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This study aims to provide insight of how conference sessions and poster sessions are relevant to libraries.

Recently attended IFLA and Internationale Funkaussteilung (IFA) and focused the conference report on generative artificial intelligence (AI).

Disappointed in the IFLA and IFA conferences and instead find that the email newsletter from Shelly Palmer is much better in keeping up with exponential growth in ChatGPT and other generative AI tools.

This study may provide ideas for libraries to experiment with generative AI tools.

This study is an original report by the authors. All photos were taken by the authors except for a table from the email newsletter of Shelly Palmer, which was included by him from another source.

The purpose of this paper is to report the 2023 conference of the International Federation of Library Associations and Institutions (IFLA) conference activities for 2023 as held in Rotterdam, The Netherlands from 21 to 25 August.

A report of the events that spanned five days, especially the aspects that hinged on technology use in libraries globally are highlighted. Narrative of the experiences during the conference is made from the participatory observation standpoint.

Librarians globally are connecting and collaborating. They use technology in their libraries and research into ways and means of collaborating more. Library associations globally are making impact especially in the use of artificial intelligence in service delivery. All sections of IFLA are active in working together and librarying!

The IFLA 2023 conference is one-of-a-kind experience in the library association world. Libraries and librarians globally are finding out new things yearly and the year 2023 is no different.

The purpose of this study is to explore whether immersive virtual reality (VR) can complement e-participation and help alleviate some major obstacles that hinder effective communication and collaboration. Immersive virtual reality (VR) can complement e-participation and help alleviate some major obstacles hindering effective communication and collaboration. VR technologies boost discussion participants' sense of presence and immersion; however, studying emerging VR technologies for their applicability to e-participation is challenging because of the lack of affordable and accessible infrastructures. In this paper, the authors present a novel framework for analyzing serious social VR engagements in the context of e-participation.

The authors propose a novel approach for artificial intelligence (AI)-supported, data-driven analysis of group engagements in immersive VR environments as an enabler for next-gen e-participation research. The authors propose a machine-learning-based VR interactions log analytics infrastructure to identify behavioral patterns. This paper includes features engineering to classify VR collaboration scenarios in four simulated e-participation engagements and a quantitative evaluation of the proposed approach performance.

The authors link theoretical dimensions of e-participation online interactions with specific user-behavioral patterns in VR engagements. The AI-powered immersive VR analytics infrastructure demonstrated good performance in automatically classifying behavioral scenarios in simulated e-participation engagements and the authors showed novel insights into the importance of specific features to perform this classification. The authors argue that our framework can be extended with more features and can cover additional patterns to enable future e-participation immersive VR research.

This research emphasizes technical means of supporting future e-participation research with a focus on immersive VR technologies as an enabler. This is the very first use-case for using this AI and data-driven infrastructure for real-time analytics in e-participation, and the authors plan to conduct more comprehensive studies using the same infrastructure.

The authors’ platform is ready to be used by researchers around the world. The authors have already received interest from researchers in the USA (Harvard University) and Israel and run collaborative online sessions.

The authors enable easy cloud access and simultaneous research session hosting 24/7 anywhere in the world at a very limited cost to e-participation researchers.

To the best of the authors’ knowledge, this is the very first attempt at building a dedicated AI-driven VR analytics infrastructure to study online e-participation engagements.

As higher education institutions (HEIs) have increasingly turned to consider sustainability over the last decade, education for sustainable development (ESD) has emerged as a way of imbuing students with the skills, values, knowledge, and attributes to live, work, and create change in societies facing complex and cross-cutting sustainability challenges. However, the question of how HEIs can actively embed ESD more broadly in and across curricula is one that continues to challenge institutions and the HE sector as a whole. While traditional teaching practices and methods associated with subject-based learning may be suitable for educating students about sustainable development, a re-orientation towards more transformational, experiential and action-oriented methods is required to educate for sustainable development. The need for educators to share their practices and learn lessons from each other is essential in this transformation.

This paper presents a selection of practical examples of how to embed a range of interactive, exploratory, action-oriented, problem-based, experiential and transformative ESD offerings into HE teaching practice and curricula. Presented by a group of academics and professional services staff at the University of Strathclyde who lead key modules and programmes in the institution’s ESD provision, this paper reflects on five approaches taken across the four faculties at Strathclyde (Humanities and Social Sciences, Science, Engineering and the Strathclyde Business School) and examines the challenges, practicalities and opportunities involved in establishing a collaborative programme of ESD.

In this chapter, we outline the background to the present volume, including the history of the Emonet group and the origins of the book series. We argue that the volume subtitle “A coat of many colors” reflects the diversity of approaches to studying emotion in organizational settings. We then provide a summary of the 11 contributor chapters in the volume, which illustrates the wide range of emotion-related topics covered in the volume.

This chapter provides an overview of the chapters in the volume, and gives a brief summary of each chapter, explaining how each fits into the overall theme of the volume and listing the key contribution of each chapter.

The introduction concludes with a summary of main findings of the chapters, and how they shape the future of the field, concluding that, since emotion-related topics nowadays are so integrated into the mainstream literature in organizational behavior and organization theory, maybe there is no longer a need to address emotions as a stand-alone topic.

The chapters in this volume address a wide range of emotion-related topics in the fields of organizational behavior and organization theory and point to the future of research in this field.

This brief history of the International Study Association on Teachers and Teaching (ISATT) documents developments and trends during the decade 2013–2023. To situate recent ISATT history, we begin with an overview of the association's first 30 years (1983–2012). The dominant theme of those early years was developing ISATT as a recognized and influential professional organization connecting researchers on teaching and teacher education from a growing list of nations and regions of the world. During the most recent decade, there has been a concerted effort toward broad internationalization through biennial conferences and regional meetings, and a growing network of national representatives from across the world. Also, the ISATT journal, Teachers and Teaching: Theory and Practice, the journal, which began in 1995, has published hundreds of peer-reviewed articles written by more than 1000 authors and coauthors, contributing to a growing body of knowledge about teaching and teacher education in many cultures. In the last 20 years and especially in the past 10, the locations of ISATT meetings have become significantly more diverse, following a trend of greater internationalization compared with ISATT's European and North American beginnings. At the same time, the number of ISATT members remains stable and small thereby preserving a collegial and collaborative tone in our exchanges. In sum, ISATT's recent decade finds the association intellectually healthy, successful in managing the challenges of the Covid-19 pandemic, and enriched by the proliferation of multinational points of view and styles of research.

Judging bias is ironically an inherent risk in every competition, which might threaten the fairness and legitimacy of the competition. The patriotism effect represents one source of judging bias as the judge favors contestants who share the same sentiments, such as the nationalistic, racial, or cultural aspects. This study attempts to explore this type of judging bias in a university student competition. In addition, this study tries to expand the literature on judging bias by proposing the term universitarian bias as the judge is suspected to give a higher score to contestants from the same university.

The association rule of data mining is used to accomplish the objective of the study. To demonstrate the applicability of the method, the data set from the annual national university student competition in Indonesia is exploited.

The result strongly discovers that the universitarian bias is likely to be present. Some recommendations are also provided in order to minimize the bias that might happen again in the future.

As the implication of the presence of the universitarian bias, the committee should remove all the university features attributed to the participants. This endeavor is expected to minimize the universitarian bias that might happen.

This research is claimed to be the first attempt in implementing the data mining technique in the field of judging bias.

Virtual organizations present numerous challenges for managers, especially in regards to organizational identity formation. This paper aims to address this gap in the extant literature by exploring how organizational narratives can foster identification with the virtual organization. Moreover, information technology can further catalyze the positive effects of narratives on identity formation.

Qualitative data from in-depth interviews with 18 members of a nonprofit, virtual organization – DiverseCS – were collected. Participants were asked about their roles in the organization, challenges and collaborative efforts. Grounded theory methodology was used to analyze the data.

Efforts to instill a sense of identity and community through the adoption of information technology was met with resistance. Rather, senior leaders encouraged and institutionalized the creation of organizational narratives. Novel use of information technology – social media and hyperlinks – became a means to amplify the positive effects of narrative creation and sharing by organizational members.

This study investigates how some members of a virtual organization use information technology in novel ways to further spread organizational narratives to other organizational members and also to external collaboration partners. This research contributes to the extant literature on virtual organizational identity and also proposes a research agenda.

The malfunction variables of power stations are related to the areas of weather, physical structure, control and load behaviour. To predict temporal power failure is difficult due to their unpredictable characteristics. As high accuracy is normally required, the estimation of failures of short-term temporal prediction is highly difficult. This study presents a method for converting stochastic behaviour into a stable pattern, which can subsequently be used in a short-term estimator. For this conversion, K-means clustering is employed, followed by Long-Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) algorithms are used to perform the Short-term estimation. The environment, the operation and the generated signal factors are all simulated using mathematical models. Weather parameters and load samples have been collected as part of a data set. Monte-Carlo simulation using MATLAB programming has been used to conduct experimental estimation of failures. The estimated failures of the experiment are then compared with the actual system temporal failures and found to be in good match. Therefore, for any future power grid, there is a testbed ready to estimate the future failures.