478 research outputs found

    Heterformer: Transformer-based Deep Node Representation Learning on Heterogeneous Text-Rich Networks

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    Representation learning on networks aims to derive a meaningful vector representation for each node, thereby facilitating downstream tasks such as link prediction, node classification, and node clustering. In heterogeneous text-rich networks, this task is more challenging due to (1) presence or absence of text: Some nodes are associated with rich textual information, while others are not; (2) diversity of types: Nodes and edges of multiple types form a heterogeneous network structure. As pretrained language models (PLMs) have demonstrated their effectiveness in obtaining widely generalizable text representations, a substantial amount of effort has been made to incorporate PLMs into representation learning on text-rich networks. However, few of them can jointly consider heterogeneous structure (network) information as well as rich textual semantic information of each node effectively. In this paper, we propose Heterformer, a Heterogeneous Network-Empowered Transformer that performs contextualized text encoding and heterogeneous structure encoding in a unified model. Specifically, we inject heterogeneous structure information into each Transformer layer when encoding node texts. Meanwhile, Heterformer is capable of characterizing node/edge type heterogeneity and encoding nodes with or without texts. We conduct comprehensive experiments on three tasks (i.e., link prediction, node classification, and node clustering) on three large-scale datasets from different domains, where Heterformer outperforms competitive baselines significantly and consistently.Comment: KDD 2023. (Code: https://github.com/PeterGriffinJin/Heterformer

    Historically Black Colleges and Universities\u27 Faculty Experiences With Online Course Design

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    Quality online course design requires course designers to make carefully informed decisions based on current resources and considerations for the learner. Some faculty at historically Black colleges and universities (HBCUs) design online learning without the assistance of instructional designers, training, or a technological infrastructure that supports online learning. To date, there is a shortage of scholarly research about how HBCU faculty design online courses and what supports or barriers exist for them. Thus, this basic qualitative research study aimed to understand faculty’s online course design experiences at HBCUs. Instructional design, adult learning theory, and the HBCU context formed the conceptual framework and influenced the research questions. Semistructured, open-ended interviews were conducted with nine HBCU faculty who had participated in an online course design project, followed by open coding and thematic analysis. Four common themes emerged from the interviews: macrolevel factors, collaboration and experience, time and tools, and student-centered design. All themes highlighted the considerations unique to HBCUs but are also similar to broader online learning contexts. This study extends the educational technology and design field of research and may contribute to positive social change by helping faculty and administration consider the influences and resources needed for designing online learning for nontraditional diverse online learner populations. As institutions address concerns faculty observe as risks to student success in online learning, students can receive a higher quality education

    Historically Black Colleges and Universities\u27 Faculty Experiences With Online Course Design

    Get PDF
    Quality online course design requires course designers to make carefully informed decisions based on current resources and considerations for the learner. Some faculty at historically Black colleges and universities (HBCUs) design online learning without the assistance of instructional designers, training, or a technological infrastructure that supports online learning. To date, there is a shortage of scholarly research about how HBCU faculty design online courses and what supports or barriers exist for them. Thus, this basic qualitative research study aimed to understand faculty’s online course design experiences at HBCUs. Instructional design, adult learning theory, and the HBCU context formed the conceptual framework and influenced the research questions. Semistructured, open-ended interviews were conducted with nine HBCU faculty who had participated in an online course design project, followed by open coding and thematic analysis. Four common themes emerged from the interviews: macrolevel factors, collaboration and experience, time and tools, and student-centered design. All themes highlighted the considerations unique to HBCUs but are also similar to broader online learning contexts. This study extends the educational technology and design field of research and may contribute to positive social change by helping faculty and administration consider the influences and resources needed for designing online learning for nontraditional diverse online learner populations. As institutions address concerns faculty observe as risks to student success in online learning, students can receive a higher quality education

    The Impact of Additive Manufacturing on Supply Chains and Business Models: Qualitative Analyses of Supply Chain Design, Governance Structure, and Business Model Change

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    Recent global crises like the COVID-19 pandemic challenge traditional global supply chains (SCs). Their disaggregated, “fine-sliced” character comes with a high risk of disruption, and current supply bottlenecks (e.g., the chip shortage in the automotive industry) demonstrate that there is often no quick fix. Firms are increasingly under pressure to react and (re-)design their SCs to increase their resilience. Additive manufacturing (AM) technologies are acclaimed for their potential to foster the shift from global SCs to shorter, decentralized, and more resilient SCs. The key feature of AM technologies lies in their inherently digital and flexible nature. Their specific characteristics are envisioned to enable location-independent manufacturing close to or even at the point of demand and lead to a commoditization of manufacturing infrastructure for flexible outsourcing to local partners. Moreover, AM technologies are expected to revolutionize the way firms do business and put traditional business models at stake. This doctoral thesis is motivated by the outlined potential of AM and the resulting impact on firms’ supply chain design (SCD) and business model choices. The extant literature raises high expectations for AM. However, concrete and real-world insights from specific application domains are still scarce. This thesis seeks to fill the gap between high-level literature-based visions and currently emerging realistic business models and SCDs for AM. Thereby, AM is understood as a potential intervention emanating from outside firms and requiring them to react by realigning their business models and SC structures to maintain a fit. This thesis aims to build an in-depth understanding of these mechanisms and, hence, of the inner causal processes involved in the AM SCD and business model choices. This concentration on the rationales and underlying behavioral patterns is formalized with primarily exploratory (how and why) research questions that are addressed with qualitative research methodologies, mainly case study research and grounded theory. These methodological practices are applied in the industrial AM context, entailing an embedding of this thesis in challenging industries where AM applications have already started to create value (i.e., in the aerospace, rail, automotive, and machinery and equipment industries). The selected research approaches are mostly inductive and, hence, strongly driven by the data collected from this context (e.g., in interviews, by reviewing documents, and by analyzing websites). Additionally, this thesis relies on grand theories, namely transaction cost economics, the resource-based view, and configuration theory, to discuss the findings in their light and to interpret and distill nuances of these theories for their application in the industrial AM context. This thesis is cumulative, consisting of four studies that form its main body. These studies are organized in two parts, part A and part B, since two domains of strategic decisions are targeted jointly, the business model development (part A) and AM SCD choice (part B) for industrial AM. Different perspectives are associated with the two parts. Logistics service providers (LSPs) are in a critical position to develop AM business models. Based on the expected shift to decentralized, shorter SCs, the traditional business models of LSPs are at risk, and their inherent customer orientation puts them under pressure to adjust to their customers’ needs in AM. In part A, study A.1 applies a process-based perspective to build a broad understanding of how LSPs currently respond to AM and consumer-oriented polymer 3D printing with specific AM activities. It proposes six profiles of how LSPs leverage AM, both as users for their in-house operations and as developers of AM-specific services for external customers. A key finding is that the initiated AM activities are oftentimes strongly based on LSPs’ traditional resources. Only a few LSPs are found whose AM activities are detached from their traditional business models to focus on digital platform-based services for AM. In contrast to the process-based perspective and focus on business model dynamics in study A.1, study A.2 takes an output perspective to propose six generic business model configurations for industrial AM. Each configuration emerges from the perspective of LSPs and is reflected by their potential partners/competitors and industrial customers. Study A.2 explores how the six generic configurations fit specific types of LSPs and how they are embedded in a literature-based service SC for industrial AM. In combination, studies A.1 and A.2 provide a comprehensive understanding of how LSPs are currently reacting to AM and an empirically grounded perspective on “finished” AM business models to evaluate and refine literature-based visions. Part B of this thesis is devoted to the mechanism of (re-)designing SCs for AM, which is investigated from the perspective of focal manufacturing firms based on their dominant position in SCs. Two dimensions are used to characterize AM SCDs, their horizontal scope (geographic dispersion) and vertical scope (governance structure). The combination of both dimensions is ideally suited to capture the literature-based vision of shorter, decentralized AM SCs (horizontal scope) with eased outsourcing to local partners (vertical scope). Study B.1 takes a firm-centric perspective to develop an in-depth understanding for AM make-or-buy decisions of manufacturing firms, the outcomes of which determine the SC governance structure. This study elaborates how the specific (digital and emerging) traits of industrial AM technologies modify arguments of grand theories that explain make-or-buy decisions in the “analog” age. In comparison, study B.2 shifts from a firm-centric to a network perspective to rely on both dimensions for investigating cohesive AM SCD configurations. More specifically, study B.2 explores four polar AM SCD configurations and reveals manufacturing firms’ rationales for selecting them. Thereby, it builds an understanding for why manufacturing firms currently have valid reasons to implement industrial AM in-house or distributed in a secure, firm-owned network. As a result, combining both studies provides an understanding of why manufacturing firms currently select specific governance structures for industrial AM and opt for SCDs that differ from the literature-based vision of decentralized, outsourced AM. Overall, this thesis positions itself as theory-oriented research that also aims at supporting managers of manufacturing firms and LSPs in making informed decisions when implementing AM in their SCs and developing AM-based business models. The three studies A.1, A.2, and B.2 contribute to initial theory building on how and why specific AM business models and SCDs emerge. With their focus on developing an understanding for the causal processes (how and why) and by assuming a process-based and output perspective, they can draw a line from firms’ current reactions to sound reflections on future-oriented, high-level expectations for AM. As a result, the studies significantly enrich and refine the current body of knowledge in the AM business model literature on LSPs and the operations and supply chain management literature on AM SCDs, focusing on their geographic dispersion and governance structure. This thesis further contributes with its context-specificity to building domain knowledge for industrial AM, which can serve as one “puzzle piece” for theorizing on how AM and other digitally dominated (manufacturing) technologies will shape the era of digital business models and SCs. In particular, study B.1 stands out by its focus on theory elaboration and the objective of developing contextual middle-range theory. It reveals that emerging digital AM is a setting where the argumentation of grand theories provides contradicting guidance on whether to develop AM in-house or outsource the manufacturing process. Such findings for industrial AM raise multiple opportunities for future research, among them are the comparison with other industry contexts with similar characteristics and the operationalization of the propositions developed in this thesis in follow-up quantitative decision-support models

    GPT Semantic Networking: A Dream of the Semantic Web – The Time is Now

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    The book presents research and practical implementations related to natural language processing (NLP) technologies based on the concept of artificial intelligence, generative AI, and the concept of Complex Networks aimed at creating Semantic Networks. The main principles of NLP, training models on large volumes of text data, new universal and multi-purpose language processing systems are presented. It is shown how the combination of NLP and Semantic Networks technologies opens up new horizons for text analysis, context understanding, the formation of domain models, causal networks, etc. This book presents methods for creating Semantic Networks based on prompt engineering. Practices are presented that will help build semantic networks capable of solving complex problems and making revolutionary changes in the analytical activity. The publication is intended for those who are going to use large language models for the construction and analysis of semantic networks in order to solve applied problems, in particular, in the field of decision making.У книзі представлені дослідження та практичні реалізації технологій обробки природної мови (НЛП), заснованих на концепції штучного інтелект, генеративний ШІ та концепція складних мереж, спрямована на створення семантичних мереж. Представлено основні принципи НЛП, моделі навчання на великих обсягах текстових даних, нові універсальні та багатоцільові системи обробки мови. Показано, як поєднання технологій NLP і семантичних мереж відкриває нові горизонти для аналізу тексту, розуміння контексту, формування моделей домену, причинно-наслідкових мереж тощо. У цій книзі представлені методи створення семантичних мереж на основі оперативного проектування. Представлені практики, які допоможуть побудувати семантичні мережі, здатні вирішувати складні проблеми та вносити революційні зміни в аналітичну діяльність. Видання розраховане на тих, хто збирається використовувати велику мову моделі побудови та аналізу семантичних мереж з метою вирішення прикладних задач, зокрема, у сфері прийняття рішень

    Beyond Quantity: Research with Subsymbolic AI

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    How do artificial neural networks and other forms of artificial intelligence interfere with methods and practices in the sciences? Which interdisciplinary epistemological challenges arise when we think about the use of AI beyond its dependency on big data? Not only the natural sciences, but also the social sciences and the humanities seem to be increasingly affected by current approaches of subsymbolic AI, which master problems of quality (fuzziness, uncertainty) in a hitherto unknown way. But what are the conditions, implications, and effects of these (potential) epistemic transformations and how must research on AI be configured to address them adequately

    Creating immersive, play-anywhere handheld augmented reality stories, through remote user testing

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    This thesis outlines new instances of Extended Reality (XR) stories as well as associated user studies with them, to create more immersive story experiences delivered at a user’s choice of location through a mobile phone. This extends prior work on Location Based Experiences (LBEs), which have typically been designed to offer a game or story at a pre-determined location. A play-anywhere experience offers potential to open up LBEs to a wider audience, as well as to those may prefer to take part individually or closer to home, such attitude shifts becoming increasingly more common. The current research adopted an in the wild approach combining practice, studies and theory, with most user data being collected remotely. Each story application developed is subsequently referred to as an app, with each app offering a bespoke story incorporating Augmented Reality (AR) features, to better bring users’ location inline with the narrative. Testing the apps across various locations matched their intended use, and resulted in new guidelines for both incorporating AR into such LBEs, as well as for conducting remote user studies. A final app offered a site-specific curated story, with all study participants taking part under similar conditions at the same location, the ability to observe them using the app providing additional insights. The story apps used available local map data alongside Handheld Augmented Reality (HAR), to overlay interactable virtual objects on top of the physical environment, and visible on the phone’s display. Guidelines from related methodologies were used to better allow for the variety of factors that might influence different users’ immersion and engagement. These included the implementation of the AR features, the story itself, real world activity, and personal preferences including onboarding requirements. The approach taken contributed a reverse methodology to a lot of related research, that would typically begin with laboratory testing before moving to public spaces. User studies with the five mobile apps contributed guidelines for such experiences, that could benefit both practitioners and researchers in related fields. In the later case, a need was identified to develop new research tools specifically suited to the subtleties of handheld play-anywhere LBEs, such issues explored within the apps tested. The guidelines identified for offering more effective XR LBEs were also implemented in the creation of a new open source Unity project, called Map Story Engine. This offers a tool to test new features, as well as providing a fully customisable template for practitioners to author their own play-anywhere HAR stories and games

    Outdata-ed museums: creating ethical and transparent data collection processes in museums

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    UK museums are contradictory sites of education and community outreach, and emblems of colonial legacy and elitism. Physical and socioeconomic barriers prevent meaningful engagement for audiences, but particularly marginalised peoples. To identify and overcome these barriers, museums and cultural institutions are seeking technological solutions that capture and analyse personal data. However, current legislation and attitudes towards personal data also risk perpetuating exclusionary barriers. Many governments and organisations use personal data to suppress, undermine, and violently target minoritised or marginalised communities whilst upholding the status quo that marginalised them in the first place. This inequality is further entrenched by the powerlessness most people feel in the face of how data is collected and used on a day-to-day basis. Drawing on Human Computer Interaction, Human Geography and New Museology, this PhD thesis seeks a solution to these concerns that empowers museums to safely collect the data they need whilst enabling audiences to become active in their own data curation. Using co-creative principles, input is sought from museums and audiences to answer three questions: • How are discourses and practices surrounding personal data negotiated, defined, perpetuated, and resisted in museums? • What is the value of personal data to museums and audiences? • Can mutually beneficial and transparent data exchange foster meaningful, long-term relationships between museums and audiences? To address these questions, a novel theoretical framework that explores museums as place, technology as mediator, and relational personal data through a lens of power is generated. Four sequential studies are then conducted utilising a post-structural feminist epistemology. The first study presents a content analysis of privacy policies to explore what data museums typically collect and how that information is conceptualised and shared with audiences, showing that museums collect a broad range of quantitative data but inadequately express to audiences what, how, or why. The second study presents a workshop with museum staff to determine what data would benefit the museum and what prevents it from being captured. It shows that museums seek qualitative, behavioural data but are limited by resource constraints. The third study uses workshop style activities to ask audiences to conceptualise the value of their desirable data and speculate different ways for their data to be used in the museum. The study highlights barriers to data engagement including fatigue and lack of understanding, and shows trust and transparency to be key motivators in data sharing. The fourth study uses a novel methodology to speculate a data-enabled museum visit, from which a technology probe called ‘MuNa’ is developed and tested in a virtual museum visit with real audiences. Evaluation shows how transparency and trust can be synchronously developed through meaningful engagement with data. This is shown to increase the engagement of audiences with both museum and data, fostering long-term, meaningful relationships between venue and visitor and the creation of data subjects able to advocate for their own data rights. The implications of this research reach across each of its disciplines and into the everyday practices of cultural organisations and audiences. Contributing novel paradigms of understanding surrounding the museum visit experience including different stakeholder perspectives addressing museums, technology, and personal data, the thesis presents evidence of an equitable and sustainable, data-enabled future

    Authentic alignment : toward an Interpretative Phenomenological Analysis (IPA) informed model of the learning environment in health professions education

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    It is well established that the goals of education can only be achieved through the constructive alignment of instruction, learning and assessment. There is a gap in research interpreting the lived experiences of stakeholders within the UK learning environment toward understanding the real impact – authenticity – of curricular alignment. This investigation uses a critical realist framework to explore the emergent quality of authenticity as a function of alignment.This project deals broadly with alignment of anatomy pedagogy within UK undergraduate medical education. The thread of alignment is woven through four aims: 1) to understand the alignment of anatomy within the medical curriculum via the relationships of its stakeholders; 2) to explore the apparent complexity of the learning environment (LE); 3) to generate a critical evaluation of the methodology, Interpretative Phenomenological Analysis as an approach appropriate for realist research in the complex fields of medical and health professions education; 4) to propose a functional, authentic model of the learning environment.Findings indicate that the complexity and uncertainty inherent in the LE can be reflected in spatiotemporal models. Findings meet the thesis aims, suggesting: 1) the alignment of anatomy within the medical curriculum is complex and forms a multiplicity of perspectives; 2) this complexity is ripe for phenomenological exploration; 3) IPA is particularly suitable for realist research exploring complexity in HPE; 4) Authentic Alignment theory offers a spatiotemporal model of the complex HPE learning environment:the T-icosa

    Design Dynamics. Navigating the new Complex Landscape of Omnichannel Fashion Retail

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    The fashion industry is entering the dynamic global competitive market, promoting various actions prioritising design, creativity, sustainability, and technological advancement as pivotal factors. At the same time, it is reimagining its business models to adapt to the changing landscape. The rise of pervasive connectivity, intuitive interfaces and innovative interaction channels has triggered a revolution in fashion retail, reshaping customer behaviour and expectations. The traditional retail framework has evolved into a fully interconnected omnichannel system. This transformation is characterised by the proliferation of physical and virtual channels and touch points and by the adoption of a more flexible and integrated approach. In this dynamic context, design plays a central role, possessing the ability to impart meaning to the production and distribution system. Design-led innovation represents an incremental form of innovation that injects a nuanced range of meaning into the marketplace, extending beyond tangible objects, including discourses, expressions, narratives, visual images, symbols, metaphors, and spaces. The book analyses the multifaceted nature of the fashion retail experience through the lens of the design discipline, aiming to contextualise the evolution of retail within increasingly complex processes, networks and interconnections, both theoretically and practically. The focus is on retail design, delving into the new skills required and the valuable tools needed to apply them in inherently multidisciplinary contexts. Ultimately, the aim is to navigate the intricate terrain of retail evolution and shed light on the evolving role of design in this multifaceted sector
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