• Educational Technology International
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• 제17권1호
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• pp.117-150
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• 2016

The purpose of this study was to develop design guidelines on the learning analytics which can help to promote students' self-regulated learning (SRL) strategies in MOOCs learning environments. First of all, to develop the first draft of design guidelines, relevant literature review and case analysis on current MOOCs platforms such as edX, K-MOOC, Coursera, Khan Academy and FutureLearn were conducted. Then, to validate the design guidelines, expert reviews (validation questionnaires and in-depth interviews) and learner evaluation (in-depth interviews) were conducted. Through the recursive validation, the design guidelines were finalized. Overall, the final version of design guidelines on learning analytics to facilitate SRL strategies was suggested. The final design guidelines consist of 15 items in 10 categories related to the information analyzed based on individual student's learning behaviors and activities on MOOCs environments. Moreover, the results of interview also revealed that the social comparisons, learning progress reports, and personalization might contribute to the improvements of their SRL competences. This study has an implication that MOOCs could offer a higher success or completion rate to students with low SRL skills by taking advantage of the information on learning analytics

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권1호
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• pp.391-406
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• 2015

Social media have emerged as new communication channels between consumers and companies that generate a large volume of unstructured text data. This social media content, which contains consumers' opinions and interests, is recognized as valuable material from which businesses can mine useful information; consequently, many researchers have reported on opinion-mining frameworks, methods, techniques, and tools for business intelligence over various industries. These studies sometimes focused on how to use opinion mining in business fields or emphasized methods of analyzing content to achieve results that are more accurate. They also considered how to visualize the results to ensure easier understanding. However, we found that such approaches are often technically complex and insufficiently user-friendly to help with business decisions and planning. Therefore, in this study we attempt to formulate a more comprehensive and practical methodology to conduct social media opinion mining and apply our methodology to a case study of the oldest instant noodle product in Korea. We also present graphical tools and visualized outputs that include volume and sentiment graphs, time-series graphs, a topic word cloud, a heat map, and a valence tree map with a classification. Our resources are from public-domain social media content such as blogs, forum messages, and news articles that we analyze with natural language processing, statistics, and graphics packages in the freeware R project environment. We believe our methodology and visualization outputs can provide a practical and reliable guide for immediate use, not just in the food industry but other industries as well.

• Journal of applied mathematics & informatics
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• 제41권5호
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• pp.1129-1143
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• 2023

Social media platforms have become an integral part of our daily lives, and they generate vast amounts of data that can be analyzed for various purposes. However, the quality of the data obtained from social media is often questionable due to factors such as noise, bias, and incompleteness. Enhancing data quality is crucial to ensure the reliability and validity of the results obtained from such data. This paper proposes an enhanced decision-making framework based on Business Decision Management Systems (BDMS) that addresses these challenges by incorporating a data quality enhancement component. The framework includes a backtracking method to improve plan failures and risk-taking abilities and a steep optimized strategy to enhance training plan and resource management, all of which contribute to improving the quality of the data. We examine the efficacy of the proposed framework through research data, which provides evidence of its ability to increase the level of effectiveness and performance by enhancing data quality. Additionally, we demonstrate the reliability of the proposed framework through simulation analysis, which includes true positive analysis, performance analysis, error analysis, and accuracy analysis. This research contributes to the field of business intelligence by providing a framework that addresses critical data quality challenges faced by organizations in decision-making environments.

• 한국게임학회 논문지
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• 제12권3호
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• pp.77-86
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• 2012

최근 트위터와 미투데이 등의 마이크로블로그 서비스가 소셜 네트워킹에서 차지하는 비중이 점점 증가하고 있다. 하지만 이러한 마이크로블로그 서비스는 사용자와 지인들 사이의 메시지를 단순히 시간 순으로 나열하여 보여주기 때문에 사용자와 특정 지인과의 관계를 구체적으로 파악하기는 어렵다. 본 논문에서는 마이크로블로그 서비스를 이용하는 사용자와 지인들이 주고 받은 메시지를 정량적, 정성적, 시간적으로 분석하여 사용자와 지인들과의 관계를 직관적으로 파악할 수 있게 하는 소셜 네트워킹 패턴 분석 및 가시화 시스템을 제안한다. 또한 관계의 변화 패턴을 분류하여 마이크로블로그 서비스 사용자의 인간관계를 관리하고 증진시킬 수 있는 도구도 제공한다. 제안 기법은 스마트폰 어플리케이션에 성공적으로 적용되어 마이크로블로그 서비스 사용자의 인간관계의 분석 및 증진을 위한 도구로서 사용될 수 있다.

• International Journal of Computer Science & Network Security
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• 제21권9호
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• pp.261-266
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• 2021

The spread of cloud computing, digital computing, and the popular social media platforms have led to increased growth of data. That growth of data results in what is known as big data (BD), which seen as one of the most strategic resources. The analysis of these BD has allowed generating value from massive raw data that helps in making effective decisions and providing quality of service. With Vision 2030, Saudi Arabia seeks to invest in BD technologies, but many challenges and barriers have led to delays in adopting BD. This research paper aims to search in the state of Big Data Analytics (BDA) in Saudi higher education sector, identify the barriers by reviewing the literature, and then to apply the design-reality gap model to assess these barriers that prevent effective use of big data and highlights priority areas for action to accelerate the application of BD to comply with Vision 2030.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권6호
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• pp.1996-2011
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• 2021

To understand a trend is to explore the intricate process of how something or a particular situation is constantly changing or developing in a certain direction. This exploration is about observing and describing an unknown field of knowledge, not testing theories or models with a preconceived hypothesis. The purpose is to gain knowledge we did not expect and to recognize the associations among the elements that were suspected or not. This generally requires examining a massive amount of data to find information that could be transformed into meaningful knowledge. That is, looking through the lens of big-data analytics with an inductive reasoning approach will help expand our understanding of the complex nature of a trend. The current study explored the trend of well-being in South Korea using big-data analytic techniques to discover hidden search patterns, associative rules, and keyword signals. Thereafter, a theory was developed based on inductive reasoning - namely the hook, upward push, and downward pull to elucidate a holistic picture of how big-data implications alongside social phenomena may have influenced the well-being trend.

• 정보과학회 컴퓨팅의 실제 논문지
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• 제21권12호
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• pp.768-773
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• 2015

사회적 혼란을 야기하는 이벤트는 발생 직후 어떻게 대응하느냐에 따라 소요되는 비용의 편차가 크다. 이에 따라 비정상적인 이벤트를 탐지하고 의미를 파악하는 연구가 많이 진행되고 있다. 또한 예측 분석에 관한 연구도 많이 수행되고 있다. 그러나 대부분의 연구는 이벤트의 전체적인 미래 경향에 대한 수치 결과를 예측할 뿐, 이벤트가 내포하는 의미에 대한 예측 연구는 미비하다. 이에 따라 본 논문에서는 비정상적인 이벤트가 내포하는 토픽의 조합을 통해 미래에 어떠한 일이 발생할 수 있는지에 대한 시각적 예측 분석 방법을 제안한다. 제안하는 방법은 먼저 트윗에서 실시간으로 비정상 이벤트를 탐지한다. 그 다음 과거 유사한 사례를 탐색한 다음 이벤트와 관련된 토픽들을 추출한다. 마지막으로 사용자는 의미 있는 토픽의 조합을 통해 미래에 어떠한 일이 발생할 수 있을지 분석할 수 있다. 실험은 두 가지 상황에 대한 예측 분석을 수행하였으며, 실험 결과 본 논문에서 제안한 방법의 타당성을 입증하였다.

• 한국정보시스템학회지:정보시스템연구
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• 제26권4호
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• pp.327-353
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• 2017

Purpose Social media such as social network services, online forums, and customer reviews have produced a plethora amount of information online. Yet, the information deluge has created both opportunities and challenges at the same time. This research particularly focuses on the challenges in order to discover and track the service defects over time derived by mining publicly available online customer reviews. Design/methodology/approach Synthesizing the streams of research from text analytics, we apply two stages of methods of sentiment analysis and structural topic model incorporating meta-information buried in review texts into the topics. Findings As a result, our study reveals that the research framework effectively leverages textual information to detect, prioritize, and categorize service defects by considering the moving trend over time. Our approach also highlights several implications theoretically and practically of how methods in computational linguistics can offer enriched insights by leveraging the online medium.

• 디지털산업정보학회논문지
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• 제16권2호
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• pp.105-115
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• 2020

This study examines the influence of the betweenness centrality on tertius gaudens orientation, relationship commitment, and individual learning performance within the university environment. The betweenness centrality explored the antecedent factor of tertius gaudens orientation. The relationship commitment explored the consequence factor of tertius gaudens orientation, and the learning performance explored the consequence factor of the relationship commitment. This survey was carried out by university students. Data were obtained from 74 respondents who have been studying tourism data analytics at one of the leading universities, in Seoul, Korea. In order to validate the research model, social network analysis tool, UCINET 6.689, and a structural equation modeling tool, SmartPLS 3.3.2, were used. The empirical result showed that all antecedent factors (betweenness centrality position, tertius gaudens orientation, and relationship commitment) of the learning performance were significant. In conclusion, this study discusses the research findings and implications. Then the limitations and future directions of the study were suggested.

• 한국콘텐츠학회논문지
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• 제15권9호
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• pp.652-661
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• 2015

연구의 목적은 학습자의 사회비교동기 유형에 따라 이러닝 참여도 동기부여자인 EngageGram이 학습자들의 이러닝 참여도에 미치는 영향에 차이가 있는지를 분석하는 것이다. 연구에 참여한 학습자들은 A대학교 '창의적 사고' 교과목을 수강한 144명(남: 106명, 여: 38명)이다. 학습자들의 사회비교동기는 사회비교동기 척도를 활용하는 방법과 학습자들이 이러닝 학습상황에서 EngageGram을 보고 든 느낌이나 생각을 적도록 한 의견을 분석함으로써 사회비교동기 유형을 구분하였다. 연구결과, 사회비교동기 척도를 활용한 경우, 학습자들의 사회비교동기 수준과 이러닝 참여도간 통계적으로 유의미한 상관관계가 없는 것으로 확인되었다. 그러나 이러닝 학습맥락에서 수집한 학습자들의 의견을 분석함으로써 도출한 사회비교유형에 따른 이러닝 참여도에는 통계적으로 유의미한 차이가 있는 것으로 나타났다. 학습자들은 학습상황에서 대체로 자기보다 참여도가 높은 학습자들을 비교대상으로 선정함으로써 참여동기가 촉진되는 것으로 확인되었다. 이 연구는 학습자의 특성을 고려한 학습분석연구 분야에 유의미한 시사점을 제공하리라 기대된다.