2025, Vol.36, No.4

While the 2022 Revised Curriculum explicitly mandates knowledge information processing and collaborative communication as core competencies, the PISA 2022 results corroborate that Korean students’ capabilities in critical information evaluation remain stagnant. This discrepancy stems from structural limitations where current information literacy education remains at the level of acquiring isolated information, failing to provide learners with opportunities to contextually connect knowledge and reconstruct it collaboratively. To address this challenge, this study proposes ‘Collaborative Knowledge Organization (CKO)’ as a practical alternative and aims to devise a strategic framework for its implementation in school settings.The research methodology employed a parallel approach of literature review and qualitative research (FGI). The literature review established the theoretical consistency of CKO based on social constructivism and metacognition theories, while the empirical study involved in-depth analysis of the field context through Focus Group Interviews (FGI) with nine experts, including teacher librarians, subject teachers, and education specialists. The analysis identified multifaceted structural constraints, including one-off operations, insufficient linkage with evaluation, and the absence of collaborative systems. Based on these findings, the study structured the key mechanisms derived from FGI into ‘Visualization,’ ‘Cyclic Interaction,’ and ‘Collaborative Refinement,’ designing a three-layered CKO execution framework comprising ‘Foundation,’ ‘Process,’ and ‘Goal.’ This study holds significance in redefining CKO not as an individual teacher’s competence but as an institutional collaborative mechanism within the school curriculum. Ultimately, this framework presents concrete execution criteria to complement the realistic constraints of information literacy education and to drive its practical and institutional settlement.

A Study on Teacher Librarians’ Perceptions of EduTech Utilization in School Libraries

Mi Yeong Choi , Hyo Jung Sim | 2025, 36(4) | pp.227~250 | number of Cited : 0

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This study analyzed the actual features of EduTech-integrated instruction implemented in school libraries and the perceptions of teacher librarians through in-depth interviews amid accelerated digital transformation in education. Drawing on the directions set by the 2022 Revised National Curriculum and the Fourth Comprehensive Plan for the Promotion of teacher Libraries, the study focused on teacher librarians’ motivations and rationales for adopting EduTech, their instructional design approaches and implementation strategies, and the changes observed in students’ learning processes—participation, use of digital literacy, production of creative outcomes and collaborative activities. The participants were five middle and high teacher teacher-librarians selected through purposive sampling on the basis of their experience in conducting EduTech-integrated lessons and their instructional design competence. Analysis of the interviews showed that the teacher-librarians decided to introduce EduTech through the interplay of policy and curriculum requirements, school organizational conditions, and their individual professional expertise, and they restructured their lessons by applying an instructional design that aligned learning objectives, tool selection, learning activities, assessment, and feedback. Students’ engagement in class, practical application of digital literacy, and ability to collaboratively produce creative products improved, whereas a shortage of devices, unstable Wi-Fi connectivity, and disparities in students’ information technology skills constrained the effectiveness of the lessons. The teacher-librarians reconceptualized their role from providers of resources to instructional designers and digital literacy educators and proposed the need for increased financial and institutional support and regular professional development programs for teachers to sustain such practices.

Extending the ACRL Framework for Information Literacy in the Age of AI

Kyounghoon Kim , Eun Youp Rha | 2025, 36(4) | pp.251~271 | number of Cited : 0

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A Study on Analysis of Small Libraries Research Trends in Korea: Using by Text-Network Analysis and Topic Modeling

Hyunsook Kim | 2025, 36(4) | pp.273~302 | number of Cited : 0

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A Comparative Study of Automatic Bibliographic Metadata Generation Performance: Focusing on Domestic and International Large Language Models (LLMs)

SeonWook Kim

, Hyekyung Lee | 2025, 36(4) | pp.303~331 | number of Cited : 0

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This study aims to examine the feasibility of using domestic sovereign AI models and global large language models (LLMs) for automated creation of library metadata by comparing their performance in MARC record generation. To this end, six generative AI models (GPT, Gemini, Grok, HyperCLOVA, EXAONE, and A.X) were used to generate MARC records for 40 domestic and foreign monographs, and their field-level performance was evaluated using three criteria: completeness, correctness, and rule compliance. The analysis showed, first, that the three global LLMs (GPT, Gemini, Grok) generally outperformed domestic sovereign AI models, with fewer missing fields and more stable handling of formal elements such as indicators and codes. However, their performance tended to decline when the cataloguing target shifted from English-language to Korean books, as errors increased in field configuration and statement of responsibility. Second, the domestic sovereign AI models (HyperCLOVA, EXAONE, A.X) exhibited relatively low overall performance in both MARC21 and KORMARC, and did not show clear performance gains even for Korean books. Third, at the field level, most models generated relatively stable results for title and statement of responsibility (245), whereas rule-dependent fields such as series statements (490/830) and the choice of main entry showed large performance gaps between models and revealed structural misunderstandings of cataloguing rules for example, mechanically transferring MARC21 practices for series treatment to KORMARC. These findings suggest that, at present, generative AI should be introduced into library metadata workflows primarily as an assistive tool for generating draft records and supporting error detection and correction, rather than as a fully automated cataloguing system. The results also indicate that, in order to ensure stable performance of domestic sovereign AI models, systematic training on Korean bibliographic data, including KORMARC records, is required. Furthermore, the careful selection and curation of training data emerges as a key task in building sovereign AI systems for library applications.

A Study on Factors Influencing Reading Attitudes: Focusing on Reading Activities and Reading Efficacy by Age Group

Ji-Hyun Kim | 2025, 36(4) | pp.333~349 | number of Cited : 0

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A Study on the Legal Institutional Improvement Measures for Standards Governing the Establishment of Archives at Private Universities

Hyunjung Kim , Sungjung Bae | 2025, 36(4) | pp.351~376 | number of Cited : 0

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Analysis of International Research Trends on Older Adults’ Digital Literacy

Sunjeong Kim , Jisu Lee | 2025, 36(4) | pp.377~402 | number of Cited : 0

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From Smart Cities to the Era of Public AI: A Study on the Expansion of Public Library Services

Ji Hei Kang | 2025, 36(4) | pp.403~428 | number of Cited : 0

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KJCKorea
Journal Central

Journal of the Korean Biblia Society for Library and Information Science 2024 KCI Impact Factor : 1.0

2025, Vol.36, No.4