• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.1
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• pp.51-73
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• 2023

Social media play a significant role in communicating information across the globe, connecting with loved ones, getting the news, communicating ideas, etc. However, a group of people uses social media to spread fake information, which has a bad impact on society. Therefore, minimizing fake news and its detection are the two primary challenges that need to be addressed. This paper presents a multi-modal deep learning technique to address the above challenges. The proposed modal can use and process visual and textual features. Therefore, it has the ability to detect fake information from visual and textual data. We used EfficientNetB0 and a sentence transformer, respectively, for detecting counterfeit images and for textural learning. Feature embedding is performed at individual channels, whilst fusion is done at the last classification layer. The late fusion is applied intentionally to mitigate the noisy data that are generated by multi-modalities. Extensive experiments are conducted, and performance is evaluated against state-of-the-art methods. Three real-world benchmark datasets, such as MediaEval (Twitter), Weibo, and Fakeddit, are used for experimentation. Result reveals that the proposed modal outperformed the state-of-the-art methods and achieved an accuracy of 86.48%, 82.50%, and 88.80%, respectively, for MediaEval (Twitter), Weibo, and Fakeddit datasets.

• International Journal of Knowledge Content Development & Technology
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• v.13 no.3
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• pp.7-30
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• 2023

Nigeria is a country with multiple ethnic groups; as a result, English language is used as a lingua franca to enhance information flow. Despite this, the Indigenous languages of communities are mostly used for interactions, even in university environments thereby affecting smooth interaction for those who do not understand them. This study therefore investigated the impact of being a linguistic outsider on information access, learning and social wellbeing of students. Descriptive research of a case study was used for this study. The population for this study consisted of non-Yoruba indigenous students. Judgmental sampling technique was used to select 50 non-indigenous students; structured interview was used. Results showed that Yoruba indigenous language was used lightly in the classroom and heavily outside the classroom, with mixtures of pidgin and English languages. It was found that being a linguistic outsider had a negative influence on information access. However it was not a total dependent factor to social wellbeing of students who desire for their various languages to be predominantly used and for them to enjoy equal benefits with Yoruba indigenes. This study also revealed that being a linguistic outsider does not have negative influence on academic learning. It was recommended that the stakeholders in university management promote the complete use of English language in the classroom while students should be encouraged to interpret Yoruba language when spoken in the midst of non-indigenes.

• Journal of Information Technology Applications and Management
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• v.30 no.1
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• pp.53-70
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• 2023

Artificial intelligence has become familiar with modern society, not the distant future. As artificial intelligence and machine learning developed more highly and became more complicated, it became difficult for people to grasp its structure and the basis for decision-making. It is because machine learning only shows results, not the whole processes. As artificial intelligence developed and became more common, people wanted the explanation which could provide them the trust on artificial intelligence. This study recognized the necessity and importance of explainable artificial intelligence, XAI, and examined the trends of XAI research by analyzing social networks and analyzing topics with IEEE published from 2004, when the concept of artificial intelligence was defined, to 2022. Through social network analysis, the overall pattern of nodes can be found in a large number of documents and the connection between keywords shows the meaning of the relationship structure, and topic modeling can identify more objective topics by extracting keywords from unstructured data and setting topics. Both analysis methods are suitable for trend analysis. As a result of the analysis, it was found that XAI's application is gradually expanding in various fields as well as machine learning and deep learning.

• Korean Medical Education Review
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• v.18 no.3
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• pp.150-155
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• 2016

Learning objectives for human and society-centered basic medical education to improve physicians' ability to practice in a Korean context were developed by the Korean Association of Medical Colleges in 2015-2016. The task-force committee identified eight domains for medical practitioners: human illness, reflection and self-improvement, patient safety, communication and collaboration, medical ethics, legal issues, social accountability, and professionalism. A total of 172 enabling learning outcomes and 42 terminal learning outcomes were identified by the workshop. The workshop members were representatives from 41 medical schools, the Korean Medical Association, and a scientific group (medical ethics, legal issues, and medical communication). The curriculum for "medical humanity and social medicine" was first published in 2007. The human and society-centered learning objectives that were developed will be revised annually.

• Journal of The Korean Association For Science Education
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• v.16 no.4
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• pp.441-450
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• 1996

Various contexts are involved in the processes of science learning and instruction. In the perspective that the results of science learning and instruction usually depend on the nature of learning task content and context, content effects or context effects have been researched up to now. But, the discrimination between them was very ambiguous. For the clarity of them, it was supposed that science content would be composed of decontextualized knowledges and contexts, which were respectively dichotomized in common and special ones among disciplines of science. Science learning and instruction was discussed in view of interactions between cognitive, learning task, and social-cultural contexts. Especially, it was emphasized that task contexts, as a bridging role among contexts should be constructed considering cognitive and social cultural contexts.

• The Journal of Korean Academic Society of Nursing Education
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• v.14 no.2
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• pp.252-261
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• 2008

Purpose: The purpose of this study was to explore how an educator can empower students by fostering communication, problem-solving, and self-directed learning ability. Method: In order to accomplish this purpose, 136 students who were attending J University and 105 students attending M University participated in the questionnaire. The students were freshman in the nursing or social welfare departments, There were 136 in the control group and 105 in the experimental group. The control group was given an applicable class of project learning. On the other hand, the experimental group was given traditional lessons once a week for 15 weeks. The research instrument used the measuring instruments developed by KEDI for communication and problem-solving and self-directed learning ability. Data was analysed by ANCOVA with SPSS/PC. Result: The results of analysis show that communication, problem-solving, and self-directed learning ability significantly increased in the experimental group. Conclusion: Based on the research finding, project learning has an educational value. Interdisciplinary cooperation project learning is effective for communication, problem-solving, and self-directed learning ability.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.3
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• pp.36-45
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• 2011

An agent in collaborative e-learning has independent function for learners in any circumstance, status and task by the reasonable and general means for social learning. In order to perform it well, communication among agents requires standardized and regular information technology method. This study suggests data model as a communication tool for various agents. Therefore this study shows various agents types for collaborative learning, designation of rule for data model that enable to communicate among agents and data element of agent communication data model. A multi-agent e-learning system using like this standardized data model should able to exchange the message that is needed for communication among agents who can take charge of their independent tasks. This study should contribute to perform collaborative e-learning successfully by the application of communication data model among agents for social learning.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.12 no.5
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• pp.79-87
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• 2017

The previous studies of online entrepreneurship education were conducted only on the effect of education on actual entrepreneurship, but did not analyze the effectiveness of education. In this study, beyond of limits of previous studies, we investigated the effect of social presence on learning expectancy and educational satisfaction. In addition, we examined the influence of learning expectation on the relationship between social presence and educational satisfaction. For the research hypothesis test, we conducted a questionnaires survey on 189 graduate students who taken online courses related to entrepreneurship, hypothesis and questionnaires were made based on the research hypotheses precedent theories. And educational satisfaction was divided into operational satisfaction and content satisfaction. As a results of the analysis using the structural equation model, social presence has a positive effects on learning expectancy. Next, the learning expectancy has a positive effects on the operational satisfaction and the content satisfaction. Finally, when social presence affects operational satisfaction, learning expectation has a complete mediation effects and content satisfaction has a partial mediation effects. The implications of the results of this study were as follows. There was a need for a way to interacted with learners when conducted online entrepreneurial education. When increased the satisfaction level of the learning operation, it is necessary to reduced the burden of learners and raised the expectancy.

• Journal of the Korean Society of Child Welfare
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• no.54
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• pp.79-111
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• 2016

The purpose of this study was to examine the structural models in which early cumulative risk factors affect children's language(indicated by expressive vocabularies) and social development(indicated by peer competence) at age 3 thorough their effects on the home learning environment. To examine the hypothesized models, the data of 1,725 families from the second and the fourth waves of the Panel Study of Korean Children was used. Correlation analysis and structural equation modeling were conducted to test the models. First, the cumulative risk factors at age 1 and 3 were highly correlated, implying the stability of the risk factors over time. The more cumulative risk factors at age 1 predicted the lower level of the home learning environment at age 3, which, in turn, was significantly related to both language and social development at age 3. However, the early cumulative risk factors did not directly influence later developmental outcomes. Moreover, the cumulative risk factors at age 3 were directly related to the child's language development, but neither social development northe home learning environment. In addition, the mediational role of the home learning environment (i.e., cumulative risk factors at age 1${\rightarrow}$home learning environment${\rightarrow}$language and social development) was statistically supported. In conclusion, the early cumulative risk factors in infancy indirectly predicted children's development at age 3 through the home learning environment. The practical implications for the early intervention and support for the families with infants who are experiencing multiple risk factors were discussed.

• Journal of Korea Multimedia Society
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• v.10 no.12
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• pp.1698-1703
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• 2007

The paper focuses on a new 'learning ecology' that is evolving and the challenges that educators must confront. It looks at e-learning as not just another add-on, but a technology that is transforming our educational institutions. How teaching and learning is conceptualized and experienced to generate a determined community of inquiry that integrates social, cognitive, and teaching presence in a manner that will take full advantage of the distinctive assets of e-learning is discussed. Likewise, the possibility of mobile learning is put forward.