Library Engagement With Emerging Technologies in Research and Learning

Library Engagement With Emerging Technologies in Research and Learning

Robert Robert Awoyemi
DOI: 10.4018/978-1-6684-5709-2.ch020
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Data-intensive emerging technologies manifest in learning and research in several ways, offering routes to impact student success and transform the research process. In learning, emerging technologies may enable new strategies for addressing student success. In research, emerging technologies are already impacting scientific methodologies with more disruption, and opportunity, anticipated. As the nature of research changes, so do the practices surrounding its dissemination and other issues taking on new importance. This chapter identifies strategic opportunities for libraries to adopt and engage with emerging technologies and ways in which library values and professional expertise inform and shape this engagement. The chapter builds on four cross-cutting opportunities that permeate many or all aspects of library services. Each section identifies key technologies shaping user behaviours and library services and highlights exemplary initiatives.
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Opportunities Presented By The Emerging Technologies

From the literature a number of opportunities in technology adoption emerged that transcend any area of research in library services (Daniele, Diana, & Ben, 2015). These cross-cutting opportunities relate to the technologies that have already seen the most widespread or productive engagement and adoption within libraries, the societal trends that are shaping research and learning activities are profound and the ways in which both technological and societal shifts intersect with the research library’s identity and mission are manifesting.

Key Terms in this Chapter

Artificial Intelligence (AI): A term that has taken on a life of its own; it is frequently invoked as an umbrella term for ML, natural language processing (NLP), expert systems, and related technologies that approximate human cognition.

Machine Learning: A sub-discipline of artificial intelligence (AI) that uses collections of examples to train software to recognize patterns, and to act on that recognition.

Data Science: A core competency for researchers, students, and scholars in many or most disciplines that routinely rely on computational data analysis in their research and learning.

Emerging Technologies: These are tools that offer a range of opportunities for libraries to make spaces more welcoming, navigable, interactive, comfortable, and productive that libraries are experimenting with the Internet of Things (IoT), particularly beacon technology, to create self-guided library tours and navigational aids, build augmented reality (AR) to provide location-specific mobile alerts, help users locate materials in the library stacks and facilitate access to bookable or restricted spaces or items.

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