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Librarians are expected to be expert searchers, and developing information literacy skills to navigate the vast world of information is a focus of most library and information science (LIS) programs. It is important to understand the information literacy and behaviors of LIS students to see if they are employing the skills they will need to assist and educate their future patrons, yet there is relatively little research into the information literacy and behaviors of librarians and library students. Using a survey on information behaviors, this study addresses this gap in the literature by examining how LIS students in 18 countries search for, evaluate, and use information in various contexts, and on whom they rely for help. The results of this study demonstrate library science students' information literacy skills within an international context. Faculty in LIS programs will be interested to see how their students approach information problems, and might use this understanding to develop or strengthen courses and inform curricular decisions.

INTRODUCTION: Artificial intelligence (AI) is a novel type of library technology. AI technologies and the needs of data librarians are hybrid and symbiotic, because academic libraries must insert AI technologies into their information and data services. Library services need AI to interpret the context of big data. OBJECTIVES: In this context, we explore the use of the OpenAI Codex, a deep learning model trained on Python code from repositories, to generate code scripts for data librarians. This investigation examines the practices, models, and methodologies for obtaining code script insights from complex code environments linked to AI GPT technologies. METHODS: The proposed AI-powered method aims to assist data librarians in creating code scripts using Python libraries and plugins such as the integrated development environment PyCharm, with additional support from the Machinet AI and Bito AI plugins. The process involves collaboration between the data librarian and the AI agent, with the librarian providing a natural language description of the programming problem and the OpenAI Codex generating the solution code in Python. RESULTS: Five specific web-scraping problems are presented. The scripts demonstrate how to extract data, calculate metrics, and write the results to files. CONCLUSION: Overall, this study highlights the application of AI in assisting data librarians with code script creation for web scraping tasks. AI may be a valuable resource for data librarians dealing with big data challenges on the Web. The possibility of creating Python code with AI is of great value, as AI technologies can help data librarians work with various types of data sources. The Python code in Data Science web scraping projects uses a machine-learning model that can generate human-like code to help create and improve the library service for extracting data from a web collection. The ability of nonprogramming data librarians to use AI technologies facilitates their interactions with all types and data sources. The Python programming language has artificial intelligence modules, packages, and plugins such as the OpenAI Codex, which serialises automation and navigation in web browsers to simulate human behaviour on pages by entering passwords, selecting captcha options, collecting data, and creating different collections of datasets to be viewed. [ABSTRACT FROM AUTHOR]

The Visegrad group comprises four countries: the Czech Republic, Hungary, Poland and Slovakia. The literature on information literacy, mainly in the respective national languages, and the development of initiatives are presented in this paper. The situation in each country is discussed separately, followed by a short discussion of similarities and differences. Approaches vary in details, but there is a common background and shared roots. The use of terminology is similar in all countries, because they are the national (native language), translated variations of internationally accepted English terms. Because of the linguistic affinity, Czech and Slovak terminology usage is even closer. Though the context behind the terminology is the same in all languages, there are some differences in the interpretations at the conceptual level, in all languages. Related national and regional initiatives are enumerated and analyzed.

After providing background to Continuing Professional Education (CPE) of librarians in Hungary, this article outlines the content of a course that seeks to make Hungarian librarians familiar with free Internet resources that are usable for library technical services and reference. One of the most important topics covered in the course is the question of finding information on the World Wide Web. The importance of virtual reference and details about Libinfo, the major Hungarian virtual reference desk service are discussed. The author also gives details about some of the Hungarian and international resources used for the course. (Contains 3 figures.)