Search results

The purpose of this study is to identify the impact of online learning on university librarians’ professional development and library services.

A mixed-methods study through an explanatory research design was applied to address the study’s objectives. Quantitative data were gathered from 341 librarians working in 221 universities, while qualitative data were gathered from 27 experts working in 21 different universities of Pakistan.

The findings of the study revealed that online learning has a significant positive impact on the professional development of university librarians. Results revealed that online learning assists in the provision of sustainable, innovative library services in university libraries.

The study has offered a model in light of the study's quantitative and qualitative findings. It contributes to theoretical understanding by expanding the existing knowledge base. It offers managerial insights, enabling the development of policies that foster the professional development of library personnel and the implementation of smart library services.

This paper aims to focus on academic library managers’ learning practices in the context of cooperative work supported by computational artefacts. Academic library managers’ everyday work is mainly cooperative. Their cooperation is supported predominantly by computational artefacts. Learning how to use the computational artefacts efficiently and effectively involves understanding the changes in everyday work that affect managers and, therefore, it requires deep understanding of their cooperative work practices.

Focused ethnography was conducted through participant observations, interviews and document analysis. Ten managers from a university library in Sweden participated in the research. A thematic method was used to analyse the empirical material. Computer supported cooperative work (CSCW) and work-integrated learning was used as the conceptual lens.

Five learning practices were identified: collaboration, communication, coordination, decision-making processes and computational artefacts’ use. The findings show that learning is embedded in managers’ cooperative work practices, which do not necessarily include sufficient training time. Furthermore, learning was intertwined with cooperating and was situational. Managers learned by reflecting together on their own experiences and through joint cooperation and information sharing while using the computational artefacts.

The main contribution lies in providing insights into how academic library managers learn and cooperate in their everyday work, emphasizing the role of computational artefacts, the importance of the work context and the collective nature of learning. It also highlights the need for continual workplace learning in contemporary knowledge work environments. Thus, the research generates contributions to the informatics field by extending the understanding of managers’ work-integrated learning in their everyday cooperative work practices supported by computational artefacts’ use. It also contributes to the intersection of CSCW and work-integrated learning.

This case study explores how universal design for learning (UDL)-informed online instruction modules developed during COVID-19 can better support student information literacy outcomes. This study will also examine how hybrid learning lends itself to UDL and may resolve some of the issues within library instruction.

This case study explores how a team of librarians at Utah State University developed three UDL-informed modules to support library instruction and hybrid learning during the height of the COVID-19 pandemic. A survey was sent to composition instructors to understand how they utilized the three new UDL-informed modules and if the modules helped their students reach information literacy outcomes.

Findings from this case study describe how academic libraries should adopt the UDL framework to support best practices for online learning as well as inclusive pedagogies. The findings indicate that the UDL-informed modules developed for hybrid instruction help students meet information literacy outcomes and goals.

The authors present a case study examining the current climate of information literacy instruction and UDL while providing actionable instructional practices that can be of use to librarians implementing hybrid instruction.

The purpose of this study was to bring library practitioners and researchers together to develop two co-designed tools for helping library practitioners gain a more holistic understanding of families in underserved groups and identify their values with the goal of developing more relevant learning experiences for them. The co-designed tools were then tested with Master’s of Library and Information Science (MLIS) students at two universities, whose feedback yielded several valuable findings and informed revisions to the tools.

A participatory, design-based approach was used throughout the study, both with engaging library practitioners in the co-design of different tools and processes introduced in the Toolkit, and to help MLIS students and library practitioners test the tools and provide feedback on the tool revisions.

Students indicated that the tools helped them develop a deeper understanding of underserved groups and their values and gave the students the time and space to reflect on their understanding of the socio-cultural and value contexts of their communities and the values they hold.

This study can help libraries more effectively design strengths-based learning experiences that are meaningful and relevant to underserved groups and their values, particularly for children and families from underserved communities.

This study explores the implementation of personalised information access, driven by machine learning, in Nigerian public libraries. The purpose of this paper is to address existing challenges, enhance the user experience and bridge the digital divide by leveraging advanced technologies.

This study assesses the current state of Nigerian public libraries, emphasising challenges such as underfunding and lack of technology adoption. It proposes the integration of machine learning to provide personalised recommendations, predictive analytics for collection development and improved information retrieval processes.

The findings underscore the transformative potential of machine learning in Nigerian public libraries, offering tailored services, optimising resource allocation and fostering inclusivity. Challenges, including financial constraints and ethical considerations, are acknowledged.

This study contributes to the literature by outlining strategies for responsible implementation and emphasising transparency, user consent and diversity. The research highlights future directions, anticipating advancements in recommendation systems and collaborative efforts for impactful solutions.

Artificial Intelligence (AI) is an emerging technology and turned into a field of knowledge that has been consistently displacing technologies for a change in human life. It is applied in all spheres of life as reflected in the review of the literature section here. As applicable in the field of libraries too, this study scientifically mapped the papers on AAIL and analyze its growth, collaboration network, trending topics, or research hot spots to highlight the challenges and opportunities in adopting AI-based advancements in library systems and processes.

The study was developed with a bibliometric approach, considering a decade, 2012 to 2021 for data extraction from a premier database, Scopus. The steps followed are (1) identification, selection of keywords, and forming the search strategy with the approval of a panel of computer scientists and librarians and (2) design and development of a perfect algorithm to verify these selected keywords in title-abstract-keywords of Scopus (3) Performing data processing in some state-of-the-art bibliometric visualization tools, Biblioshiny R and VOSviewer (4) discussing the findings for practical implications of the study and limitations.

As evident from several papers, not much research has been conducted on AI applications in libraries in comparison to topics like AI applications in cancer, health, medicine, education, and agriculture. As per the Price law, the growth pattern is exponential. The total number of papers relevant to the subject is 1462 (single and multi-authored) contributed by 5400 authors with 0.271 documents per author and around 4 authors per document. Papers occurred mostly in open-access journals. The productive journal is the Journal of Chemical Information and Modelling (NP = 63) while the highly consistent and impactful is the Journal of Machine Learning Research (z-index=63.58 and CPP = 56.17). In the case of authors, J Chen (z-index=28.86 and CPP = 43.75) is the most consistent and impactful author. At the country level, the USA has recorded the highest number of papers positioned at the center of the co-authorship network but at the institutional level, China takes the 1st position. The trending topics of research are machine learning, large dataset, deep learning, high-level languages, etc. The present information system has a high potential to improve if integrated with AI technologies.

The number of scientific papers has increased over time. The evolution of themes like machine learning implicates AI as a broad field of knowledge that converges with other disciplines. The themes like large datasets imply that AI may be applied to analyze and interpret these data and support decision-making in public sector enterprises. Theme named high-level language emerged as a research hotspot which indicated that extensive research has been going on in this area to improve computer systems for facilitating the processing of data with high momentum. These implications are of high strategic worth for policymakers, library stakeholders, researchers and the government as a whole for decision-making.

The analysis of collaboration, prolific authors/journals using consistency factor and CPP, testing the relationship between consistency (z-index) and impact (h-index), using state-of-the-art network visualization and cluster analysis techniques make this study novel and differentiates it from the traditional bibliometric analysis. To the best of the author's knowledge, this work is the first attempt to comprehend the research streams and provide a holistic view of research on the application of AI in libraries. The insights obtained from this analysis are instrumental for both academics and practitioners.

This paper aims to explore the potential impact of artificial intelligence (AI) image generators, specifically MidJourney and DALL-E, on education and library services. The study aims to understand how these tools can revolutionize learning experiences and library resources while also addressing the ethical considerations surrounding their use.

This study investigates the technical foundations of MidJourney and DALL-E, highlighting their neural network architectures. It also traces the iterative refinement of these models and examines cost, accessibility and the unique prompt-guided capabilities of DALL-E 3.

MidJourney and DALL-E show remarkable progress in generating high-quality, photorealistic images from text prompts. The iterative refinement of these models demonstrates a trend toward improved creative output and user accessibility. DALL-E 3, in particular, allows users to guide image generation through prompt modifications, offering unprecedented control over the creative process. The study identifies potential applications in personalized learning, visual communication and research support in libraries, while recognizing challenges such as cost and accessibility.

This research innovatively explores AI's impact on education and libraries, detailing applications in personalized learning and research while addressing legal and ethical considerations.

The purpose of this study Artificial intelligence (AI) is one of the important emerging trends in information technology and is slowly being implemented in libraries. The researchers have presented a brief strengths, weaknesses, opportunities and threats (SWOT) analysis of the application of AI in Pakistani university libraries.

This study uses an ethnographic approach for data retrieval. Five chief librarians were interviewed by phone, during which they were asked to identify one key strength, weakness, opportunity and threat in terms of introducing AI technologies. The researchers have used a standard SWOT matrix to report the respondents’ comments.

AI is already slowly being introduced into Pakistani university libraries. While commenting on ways in which AI could help their libraries deliver more innovative services and better meet user needs, respondents expressed concern about the investment required in funding, time and staff.

Further study is indicated to identify existing AI implementations in Pakistani university libraries and to assess relevant library users’ perspectives. This study is limited to brief, qualitative data; its main purpose is to validate the use of a SWOT analysis.

Given that AI-based tools are already being used in libraries to some degree regardless of location, now is an opportune time to develop strategies for implementing AI technologies more widely. A SWOT analysis can be used to identify and categorize challenges and risks specific to AI in a logical way to support strategic decision-making.

To date, no SWOT analysis has been conducted in the context of AI applications in libraries, let alone specifically university libraries in Pakistan.

This study aims to describe and examine the strategy used by the Taman Ismail Marzuki Library for increasing its social sustainability capabilities.

The research questions in this study are (1) What is the TIM Library’s social sustainability strategy for supporting the green library concept? and (2) What are the impediments and facilitators to implementing the green library concept in the TIM Library through a social sustainability process? This study adopted a qualitative approach, using a case study method, in research conducted over the period July–November 2022. The data collection methods used were purposive sampling, interviews, observations and document analysis.

This study’s findings indicate that the TIM library’s social sustainability strategy supports economic sustainability up to the independence stage, whereas environmental sustainability is still at the empowerment stage. The green library concept is sustainable due to the library’s commitment to the “third place” concept and library cooperation. The TIM Library’s continuing strategy to use creative community development programs to attract public interest and change the library’s perception in the community should help it realize the green library concept.

Libraries can use the research findings to guide their strategies for community engagement and inclusivity.

The paper suggests that policymakers supporting libraries can consider incorporating elements of the Green Library concept and community development stages into policies to enhance the societal impact of libraries.

The significance of this study is that it uncovers strategies to help public libraries meet the requirements of the green library concept.

As a part of doctoral study, this study aims to analyze research on library management models (LMMs) by conducting a systematic literature review (SLR).

A Preferred Reporting Items for Systematic Review and Mata-Analysis approach was used to search four databases. The search criteria included studies published in English until 2022, resulting 9,125 records. Out of these records, a total of 36 studies were selected for final analysis

The results show a positive attitude among researchers toward the development of LMM for libraries globally. The results depict that more than one-third (39%) of the target population was comprised of academic staff and students. The majority (91.76%) of studies were conducted using survey. Quantitative methods were predominant (89%) for LMMs. There were a significant number of studies conducted in 2016. The country-wise distribution shows the USA and China each contribute (20%) of the studies.

The findings of this research could assist policymakers and authorities in reconciling the LMMs applied in libraries for providing efficient access to information resources and services to end users.

To the best of the authors’ knowledge, this study is unique as no comprehensive study has been conducted on LMMs using the SLR method.