This study investigates the relationship between artificial intelligence (AI) literacy and research skills among university students in Vietnam, within the context of digital transformation and the rapid development of artificial intelligence (AI). The study surveyed 465 students across different academic years and disciplines. Results indicate that both AI literacy and research skills are at a moderately good level. The dimensions of “AI application” and “AI ethics” were highly rated, whereas “AI creativity” was found to be limited. Correlation and regression analyses revealed a statistically significant positive relationship between AI literacy and research skills, particularly in the dimension of “AI application.” The study recommends integrating AI into educational curricula, enhancing creative capacities, and strengthening the role of academic libraries in supporting students’ research skill development.

This study presents a proof-of-concept examination of how generative artificial intelligence tools, text-to-speech, text-to-image and text-to-video platforms, interpret translated Ao Naga oral traditions. Using a small set of folk songs and narrative descriptions, the study evaluates the cultural accuracy, semantic coherence and representational fidelity of artificial-intelligence-generated outputs. The findings reveal both the potential of multimodal artificial intelligence technologies for enhancing access to Indigenous cultural materials and their significant limitations, including mispronunciation, cultural flattening and stereotypical visual representations. These outcomes align with broader concerns about digital colonialism and the structural biases embedded in mainstream artificial intelligence training data sets. As the study does not include community participation, the results should be viewed as preliminary technical observations rather than culturally validated interpretations. The work establishes a baseline for future participatory research involving Ao knowledge-holders and highlights the need for culturally grounded and ethically informed approaches to artificial intelligence use in Indigenous heritage contexts.

The IFLA–UNESCO Public Library Manifesto (2022) identifies 11 key missions that ‘should be at the core of public library services’. The mission, vision and purpose statements of a sample of 50 public library networks in Australia were analysed to gauge the extent to which they reflect these 11 key missions. It was found that the public library mission statements typically only touched on one of the Manifesto 's missions, most of which were covered by few, if any, of the statements. The analysis was repeated for a smaller sample of the networks’ strategy documents. Although these touched on more of the key missions, typically it was still only about a third of them. The ways in which each of the Manifesto 's missions was covered, or not covered, are detailed, and possible explanations for the lack of coverage discussed.

This study aims to assess the criteria employed by researchers at Tanzanian universities to identify predatory publishers as part of their efforts to maintain academic integrity. Specifically, the study seeks to analyze the criteria researchers used to detect predatory publishers and examine the resources they rely on to avoid them. A mixed-methods approach involving 201 researchers from the University of Dodoma (131) and Sokoine University of Agriculture (70) explored how participants of varied educational levels use criteria and resources to avoid predatory publishers. The study reveals moderate utilization of key criteria such as editorial board transparency, with 47.8 and 33.8% of researchers identifying it as a marker of predatory publishers. However, the low usage of formal tools like Cabell's List (10%) underscores limited institutional support and guidance for ethical publishing. This study offers practical insights on academic integrity, emphasizing institutional roles in promoting ethical publishing and guiding policy in Tanzanian and other developing contexts.

Library professionals and library researchers use surveys for data collection from human subjects, involving a research methods skill set. However, creating quality surveys can be challenging, involving close attention to design and revision through validation processes. When survey design errors are not detected prior to data collection, the survey data is unreliable. Generative artificial intelligence tools could potentially assist library professionals and researchers with survey design error detection to enhance the quality of the data collected. This research tested the performance of five generative artificial intelligence tools in detecting two common survey question errors: double-barrelled and acronym-dependent questions. While the generative artificial intelligence tools were typically able to detect acronym-dependent questions, they underperformed in the detection of double-barrelled questions. Even the subsequent provision of explicit training on double-barrelled questions did not lead to full accuracy in detection across the generative artificial intelligence tools. Generative artificial intelligence tools cannot be relied on for this aspect of survey quality control at this stage of their evolution.

The work explores transformation of services of Ukrainian public libraries in response to the full-scale military invasion of Ukraine. It focuses on the role of libraries as vital community centers that offer shelter, humanitarian help, counseling and health services, and as entities fighting misinformation and documenting war crimes. The work reinforces librarianship's significance as a social service profession.

This study explores the opportunities and challenges of integrating robotics technologies into science-hub libraries in Zanzibar, focusing on three hubs located on Unguja Island. The study population included staff working in the hubs and stakeholders dealing with robotics technologies in the country. A case study research design with a qualitative research approach was employed to collect, analyze, and interpret the data. Qualitative data was gathered through focus group discussions to gauge the respondents’ perceptions and experiences regarding educational robotics technologies in the hub settings. The findings highlight promising opportunities, including government support through infrastructure investments; grants for science, technology, engineering, and mathematics education; a competence-based curriculum; and access to professional development such as online courses. However, key challenges persist, including limited robotics infrastructure, insufficient librarian training, and financial constraints. To address these issues, the study recommends securing long-term funding, advocating for the inclusion of robotics in Zanzibar's education curriculum, and introducing affordable mobile robotics kits.

This study examined the influence of demographic characteristics and technological skills on students’ perceived search self-efficacy and their actual search performance. A printed questionnaire was used to collect data on students’ demographic backgrounds and technological skills, search self-efficacy, and search performance on a set of task-based questions. Descriptive statistics were used to analyze the demographic data and technological skills, self-efficacy levels, and task performance scores, while inferential statistics were conducted to compare the self-efficacy and task performance scores across the groups. Additionally, Pearson's correlation was used to examine the relationships between various aspects of search self-efficacy and total task scores. The findings revealed that while students exhibited moderate search self-efficacy, they performed poorly on task-based questions. Significant differences in self-efficacy and task performance were observed based on demographic backgrounds and technological skill levels. Pearson's correlation identified weak but significant positive relationships between search self-efficacy and task scores, and strong positive correlations among the self-efficacy measures.

As digital transformation accelerates outsourcing adoption in university libraries, concerns emerge regarding core capability erosion in reading promotion services, yet systematic understanding of optimal insourcing–outsourcing boundary choices remains limited. This study employs crisp-set Qualitative Comparative Analysis to examine 2399 reading promotion activities from 19 Shanghai universities over the past 5 years, analyzing configurational pathways across four capability dimensions: core collections, distinctive services, data elements, and library spaces. Results reveal asymmetric advantages between service models: insourcing pathways achieve effectiveness through physical space–staff synergy (CO1–CO3, consistency = 0.897–1.000), emphasizing face-to-face interactions and professional relationships, while outsourcing pathways leverage technology–expertise coupling (SO1–SO3, consistency = 0.860–1.000), integrating virtual platforms with external knowledge resources. No single capability proves necessary for success, confirming configurational causality in reading promotion effectiveness. These findings demonstrate that sustainable competitive advantage emerges from capability-specific boundary delineation rather than wholesale outsourcing strategies, providing theoretical insights for capability-based outsourcing decisions and practical guidance for dynamic resource allocation in library digital transformation contexts.