Exploring potential roles of academic libraries in undergraduate data science education curriculum development

Shao, Gang; Quintana, Jenny; Zakharov, Wei; Purzer, Şenay; Kim, Eunhye

doi:10.1016/j.acalib.2021.102320

Cited by 8 publications

(5 citation statements)

References 42 publications

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“…Applying AI to data about users is simply an extension of this. It is generally accepted that data science is a combination of domain knowledge, statistical analysis and computational methods (Shao et al, 2021). Librarians have the first.…”

Section: Use Case 5: Use Of Data To Analyse Predict and Influence Use...mentioning

confidence: 99%

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Defining artificial intelligence for librarians

Cox

Mazumdar

2022

Journal of Librarianship and Information Science

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The aim of the paper is to define Artificial Intelligence (AI) for librarians by examining general definitions of AI, analysing the umbrella of technologies that make up AI, defining types of use case by area of library operation, and then reflecting on the implications for the profession, including from an equality, diversity and inclusion perspective. The paper is a conceptual piece based on an exploratory literature review, targeting librarians interested in AI from a strategic rather than a technical perspective. Five distinct types of use cases of AI are identified for libraries, each with its own underlying drivers and barriers, and skills demands. They are applications in library back-end processes, in library services, through the creation of communities of data scientists, in data and AI literacy and in user management. Each of the different applications has its own drivers and barriers. It is hard to anticipate the impact on professional work but as information environment becomes more complex it is likely that librarians will continue to have a very important role, especially given AI’s dependence on data. However, there could be some negative impacts on equality, diversity and inclusion if AI skills are not spread widely.

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Section: Use Case 5: Use Of Data To Analyse Predict and Influence Use...mentioning

confidence: 99%

“…The activities in such units could include organising training programmes and reading groups. Libraries might support data science teaching programmes with data management teaching, which tends to get neglected in curricula (Shao et al, 2021).…”

Section: Use Case 3: Supporting Communities Of Data Scientistsmentioning

confidence: 99%

Defining artificial intelligence for librarians

Cox

Mazumdar

2022

Journal of Librarianship and Information Science

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“…Based on the study conducted at Purdue University in 2017 to examine the roles of academic libraries to support data science education curriculum, results showed that "hard-core" scientific courses for third-and fourth-year STEM students were most common as opposed to offerings in data-oriented skills, such as data management, data ethics, and data communications. 85 At schools of information, a group of instructors who teach data curation have expressed the importance of integrating both research and teaching in the curriculum. The objective would give students opportunities to develop core competencies, learn about data librarianship and practices to support preservation and access, and broaden their professional horizons by gaining a greater awareness with multidimensional problems of working with data.…”

Section: Datamentioning

confidence: 99%

Top trends in academic libraries: A review of the trends and issues

2022

CRLN

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This article summarizes trending topics in academic librarianship from the past two years-a time of tremendous upheaval and change, including a global pandemic, difficult reflections concerning racial justice, and war between nation states. Rapid changes and uncertainty from these events have created a significant amount of shifts to academic libraries, higher education, and society in general. Such shifts have yielded new perspectives and innovations in how librarians approach delivering services, supporting student success, managing staff and physical spaces, embracing new technology, and managing data. This report attempts to provide a snapshot of developments worth noting. COVID-related trendsThe impact of the COVID-19 pandemic on academic library services has been significant, and these changes, in many cases, are ongoing. The issues identified below transcend the period covered by this review as libraries face a fundamental shift that will extend far into the future and beyond the pandemic. In early 2020, nearly all academic 1 and public 2 libraries closed temporarily and shifted towards virtual services. Despite in-person closures, libraries continued online services, 3 kept their communities informed, 4 and adopted innovative collaborations 5 and technologies to adapt to changing circumstances. These closures and the institutional changes that enabled them had a significant and diverse impact on librarianship, including rethinking long-held paradigms, 6 increased professional stress around institutional budgets, 7 and the ability to work remotely. 8 The pandemic also surfaced long-standing issues of inequality 9 and inaccessibility 10 in libraries. Despite the challenges raised by closures, libraries continued to deliver core services and creative solutions, including virtual reference with increasing complexity, 11 a renewed focus on digital literacy with the rise in online learning, 12 and born-digital collection development. 13 2021-22 ACRL Research Planning and Review Committee Top trends in academic libraries A review of the trends and issues 2021-22 ACRL Research Planning and Review Committee: Alex McAllister (chair) is associate professor and coordinator of Collection Management, Appalachian State University Libraries, email:

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“…This paper, published around the time NC State Libraries founded DVS, reflects the changing institutional priorities for many research universities across the United States. Often, statistical consulting at academic institutions is housed in statistics departments, and other computer programming support is siloed in computer science‐related departments (Parker et al, 2021; Shao et al, 2021). Academic libraries offer a unique ‘home’ to statistical and data science consulting, due to their traditionally large role in undergraduate education support, and the campus‐wide access of their services (Mani et al, 2021; Shao et al, 2021).…”

Section: Introduction: Landscape Of Data Science Consulting and Need ...mentioning

confidence: 99%

The student staffing advantage: Data Science Consulting Service at NC State University Libraries

Marchesoni,

Freeman,

Tezbasaran

et al. 2024

Stat

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The primarily peer‐to‐peer, graduate student‐staffed Data Science Consulting Service at NC State University Libraries, within the Data & Visualization Services (DVS) department and collaborating closely with the Data Science Academy (DSA), has established a sustainable service and staffing model focused on providing broad data science analytic support to researchers across the university community. The service addresses the needs of university researchers who possess domain knowledge in their fields of study but a skills gap in the data science competencies required for research. The literature shows that it has been difficult for libraries to cover these needs with existing staffing models. Few universities follow the model practiced at NC State University, so a scan of the current landscape of data science consulting at universities across the country was performed to establish context. The support model and its advantages are described, including partnership with the DSA, student success, model sustainability and future directions for the service. Through a summary of the DVS assessment and needs evaluation process, the service's advantages in staying ahead of patron needs are illustrated. This scalable, sustainable, student‐focused model could be implemented by similar research institutions to expand the capacity of their technical research services.

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Exploring potential roles of academic libraries in undergraduate data science education curriculum development

Cited by 8 publications

References 42 publications

Defining artificial intelligence for librarians

Defining artificial intelligence for librarians

Top trends in academic libraries: A review of the trends and issues

The student staffing advantage: Data Science Consulting Service at NC State University Libraries

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