• 제목/요약/키워드: Social Media Learning

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Design and Implementation of Electronic Text Books in order to Utilize Regional Text Books for Social Studies (사회과 지역교과서 활용을 위한 전자교과서의 설계 및 구현)

  • Kang, Oh-Han;Park, Hui-Seong
    • The Journal of Korean Association of Computer Education
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    • v.9 no.1
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    • pp.19-28
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    • 2006
  • In this paper, we have developed electronic textbooks for social studies centering on contents of a public educational process so that primary schools can use them as a text book. Also, we conducted a survey to find out how teachers perceived electronic textbooks in respect to site accessibility and utility, instructional design, progress of lesson, validity and accuracy of learning content, interface design, and web-based multimedia. In this paper, we presented a new model for electronic textbooks development, which is expected to be useful in developing electronic textbooks as a main text book, unlike other existing models. We applied the navigation utilizing book metaphors to the user interface, on the basis of the results from the analysis of the existing electronic textbooks. In addition, we provided affluent multi-media materials as well as hyperlink, a strong point of on-lines. Experimental results show that the academic achievement was high in knowledge-understanding areas and functional areas in the perspective of academic achievements of the learners.

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Effective Learning Tasks and Activities to Improve EFL Listening Comprehension

  • Im, Byung-Bin
    • English Language & Literature Teaching
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    • no.6
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    • pp.1-24
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    • 2000
  • Listening comprehension is an integrative and creative process of interaction through which listeners receive speakers' production of linguistic or non-linguistic knowledge. Compared with reading comprehension, it may arouse difficulties and thus impose more burdens on foreign learners. The Audio-Lingual Method focused primarily on speaking. Mimicry, repetition, rote memory, and transformation drills actually interfered with listening comprehension. So learners lost interest and were not highly motivated. Improving listening comprehension requires continual attentiveness and interest. Listening skill can be extended systematically only when students are frequently exposed to a wide range of listening materials with an affective, cultural, social, and psycholinguistic approach. Therefore, teachers should help students learn how to comprehend intactly the overall meaning of intended messages. The literature on teaching listening skill suggests various useful activities: TPR, dictation, role playing, singing, picture recognition, completion, prediction, seeking specific information, summarizing, labeling, humor, jokes, cartoons, media, and so on. Practical classroom teaching necessitates a systematic procedure in which students should take part in meaningful tasks/activities. In addition to this, learners must practice listening comprehension trough a self-study process.

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Automated Fact Checking Model Using Efficient Transfomer (효율적인 트랜스포머를 이용한 팩트체크 자동화 모델)

  • Yun, Hee Seung;Jung, Jason J.
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.9
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    • pp.1275-1278
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    • 2021
  • Nowadays, fake news from newspapers and social media is a serious issue in news credibility. Some of machine learning methods (such as LSTM, logistic regression, and Transformer) has been applied for fact checking. In this paper, we present Transformer-based fact checking model which improves computational efficiency. Locality Sensitive Hashing (LSH) is employed to efficiently compute attention value so that it can reduce the computation time. With LSH, model can group semantically similar words, and compute attention value within the group. The performance of proposed model is 75% for accuracy, 42.9% and 75% for Fl micro score and F1 macro score, respectively.

Design and Implementation of a Cosmetics Recommendation System Based on Machine Learning in Social Media Environments (소셜 미디어 환경에서 기계 학습을 활용한 화장품 추천 시스템의 설계 및 구현)

  • Shin, Haeran;Lim, Yujung;Hong, Yujin;Lim, Jongtae;Park, Jaeyeol;Lee, Hyeonbyeong;Shin, Bokyoung;Bok, Kyoungsoo;Yoo, Jaesoo
    • Proceedings of the Korea Contents Association Conference
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    • 2019.05a
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    • pp.289-290
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    • 2019
  • 최근 뷰티에 대한 관심이 증가함으로써 화장품 관련 정보가 대량으로 발생하였다. 사용자는 선택적으로 정보를 얻고자 하기 때문에 사용자 맞춤형 추천 서비스가 부각되고 있다. 본 논문에서는 소셜 미디어 환경에서 기계 학습을 활용한 화장품 추천 시스템을 설계하고 구현한다.

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Misinformation Detection and Rectification Based on QA System and Text Similarity with COVID-19

  • Insup Lim;Namjae Cho
    • Journal of Information Technology Applications and Management
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    • v.28 no.5
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    • pp.41-50
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    • 2021
  • As COVID-19 spread widely, and rapidly, the number of misinformation is also increasing, which WHO has referred to this phenomenon as "Infodemic". The purpose of this research is to develop detection and rectification of COVID-19 misinformation based on Open-domain QA system and text similarity. 9 testing conditions were used in this model. For open-domain QA system, 6 conditions were applied using three different types of dataset types, scientific, social media, and news, both datasets, and two different methods of choosing the answer, choosing the top answer generated from the QA system and voting from the top three answers generated from QA system. The other 3 conditions were the Closed-Domain QA system with different dataset types. The best results from the testing model were 76% using all datasets with voting from the top 3 answers outperforming by 16% from the closed-domain model.

U-Net-based Recommender Systems for Political Election System using Collaborative Filtering Algorithms

  • Nidhi Asthana;Haewon Byeon
    • Journal of information and communication convergence engineering
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    • v.22 no.1
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    • pp.7-13
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    • 2024
  • User preferences and ratings may be anticipated by recommendation systems, which are widely used in social networking, online shopping, healthcare, and even energy efficiency. Constructing trustworthy recommender systems for various applications, requires the analysis and mining of vast quantities of user data, including demographics. This study focuses on holding elections with vague voter and candidate preferences. Collaborative user ratings are used by filtering algorithms to provide suggestions. To avoid information overload, consumers are directed towards items that they are more likely to prefer based on the profile data used by recommender systems. Better interactions between governments, residents, and businesses may result from studies on recommender systems that facilitate the use of e-government services. To broaden people's access to the democratic process, the concept of "e-democracy" applies new media technologies. This study provides a framework for an electronic voting advisory system that uses machine learning.

Strategies for Revitalizing E-Learning Through Investigating the Characteristics of E-Learning and the Needs of Distance Learners in the Domestic Universities in Korea (국내 대학 e-러닝의 운영 특징 및 수강자 요구 조사를 통한 활성화 방안)

  • Min, Kyung-Bae;Shin, Myoung-Hee;Yu, Tae-Ho;Kwak, Sun-Hye
    • The Journal of the Korea Contents Association
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    • v.14 no.1
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    • pp.30-39
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    • 2014
  • The purpose of this study is to suggest the feasible strategies to vitalize e-learning through investigating the characteristics of e-learning and the evaluations of distance learners on online courses in the domestic universities in Korea. First, in order to accomplish this, 10 Universities and 17 Cyber Universities were selected to explore their characteristics and main projects of e-learning for the administration level investigation. Secondly, content analysis of the bulletin board systems(BBS) and in-depth interviews on distance learners in Cyber Universities were conducted for the user level investigation. The results revealed that Universities in Korea were focused on establishing mobile or smart campuses, diversifying online educational contents, enhancing online interactive systems, and educating e-learning system and smart device utilization. However, distance learners reported that mobile e-learning lacked stability when taking online courses despite its convenience for purpose of academic administration. In addition, distance learners requested the social application workshops to improve on their learning experience as well as the interactions among peers. Therefore, it is important to focus more on how to establish the education-oriented e-learning environment rather than how to implement the administrative projects to animate e-learning in the domestic universities in Korea.

Big Five Personality in Discriminating the Groups by the Level of Social Sims (심리학적 도구 '5요인 성격 특성'에 의한 소셜 게임 연구: <심즈 소셜> 게임의 분석사례를 중심으로)

  • Lee, Dong-Yeop
    • Cartoon and Animation Studies
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    • s.29
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    • pp.129-149
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    • 2012
  • The purpose of this study was to investigate the clustering and Big Five Personality domains in discriminating groups by level of school-related adjustment, as experienced by Social Sims game users. Social Games are based on web that has simple rules to play in fictional time and space background. This paper is to analyze the relationships between social networks and user behaviors through the social games . In general, characteristics of social games are simple, fun and easy to play, popular to the public, and based on personal connections in reality. These features of social games make themselves different from video games with one player or MMORPG with many unspecific players. Especially Social Game show a noticeable characteristic related to social learning. The object of this research is to provide a possibility that game that its social perspective can be strengthened in social game environment and analyze whether it actually influences on problem solving of real life problems, therefore suggesting its direction of alternative play means and positive simulation game. Data was collected by administering 4 questionnaires (the short version of BFI, Satisfaction with life, Career Decision-.Making Self-.Efficacy, Depression) to the participants who were 20 people in Seoul and Daejeon. For the purposes of the data analysis, both Stepwise Discriminant analysis and Cluster analysis was employed. Neuroticism, Openness, Conscientiousness within the Big Five Personality domains were seen to be significant variables when it came to discriminating the groups. These findings indicated that the short version of the BFI may be useful in understanding for game user behaviors When it comes to cultural research, digital game takes up a significant role. We can see that from the fact that game, which has only been considered as a leisure activity or commercial means, is being actively research for its methodological, social role and function. Among digital game's several meanings, one of the most noticeable ones is the research on its critical, social participating function. According to Jame Paul gee, the most important merit of game is 'projected identity'. This means that experiences from various perspectives is possible.[1] In his recent autobiography , he described gamer as an active problem solver. In addition, Gonzalo Francesca also suggested an alternative game developing method through 'game that conveys critical messages by strengthening critical reasons'. [2] They all provided evidences showing game can be a strong academic tool. Not only does a genre called social game exist in the field of media and Social Network Game, but there are also some efforts to positively evaluate its value Through these kinds of researches, we can study how game can give positive influence along with the change in its general perception, which would eventually lead to spreading healthy game culture and enabling fresh life experience. This would better bring out the educative side of the game and become a social communicative tool. The object of this game is to provide a possibility that the social aspect can be strengthened within the game environment and analyze whether it actually influences the problem solving of real life problems. Therefore suggesting it's direction of alternative play means positive game simulation.

Research Trends Investigation Using Text Mining Techniques: Focusing on Social Network Services (텍스트마이닝을 활용한 연구동향 분석: 소셜네트워크서비스를 중심으로)

  • Yoon, Hyejin;Kim, Chang-Sik;Kwahk, Kee-Young
    • Journal of Digital Contents Society
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    • v.19 no.3
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    • pp.513-519
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    • 2018
  • The objective of this study was to examine the trends on social network services. The abstracts of 308 articles were extracted from web of science database published between 1994 and 2016. Time series analysis and topic modeling of text mining were implemented. The topic modeling results showed that the research topics were mainly 20 topics: trust, support, satisfaction model, organization governance, mobile system, internet marketing, college student effect, opinion diffusion, customer, information privacy, health care, web collaboration, method, learning effectiveness, knowledge, individual theory, child support, algorithm, media participation, and context system. The time series regression results indicated that trust, support satisfaction model, and remains of the topics were hot topics. This study also provided suggestions for future research.

Big data mining for natural disaster analysis (자연재해 분석을 위한 빅데이터 마이닝 기술)

  • Kim, Young-Min;Hwang, Mi-Nyeong;Kim, Taehong;Jeong, Chang-Hoo;Jeong, Do-Heon
    • Journal of the Korean Data and Information Science Society
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    • v.26 no.5
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    • pp.1105-1115
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    • 2015
  • Big data analysis for disaster have been recently started especially to text data such as social media. Social data usually supports for the final two stages of disaster management, which consists of four stages: prevention, preparation, response and recovery. Otherwise, big data analysis for meteorologic data can contribute to the prevention and preparation. This motivated us to review big data technologies dealing with non-text data rather than text in natural disaster area. To this end, we first explain the main keywords, big data, data mining and machine learning in sec. 2. Then we introduce the state-of-the-art machine learning techniques in meteorology-related field sec. 3. We show how the traditional machine learning techniques have been adapted for climatic data by taking into account the domain specificity. The application of these techniques in natural disaster response are then introduced (sec. 4), and we finally conclude with several future research directions.