligence, and it aims to enable artificial intelligence agents to make decisions by using machine-readable and processible knowledge constructed from complex and informal human knowledge and rules in various fields. A knowledge base is used to optimize information collection, organization, and retrieval, and recently it is used with statistical artificial intelligence such as machine learning. Recently, the purpose of the knowledge base is to express, publish, and share knowledge on the web by describing and connecting web resources such as pages and data. These knowledge bases are used for intelligent processing in various fields of artificial intelligence such as question answering system of the smart speaker. However, building a useful knowledge base is a time-consuming task and still requires a lot of effort of the experts. In recent years, many kinds of research and technologies of knowledge based artificial intelligence use DBpedia that is one of the biggest knowledge base aiming to extract structured content from the various information of Wikipedia. DBpedia contains various information extracted from Wikipedia such as a title, categories, and links, but the most useful knowledge is from infobox of Wikipedia that presents a summary of some unifying aspect created by users. These knowledge are created by the mapping rule between infobox structures and DBpedia ontology schema defined in DBpedia Extraction Framework. In this way, DBpedia can expect high reliability in terms of accuracy of knowledge by using the method of generating knowledge from semi-structured infobox data created by users. However, since only about 50% of all wiki pages contain infobox in Korean Wikipedia, DBpedia has limitations in term of knowledge scalability. This paper proposes a method to extract knowledge from text documents according to the ontology schema using machine learning. In order to demonstrate the appropriateness of this method, we explain a knowledge extraction model according to the DBpedia ontology schema by learning Wikipedia infoboxes. Our knowledge extraction model consists of three steps, document classification as ontology classes, proper sentence classification to extract triples, and value selection and transformation into RDF triple structure. The structure of Wikipedia infobox are defined as infobox templates that provide standardized information across related articles, and DBpedia ontology schema can be mapped these infobox templates. Based on these mapping relations, we classify the input document according to infobox categories which means ontology classes. After determining the classification of the input document, we classify the appropriate sentence according to attributes belonging to the classification. Finally, we extract knowledge from sentences that are classified as appropriate, and we convert knowledge into a form of triples. In order to train models, we generated training data set from Wikipedia dump using a method to add BIO tags to sentences, so we trained about 200 classes and about 2,500 relations for extracting knowledge. Furthermore, we evaluated comparative experiments of CRF and Bi-LSTM-CRF for the knowledge extraction process. Through this proposed process, it is possible to utilize structured knowledge by extracting knowledge according to the ontology schema from text documents. In addition, this methodology can significantly reduce the effort of the experts to construct instances according to the ontology schema.

• Therapeutic Science for Rehabilitation
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• v.10 no.2
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• pp.109-128
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• 2021

Objective : The purpose of this study was to develop a Korean version of the Activities of Daily Living (ADL)-focused Occupation-Based Neurobehavioral Evaluation (A-ONE) through cross-cultural adaptation and examine its validity and reliability. Methods : This study translated the A-ONE into Korean and performed cross-cultural adaptation for the Korean population. After the development of the Korean version of the A-ONE, cross-cultural and concurrent validities were analyzed. Internal consistency, test-retest reliability, and inter-rater reliability were also evaluated. Results : We adapted three items to the Korean culture. The Korean version of the A-ONE showed high cross-cultural validity with a content validity index (I-CVI) >0.9. It correlated with the Functional Independence Measure (FIM) (r=0.52-0.77, p<0.001), except for communication. Cronbach's α was 0.58-0.93 for the functional independence scale (FI) and 0.42-0.93 for the neurobehavioral specific impairment subscale (NBSIS). Intraclass correlation coefficients (ICCs) indicated high test-retest and inter-rater reliability for FI (ICC=0.79-1.00 and 0.75-1.00, respectively) and NBSIS (ICC=0.74-1.00 and 0.72-1.00, respectively). Conclusion : The Korean version of the A-ONE is well adapted to the Korean culture and has good validity and reliability. It is recommended to evaluate ADL performance skills and neurobehavioral impairments simultaneously in Korea.

• The Journal of Korean Academy of Sensory Integration
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• v.19 no.1
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• pp.69-82
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• 2021

Objective : This recent work intended to provide basic information for researchers and practitioners related to occupational therapy about Developmental Coordination Disorder (DCD) in South Korea. The previous research of screening DCD and the effects of intervention programs were reviewed. Methods : Peer-reviewed papers relating to DCD and published in Korea from January 1990 to December 2020 were systematically reviewed. The search terms "developmental coordination disorder," "development coordination," and "developmental coordination" were used to identify previous Korean research in this area from three representation database, the Research Information Sharing Service, Korean Studies Information Service System, and Google Scholar. We found a total of 4,878 articles identified through the three search engines and selected seventeen articles for analysis after removing those that corresponded to the overlapping or exclusion criteria. We adopted "the conceptual model" to analyze the selected articles about DCD assessment and intervention. Results : We found that twelve of the 17 studies showed the qualitative level of Level 2 using non-randomized approach between the two groups. The Movement Assessment Battery for Children and its second edition were the most frequently used tools in assessing children for DCD. Among the intervention studies, the eight articles (47%) were adopted a dynamic systems approach; a normative functional skill framework and cognitive neuroscience were each used in 18% of the pieces; and 11% of the articles were applied neurodevelopmental theory. Only one article was used a combination approach of normative functional skill and general abilities. These papers were mainly focused on the movement characteristics of children with DCD and the intervention effect of exercise or sports programs. Conclusion : Most of the reviewed studies investigated the movement characteristics of DCD or explore the effectiveness of particular intervention programs. In the future, it would be useful to investigate the feasibility of different assessment tools and to establish the effectiveness of various interventions used in rehabilitation for better motor performance in children with DCD.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.49-71
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• 2021

Users who intend to utilize knowledge to actively solve given problems proceed their jobs with cross- and sequential exploration of associated knowledge related each other in terms of certain criteria, such as content relevance. A knowledge map is the diagram or taxonomy overviewing status of currently managed knowledge in a knowledge-base, and supports users' knowledge exploration based on certain relationships between knowledge. A knowledge map, therefore, must be expressed in a networked form by linking related knowledge based on certain types of relationships, and should be implemented by deploying proper technologies or tools specialized in defining and inferring them. To meet this end, this study suggests a methodology for developing the knowledge graph-based knowledge map using the Graph DB known to exhibit proper functionality in expressing and inferring relationships between entities and their relationships stored in a knowledge-base. Procedures of the proposed methodology are modeling graph data, creating nodes, properties, relationships, and composing knowledge networks by combining identified links between knowledge. Among various Graph DBs, the Neo4j is used in this study for its high credibility and applicability through wide and various application cases. To examine the validity of the proposed methodology, a knowledge graph-based knowledge map is implemented deploying the Graph DB, and a performance comparison test is performed, by applying previous research's data to check whether this study's knowledge map can yield the same level of performance as the previous one did. Previous research's case is concerned with building a process-based knowledge map using the ontology technology, which identifies links between related knowledge based on the sequences of tasks producing or being activated by knowledge. In other words, since a task not only is activated by knowledge as an input but also produces knowledge as an output, input and output knowledge are linked as a flow by the task. Also since a business process is composed of affiliated tasks to fulfill the purpose of the process, the knowledge networks within a business process can be concluded by the sequences of the tasks composing the process. Therefore, using the Neo4j, considered process, task, and knowledge as well as the relationships among them are defined as nodes and relationships so that knowledge links can be identified based on the sequences of tasks. The resultant knowledge network by aggregating identified knowledge links is the knowledge map equipping functionality as a knowledge graph, and therefore its performance needs to be tested whether it meets the level of previous research's validation results. The performance test examines two aspects, the correctness of knowledge links and the possibility of inferring new types of knowledge: the former is examined using 7 questions, and the latter is checked by extracting two new-typed knowledge. As a result, the knowledge map constructed through the proposed methodology has showed the same level of performance as the previous one, and processed knowledge definition as well as knowledge relationship inference in a more efficient manner. Furthermore, comparing to the previous research's ontology-based approach, this study's Graph DB-based approach has also showed more beneficial functionality in intensively managing only the knowledge of interest, dynamically defining knowledge and relationships by reflecting various meanings from situations to purposes, agilely inferring knowledge and relationships through Cypher-based query, and easily creating a new relationship by aggregating existing ones, etc. This study's artifacts can be applied to implement the user-friendly function of knowledge exploration reflecting user's cognitive process toward associated knowledge, and can further underpin the development of an intelligent knowledge-base expanding autonomously through the discovery of new knowledge and their relationships by inference. This study, moreover than these, has an instant effect on implementing the networked knowledge map essential to satisfying contemporary users eagerly excavating the way to find proper knowledge to use.

• Journal of Christian Education in Korea
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• v.71
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• pp.121-154
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• 2022

This study is to summarize the relationship between youth in terms of developmental psychology, university education, faith, and spirituality in order to form and improve relationships, which are major developmental tasks of youth, and to suggest Christian youth education by the elements of education. Relationships are formed when you are connected to another person and community, feel interested in each other, feel a sense of bond and belonging, and maintain a stable and satisfactory relationship. This is not skill or technology, but is related to life attitude and value, and continuous learning and training are required. Various developmental tasks in youth have something in common with relationships. Relationships positively affect the lives of young people, such as satisfaction with college life in the early stages of youth, adaptation to college life, personality, and career decision. Relationships are also very important in faith because human existence and faith are defined and formed through relationships. The relationship between the community and others plays an important role in spiritual development for the meaning of life and inner growth. In the aspects of learners and educational environment, it was suggested to understand learners with desire for relationships, the generation they live in, and the educational environment in which the relationship between young people occurs. In terms of teachers, teachers have to try to change their roles such as facilitators, guides, managers, and mentors. For the educational purpose and content, it was suggested that relationships should be the ultimate purpose and the educational content for this was presented in three different types of relationships and each main contents to be dealt with. In terms of educational method, it was proposed to select a learner-centered group learning method that induces communication and active participation of learners to cause interaction by considering other elements of education according to the content of the relationship in the cognitive, emotional, and behavioral dimensions. In the aspects of educational results and evaluation, it was proposed to confirm that what was considered during the educational planning stage was effectively carried out in actual education, to evaluate various evaluation methods, various aspects, and to summarize the evaluation results for the specific application.

• Korean Journal of Health Education and Promotion
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• v.2 no.1
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• pp.31-61
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• 2000

Introduction. Despite the fact that half of premature deaths are caused by unhealthy lifestyles such as smoking tobacco, sedentary lifestyle, alcohol and drug abuse and poor nutrition, there are no theoretical models which accurately explain these health promotion related behaviors. This study tests a new model of health behavior called the Model of Health Promotion Behavior. This model draws on elements and frameworks suggested by the Health Belief Model, Social Cognitive Theory, the Theory of Planned Action and the Health Promotion Model. This model is intended as a general model of behavior but this first test of the model uses amount of exercise as the outcome behavior. Design. This study utilized a cross sectional mail-out, mail-back survey design to determine the elements within the model that best explained intentions to exercise and those that best explained amount of exercise. A follow-up questionnaire was mailed to all respondents to the first questionnaire about 10 months after the initial survey. A pretest was conducted to refine the questionnaire and a pilot study to test the protocols and assumptions used to calculate the required sample size. Sample. The sample was drawn from 2000 eligible participants at two blue collar (utility company and part of a hospital) and two white collar (bank and pharmaceutical) companies located in Southeastern Michigan. Both white collar site had employee fitness centers and all four sites offered health promotion programs. In the first survey, 982 responses were received (49.1％) after two mailings to non-respondents and one additional mailing to secure answers to missing data, with 845 usable cases for the analyzing current intentions and 918 usable cases for the explaining of amount of current exercise analysis. In the follow-up survey, questionnaires were mailed to the 982 employees who responded to the initial survey. After one follow-up mailing to non-respondents, and one mailing to secure answers to missing data, 697 (71.0％) responses were received, with 627 (63.8％) usable cases to predict intentions and 673 (68.5％) usable cases to predict amount of exercise. Measures. The questionnaire in the initial survey had 15 scales and 134 items; these scales measured each of the variables in the model. Thirteen of the scales were drawn from the literature, all had Cronbach's alpha scores above .74 and all but three had scores above .80. The questionnaire in the second mailing had only 10 items, and measured only outcome variables. Analysis. The analysis included calculation of scale scores, Cronbach's alpha, zero order correlations, and factor analysis, ordinary least square analysis, hierarchical tests of interaction terms and path analysis, and comparisons of results based on a random split of the data and splits based on gender and employer site. The power of the regression analysis was .99 at the .01 significance level for the model as a whole. Results. Self efficacy and Non-Health Benefits emerged as the most powerful predictors of Intentions to exercise, together explaining approximately 19％ of the variance in future Intentions. Intentions, and the interaction of Intentions with Barriers, with Support of Friends, and with Self Efficacy were the most consistent predictors of amount of future exercise, together explaining 38％ of the variance. With the inclusion of Prior Exercise History the model explained 52％ of the variance in amount of exercise 10 months later. There were very few differences in the variables that emerged as important predictors of intentions or exercise in the different employer sites or between males and females. Discussion. This new model is viable in predicting intentions to exercise and amount of exercise, both in absolute terms and when compared to existing models.