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Introduction Scientific Initiation (SI) is an educational activity that allows students to begin their scientific training and research under the guidance of an experienced researcher. While several studies have examined students’ perceptions of SI, research on the perspective of researchers working in this field is currently lacking. Thus, this study’s aim is to describe the protocol design for conducting a systematic review. At the same time, the review aims also to identify factors influencing the work of researchers in SI and explore the motivations leading researchers to engage in research projects within institutions and their respective impacts. Method and analyses Literature search will be done using the bibliographic databases, including Academic Search Premier, APA PsycNet, CINAHL Plus, ERIC, SocINDEX, Scopus, and Web of Science. The search strategy was guided by the PICo framework (Population, phenomenon of Interest, and Context). The preparation and development of this protocol following guidelines were employed: Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Protocols 2015 (PRISMA-P 2015), Peer Review of Electronic Search Strategies 2015 (PRESS 2015), and PRISMA-Search (PRISMA-S). Original, peer-reviewed articles that examine the factors related to the work of researchers in SI will be included without any language or publication date restrictions. Qualitative, quantitative, and mixed-methods studies will be screened by two independent researchers. The included studies will be analyzed to identify factors, policies, and their impacts obtained analytically. Findings will be objectively categorized and synthetically represented through figures, diagrams, and graphic models. The risk of bias will be assessed using the Critical Appraisal Skills Program (CASP) and the Downs and Black checklists. A third senior reviewer will resolve any discrepancies. Discussion We aim to understand the factors that drive researchers to engage in SI research through the dissemination of the findings of this systematic review. This may aid the development of institutional strategies and actions that can support the enhancement of SI programs and encourage greater researcher participation.

The impact of Artificial Intelligence (AI) is visible in both the workplace and in education. The progress in AI usage brings about changes and new opportunities for higher education as a whole, across various professional domains. The implications of AI's impact pose a challenge for higher education institutions because students need to be prepared for professional careers, taking into account both the opportunities and offerings created by AI. The study and daily life with AI are widely discussed topics in various sectors, including education. The aim of the research is to provide an overview of the use of AI tools in higher education, particularly in fields like engineering and design, and to analyze the level of user readiness for their application. Research methods include theoretical aspects such as literature review and analysis of internet resources, as well as empirical methods like focus group discussions and analysis of expert interview data. The research is based on 44 students, 4 lecturers in the field of Information and Communication Technology (ICT), and 1 representative from a company working with AI and Machine Learning (ML). The research period is in the autumn of 2023. The research results offer an overview of existing tools and demonstrate awareness of the impact and application possibilities of AI in studies, as well as the current level of user readiness for using AI tools. They also highlight potential research directions for integrating AI capabilities with the study process to assist teachers and students in understanding the latest AI opportunities, promoting preparedness, and considering AI challenges in the future.

The general implications of AI for libraries are much discussed in library literature. But while this discussion takes place at the library-wide level, there are also important implications for subject librarians due to the specific uses of AI in different professions and areas of study. These are often overlooked as these specializations tend to publish in subject-specific journals. This article aims to address this research gap by providing a comparison and thematic analysis of this literature. Subject-specific library journals in the areas of law, health sciences, business, and humanities and social sciences were searched to identify relevant journal articles that discussed AI. 131 articles were identified and tagged with at least one category that reflected the nature of the discussion around AI. The following analysis showed that literature related to law had the greatest number of articles by far, though the publishing activity in all disciplines has increased significantly in the last 10 years. This article explores these trends to gain a more comprehensive understanding of the implications for subject-specific library work.