• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.8
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• pp.2814-2832
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• 2014

As information society matures to an even higher level and as information technology becomes a necessity to our everyday lives, the needs to develop, support and satisfy personal and social needs without the limitation of time, space, and location have become a vital point to everyday lives. Smartphone users are increasing at a staggering rate but the research on mobile-Learning model and the implementation of m-Learning scenario are still behind the needs of the users. Therefore, this paper focuses on the design of 'repeatable and short-spanned m-Learning model' to meet the needs of the learners who are on the go and on the move with their smartphones. Smartphone users frequently reach out for their phones but compare to the frequencies, the actual span of time they spend per use are relatively and surprisingly short. One way to understand this phenomenon is that the users tend to immediately replace their smartphones with laptops or desktops whenever they are available. A leaning model was needed to reflect this short and frequent use, a use that is solely based on the smartphone environment. This proposed learning model first defines this particular setting and implements the model to real smartphone users over an 8 week period. To understand whether different learning backgrounds can influence this model, different schools with online and offline learning channels participated in the experiment. User survey was conducted after the experiment to get a better understanding of the smartphone users. Pretest and posttest were conducted before and after the experiment and the data were validated and analyzed using SPSS version 18.0 for PC. Preliminary descriptive statistics, multiple regression and cross validation was conducted for the analysis. The results showed that the proposed English Listening and Comprehension Mobile Digital Textbook (ELCMDT) had a positive effect on the learners in general and was more effective for learners who were already experienced with online learning.

• Asia pacific journal of information systems
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• v.9 no.1
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• pp.193-209
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• 1999

Developing Information Systems is a process of decomposing the entire systems into sub systems and identifying a hierarchical structure among the sub systems. Diagrammatic representation of hierarchy is an essential part of systems development since the identified hierarchical structures are usually presented in diagrams. The main goal of this research is to identify the most effective ways of representing system structures using diagrams. In order to achieve the main goal, this study performed three phases of research. In the first step, a theoretical model was constructed to conceptually explain users' comprehension on diagrams. Then visual factors of diagrammatic representations were identified based on the diagrams used in systems development. Finally, three consecutive experiments were conducted to identify the impacts of visual factors on the level of users' comprehension. The results indicate that familiarity and affordance of diagrams affect the degree of comprehension about the diagrams, which is in turn influenced by the complexity of tasks and the types of hierarchies. This paper concludes with the limitations of the study results and implications in the development of information systems.

• Journal of the HCI Society of Korea
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• v.9 no.2
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• pp.23-31
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• 2014

A variety of writing support systems focus on the information management or the feature analysis of the commercially successful narrative texts. In these approaches, the reader's role in the narrative creating process is overlooked. During a writing work, an author anticipates the reader's response or expectation to the narrative and he/she organizes the narrative either along or against the prediction about readers. Assessing and controlling the reader's comprehension in the development of events influences the aesthetic quality of the narrative. In this paper, we suggest a writing support system to visualize and adjust the characteristics of a narrative text related to the reader's comprehension, which is theoretically based on the narrative structure model and the event-indexing situation model. Under the development of the support system, we designed an interactive framework to create events as the basic units of story and arrange them onto both story- and discourse-time axes. Using this framework, we analyzed the organization of events about an actual film narrative. We also proposed both the continuity of the situational dimensions and the cognitive complexity as the characteristics to affect the reader's comprehension, hence we devised a method to visualize and evaluate them. This method was applied to the actual film narrative and the result was discussed in the aspect of the features of the narrative and wiring support strategies.

• Korean Journal of Child Studies
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• v.37 no.6
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• pp.107-117
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• 2016

Objective: This study examined the construct validity of K-WPPSI-IV. Factor structures of the structures of the K-WPPSI-IV full scale as well as primary index scales for two age ranges (2 years, 6 months to 3 years, 11 months; 4 years to 7 years, 7 months) were examined. Methods: Data were collected from 1,700 children aged 2 years, 6 months to 7 years, 7 months during the K-WPPSI-IV standardization. Confirmatory factor analyses were conducted using the K-WPPSI-IV subtest performances with maximum likelihood estimation using Amos 18. Results: First, the three-factor model (verbal comprehension, visual spatial, and working memory) fitted best for the younger age range. However, the five-factor model (verbal comprehension, visual spatial, fluid reasoning, working memory, and processing speed) fitted best for the older age range. Residuals suggest the presence of two nested subfactors within the verbal comprehension factor (broad/expressive and focused/simple). Second, the confirmatory factor analysis on primary index subtests identified factors that account for the intercorrelations among the reduced sets of primary index subtests. Conclusion: The findings showed that the theoretical structures of WPPSI-IV subtests were confirmed within K-WPPSI-IV.

• Journal of Internet Computing and Services
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• v.12 no.1
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• pp.119-130
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• 2011

As a de facto standard for system modeling, UML diagrams have been widely used in the industry. Of these, the class diagram is useful to visualize the classes and their relationships and thus directly influences the forward and reverse processes of system modeling and development. Many earlier studies have attempted to examine as to what impact the layout and complexity of the class diagram would have on the comprehension of system modeling. However, their findings have been equivocal and it is not easy to understand the effects of diagram layout. Accordingly this research relied on the guidelines of diagram layout suggested in the earlier studies and designed a 2 (layout) x 2 (complexity) factorial design to examine their impact on diagram comprehension. 47 subjects were participated in the experiment where class diagrams were provided differently in their layout and complexity. We found that a good layout was significantly more effective than the bad. Furthermore the results were significantly persistent in the complex group than the simple. However, there was no interaction effect between layout and complexity of the diagram.

• Journal of Internet of Things and Convergence
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• v.8 no.5
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• pp.17-25
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• 2022

Recently the massive amount of data has been generated because of the number of edge devices increases. And especially, the number of raw unstructured HTML documents has been increased. Therefore, MRC(Machine Reading Comprehension) in which a natural language processing model finds the important information within an HTML document is becoming more important. In this paper, we propose HTDE(HTML Tag Depth Embedding Method), which allows the BERT to train the depth of the HTML document structure. HTDE makes a tag stack from the HTML document for each input token in the BERT and then extracts the depth information. After that, we add a HTML embedding layer that takes the depth of the token as input to the step of input embedding of BERT. Since tokenization using HTDE identifies the HTML document structures through the relationship of surrounding tokens, HTDE improves the accuracy of BERT for HTML documents. Finally, we demonstrated that the proposed idea showing the higher accuracy compared than the accuracy using the conventional embedding of BERT.

• Journal of the Korean School Mathematics Society
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• v.4 no.1
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• pp.9-27
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• 2001

The purpose of this study is to develop effective models for performance assesment in the subject of mathematics, In this study, a procedural model was created through selecting five evaluation methods that are the most relevant to evaluate mathematics comprehension. Also this study provides the application of procedural model over the span of an academic semester.

• International Journal of Advanced Culture Technology
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• v.12 no.3
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• pp.73-79
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• 2024

The smart tourism chatbot service provide smart tourism services to users easily and conveniently along with the smart tourism app. In this paper, the tourism information QA (Question Answering) service is proposed based on the task-oriented smart tourism chatbot system [13]. The tourism information QA service is an MRC (Machine reading comprehension)-based QA system that finds answers in context and provides them to users. The tourism information QA system consists of NER (Named Entity Recognition), DST (Dialogue State Tracking), Neo4J graph DB, and QA servers. We propose tourism information QA service uses the tourism information NER model and DST model to identify the intent of the user's question and retrieves appropriate context for the answer from the Neo4J tourism knowledgebase. The QA model finds answers from the context and provides them to users through the smart tourism app. We develop the tourism information QA model by transfer learning the bigBird model, which can process the context of 4,096 tokens, using the tourism information QA dataset.

• Journal of The Korean Association For Science Education
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• v.22 no.5
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• pp.1010-1029
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• 2002

The purpose of this research was to survey middle school students' preference for science and its causal factors, so as to analyze the causal relationships between them. Preference for science and its causal factors were defined theoretically, and a theoretical model was constructed to measure them and analyze the causal relationship by structural equation modeling. According to the theoretical model and a pilot test, a questionnaire was developed with three parts; the background information of a respondent, the preference for science, and the causal factors of preference. The questionnaire was administered to one class per grade of randomly selected 8 middle schools from 4 areas across the country, and 819 students' data were collected. Preference for science was defined as a state of mind. It revealed to what extent, and how, one likes science. It consisted of 3 categories - 'emotional response', 'behavioral volition', 'valuational comprehension', and each category was divided into two subcategories. Causal factors affecting the preference for science consisted of three categories - personal, educational and social factors, and each was divided into 2 or 3 subcategories. Middle school students' preference for science was middling as a total. Curiosity about contents of science and valuation of science were high, comparatively, but behavioral volition about science was especially low. Students' responses to the causal factors were relatively high in every educational factor and sociocultural valuation of social factors, but relatively low in socioeconomic rewards of social factors, and especially low in personal factors. The causal relationship about the preference for science was investigated by multiple regression analysis and path analysis, using the structural equation model. Multiple regression analysis about the preference for science and its causal factors revealed important factors. The important factors were personal ability, the personal traits, rewards in school science, and contents of school science in order of magnitude of standardized regression coefficient ${\beta}$. Stepwise regression analysis with each of the subcategories of the preference for science as dependent variables showed what factors were important in each subcategory. According to the result of structural equation modeling, personal factors affected 'emotional response' and 'behavioral volition' directly, and social factors affected 'valuational comprehension' directly. Educational factors affected all categories of the preference for science by influencing not only 'emotional response' and 'valuational comprehension' directly, but also 'behavioral volition' indirectly. The way to promote middle school students' preference for science was suggested, based on the analysis result.

• Knowledge Management Research
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• v.20 no.2
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• pp.87-103
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• 2019

The purpose of this study was to explore the factors influencing acceptance (e.g., comprehension,) and diffusion of information recipients' by depending on the authenticity of news. Specifically, this study has examined the effects of the news contents(political vs. general), need for cognition(high vs. low) and authenticity of the News(real news vs. fake news) on both acceptance and diffusion of news. Based on previous work, this study has developed a conceptual model to present each research hypothesis and tested it by conducting experiments as the follows. As a result, according to the authenticity of the news and the contents of the news (political and general), the acceptance of political contents was high regardless of the authenticity of the news, and the acceptance of real news was higher than that of fake news. However, in the proliferation (comment), both the political contents and the general contents showed the characteristic of spreading (commenting) fake news rather than real news. contrary to this, the cognitive level did not show any significant difference in acceptance (understanding) and proliferation (comment, sharing, recommendation). This study provides academic implications in that it examines the influences of accepting (comprehension) and diffusion (comment, sharing, recommendation) of real news and fake news. It also provides practical implications for responding to fake news and new marketing strategies in an environment where contents are delivered through diverse social media.