2026, Vol.57, No.2

Journal of Korean Library and Information Science Society 2024 KCI Impact Factor : 0.91

pISSN : 2466-2542 / eISSN : 3140-2291
https://journal.kci.go.kr/liss

The purpose of this study is to develop an AI-based Information and Media Literacy (AI-IML) model. To this end, the MIL model, the Big6 model, and CT model were analyzed, and the Big6 model was modified into an AI-based Big6 model that incorporates AI literacy. Subsequently, the MIL model, the AI-based Big6 model, and the CT model were mapped, and an AI-IML model was developed by structuring MIL model as the goal layer that presents goals, the AI-based Big6 model as the behavior layer that presents behavioral standards, and CT model as the judgment layer that presents cognitive and metacognitive standards. To verify the practical applicability and validity of the developed AI-IML model, classes were conducted at two high schools. The results of the classes confirmed that the AI-IML, composed of three layers, is applicable to classes that reflect AI literacy. This study is meaningful in that AI literacy, an important competency for information production, was integrated with Big6, an information literacy model, MIL, a model with media literacy, and CT, a cognitive model.

This study aims to establish the conceptual structure of AI literacy required of librarians in AI-based library environments and to propose directions for designing educational programs that reflect this structure. To this end, the study conducts a literature-based comparative analysis of the ACRL AI Literacy Framework and the AI literacy framework for librarians proposed by Tang and Ma, and reviews AI education programs for librarians offered by Choice/ALA and the National Library of Korea. The analysis indicates that librarians’ AI literacy can be conceptualized around a common competency structure consisting of knowledge and understanding, analysis and evaluation, and use and application, grounded in ways of thinking and ethical considerations. In addition, it is necessary to integrate practical application competencies linked to librarians’ professional duties, including collection development, information services, user services, technical support, and strategic management. Furthermore, AI education for librarians should be designed around several key directions: adopting a flipped learning model that combines common e-learning with practice-based in-person training; treating ethics and policy as independent educational components; introducing educational content focused on analysis, evaluation, and task-specific use and application; establishing a progressive learning structure that reflects learners’ levels and job characteristics; improving access to education; and supporting continuous professional development through communities of practice.

This study reconstructs the research lifecycle based on the actual research practices of science and technology researchers and analyzes their information needs and data utilization characteristics at each stage. In-depth interviews were conducted with experienced researchers, and the data were analyzed using thematic analysis. The results identified eight stages of the research lifecycle: idea generation, research funding acquisition, literature review, research planning, research execution, research output creation, data dissemination, and evaluation. Researchers experienced difficulties in information discovery and utilization due to fragmented information and data resources. They also actively used generative AI for literature exploration, research planning, and manuscript writing, while emphasizing the need for reliable and standardized AI-ready data. The findings also highlighted the importance of an integrated research environment that enables the combined use of scholarly articles, patents, and research data. They revealed growing demand for data-linked research support services. This study analyzes information needs across the research lifecycle and suggests directions for AI-ready data and data-driven research support services in the era of generative AI. It provides a foundation for developing data-linked research support services and AI-based scholarly information services in Korea.