• Journal of the Korean Society for information Management
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• v.35 no.4
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• pp.223-236
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• 2018

The purpose of this study is to suggest the concept of data literacy and its detailed competencies based on humanities focused on LIS. To do this, we define the concept of data literacy by comparing and analyzing researches related data literacy, data information literacy, and digital literacy in domestic and foreign. And we design the basic 11 elements of data literacy based on digital humanities concepts. The result of this study is expected to be used as a basic data when design henceforward data literacy framework.

• Journal of the Korean Society for information Management
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• v.37 no.1
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• pp.179-195
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• 2020

As data becomes more important, data literacy has recently emerged as an significant term. The purpose of this study is to design data literacy model based on digital humanities. To attain this end, data literacy model was designed by combining the main contents derived from the digital humanities education program with specific capabilities extracted from research related to data literacy. By applying the data literacy model, which is the result of this study, it will be applicable to the data literacy courses in universities, and I would like to propose a follow-up study to evaluate the effectiveness of data literacy in the future.

• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.469-470
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• 2024

본 논문에서는 DigComp를 분석하여 데이터 리터러시 수준을 분석하고자 하였다. 이를 위해 DigComp의 구성요소인 데이터 리터러시, 소통 및 협업, 디지털 콘텐츠 제작, 보안, 문제해결 중 데이터 리러터시 영역의 세부 요소를 살펴보았다. 데이터 리터러시는 탐색·검색·필터링, 평가, 관리 3가지로 세분되어 있었고, 각각은 수준에 따라 기초, 중급, 고급, 전문가의 4단계로 구분되어 있었다. 그리고 3가지 영역의 수준을 분석하여 각 수준을 대표하는 핵심 단어를 추출하였다. 향후 이를 바탕으로 한 구체적 적용방안에 관한 연구가 이뤄지길 기대한다.

• Proceedings of the Korean Society for Information Management Conference
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• 2015.08a
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• pp.11-15
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• 2015

데이터 사이언스가 경영, 학술, 교육 등의 전 영역에 확산되면서 변화를 이끌어내고 있다. 문헌정보학과 도서관의 입장에서 데이터 사이언스라는 대세를 수용하는 전략에 대해서 데이터 리터러시를 중심으로 살펴보았다. 연구 데이터 리터러시, 통계 데이터 리터러시, 실무 데이터 리터러시의 세 가지로 나누어 살펴본 결과, 데이터 리터러시는 데이터와 관련된 기술과 역량을 강조하는 용어로서 문헌정보학과 도서관 현장에서 데이터 사이언스를 주도적인 입장에서 수용하는 브랜드로 육성시킬 필요가 있다고 판단된다.

• Journal of the Korean Society for Library and Information Science
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• v.57 no.3
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• pp.303-323
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• 2023

The purpose of this study is to introduce this language model in the era of generative AI such as ChatGPT, and to provide direction for data literacy education components in libraries using it. To this end, the following three research questions are proposed. First, the technical features of ChatGPT-like language models are examined, and then, it is argued that data literacy education is necessary for the proper and accurate use of information by users using a service platform based on generative AI technology. Finally, for library data literacy education in the ChatGPT era, it is proposed a data literacy education scheme including seven components such as data understanding, data generation, data collection, data verification, data management, data use and sharing, and data ethics. In conclusion, since generative AI technologies such as ChatGPT are expected to have a significant impact on users' information utilization, libraries should think about the advantages, disadvantages, and problems of these technologies first, and use them as a basis for further improving library information services.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.377-380
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• 2023

본 논문에서는 중등 교육에 적합한 데이터 리터러시 핵심 역량을 도출하기 위해 국내외 중등 교육과정의 내용을 분석하였다. 고등 교육 졸업생들을 대상으로 개발된 기존 데이터 리터러시 역량 프레임워크를 분석 매트릭스로하여 한국, 영국, 호주, 싱가포르, CSTA의 교육과정 내용을 분석한 결과, 중등 교육과정에서 공통적으로 나타나는 역량과 기존 프레임워크에 있으나 중등 교육과정에는 포함되지 않은 역량, 기존 프레임워크에 없지만 중등 교육과정에서 공통적으로 나타나는 내용 등을 확인할 수 있었다.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.33 no.1
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• pp.139-166
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• 2022

Ethical Issues increase when people engage in smart technological systems such as 5G, IoT, Cloud computing services and AI applications. Range of this research is comparison of various literacy concepts and its ethical issues in considering of 5G features and UX. 86 research papers and reports which have been published within the recent 5 years (2017-2022), relating the research subject, are investigated and analyzed. Two results show that various literacies can be grouped into four areas and that some of common issues among those areas as well as unique issues of each area are identified. Based on the literature analysis, an Operational Definition of Ethics-Literacy is presented and the model of ethics-literacy curriculum supporting ethical behavior of 5G information professionals is developed and suggested.

• Journal of The Korean Association of Information Education
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• v.26 no.2
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• pp.141-151
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• 2022

Recently, basic literacy education related to digital literacy and data literacy has been emphasized for students who will live in a rapidly developing future digital society. Accordingly, demand for education to improve big data and data literacy is also increasing in general universities and universities of education as basic knowledge. Therefore, this study designed and applied big data analysis courses for pre-service teachers and analyzed the impact on data literacy. As a result of analyzing the interest and understanding of the input program, it was confirmed that it was an appropriate form for the level of pre-service teachers, and there was a significant improvement in competencies in all areas of 'knowledge', 'skills', and 'values and attitudes' of data literacy. It is hoped that the results of this study will contribute to enhancing the data literacy of students and pre-served teachers by helping with systematic data literacy educational research.

• Journal of the Korean Society for information Management
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• v.40 no.4
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• pp.403-428
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• 2023

This study investigates the development path and intellectual structure of data literacy research, aiming to identify emerging topics in the field. A comprehensive search for data literacy-related articles on the Web of Science reveals that the field is primarily concentrated in Education & Educational Research and Information Science & Library Science, accounting for nearly 60% of the total. Citation network analysis, employing the PageRank algorithm, identifies key papers with high citation impact across various topics. To accurately trace the development path of data literacy research, an enhanced PageRank main path algorithm is developed, which overcomes the limitations of existing methods confined to the Education & Educational Research field. Keyword bibliographic coupling analysis is employed to unravel the intellectual structure of data literacy research. Utilizing the PNNC algorithm, the detailed structure and clusters of the derived keyword bibliographic coupling network are revealed, including two large clusters, one with two smaller clusters and the other with five smaller clusters. The growth index and mean publishing year of each keyword and cluster are measured to pinpoint emerging topics. The analysis highlights the emergence of critical data literacy for social justice in higher education amidst the ongoing pandemic and the rise of AI chatbots. The enhanced PageRank main path algorithm, developed in this study, demonstrates its effectiveness in identifying parallel research streams developing across different fields.

• Journal of The Korean Association of Information Education
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• v.26 no.6
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• pp.553-566
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• 2022

This study collects social data and academic research data from portal sites and RISS, and analyzes TF-IDF, N-Gram, semantic network analysis, and CONCOR analysis to analyze the social awareness and current aspects of 'AI Literacy' and 'AI Convergence Education'. Through this, we tried to understand the social awareness aspect and the current situation, and to suggest implications and directions. In the social data, the collection of 'AI Convergence Education' was more than twice that of 'AI Literacy', indicating that awareness of 'AI Literacy' was relatively low. In 'AI Literacy', the keyword 'human' in social data showed no cluster to which it belonged, indicating a lack of philosophical interest in and awareness of humanities and AI. In addition, the keyword 'Ministry of Education' showed high frequency, importance, and centrality of connection only in the social data of 'AI convergence education', confirming that 'AI convergence education' is closely related to government policy.