“The #DLFteach Toolkit 2.0 focuses on lesson plans to facilitate disciplinary and interdisciplinary work engaged with 3D technology. As 3D/VR technology becomes relevant to a wide range of scholarly disciplines and teaching context, libraries are proving well-suited to coordinating the dissemination and integration of this technology across the curriculum. For our purposes, 3D technology includes, but is not limited to Augmented Reality (AR) and Virtual Reality (VR) technologies, 3D modeling and scanning software, 3D game engines and WebGL platforms, as well as 3D printers and extruders. While 3D/VR/AR technologies demonstrate real possibilities for collaborative, multidisciplinary learning, they are also fraught with broader concerns prevalent today about digital technologies.”
Reconsidering Technical Labor in Information Institutions: The Case of Analog Video Digitization
Zack Lischer-Katz
Library Trends, Volume 68, Number 2, Fall 2019, pp. 213-251 (Article)
empirical study conducted by the author from 2015–2017 that used qualitative-interpretive methods to study the discursive and material practices of professional media preservationists as they worked to digitize analog video recordings in small-scale, high-quality (“artisanal”) digitization projects
p. 215 Furthermore, understanding technical work in li-braries can contribute to ongoing debates in information studies and the digital humanities on the relationship between “doing” and “signifying” in terms of scholarly production (Cecire 2011)
In opposing the @clarivate acquisition of @ProQuest, @SPARC_NA asserts three major claims. (1) An “effective monopoly” on library systems raises concerns about anti-competitive practices; [PDF: https://t.co/tnaFQFcGiB ]
“Clarivate may…portray the merger as increasing competition by creating a strong challenger to Elsevier…[but] these two emerging platform monopolies are likely to…drive out…weaker competitors, creating a duopoly between Clarivate & Elsevier.”
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More on academic library in this blog https://blog.stcloudstate.edu/ims?s=Academic+library
Part of the Debates in the Digital Humanities Series A book series from the University of Minnesota Press Matthew K. Gold and Lauren F. Klein, Series Editors
Defintion
Critical infrastructure studies has emerged as a framework for linking thought on the complex relations between society and its material structures across fields such as science and technology studies, design, ethnography, media infrastructure studies, feminist theory, critical race and ethnicity studies, postcolonial studies, environmental studies, animal studies, literary studies, the creative arts, and others (see the CIstudies.org Bibliography )
An informal consensus seems to have emerged that if students in the humanities are going to make use of quantitative methods, they should probably first learn to program. Introductions to this dimension of the field are organized around programming languages: The Programming Historian is built around an introduction to Python; Matthew Jockers’s Text Analysis with R is at its heart a tutorial in the R language; Taylor Arnold and Lauren Tilton’s Humanities Data in R begins with chapters on the language; Folgert Karsdorp’s Python Programming for the Humanities is a course in the language with examples from stylometry and information retrieval.[11] “On the basis of programming,” writes Moretti in “Literature, Measured,” a recent retrospective on the work of his Literary Lab, “much more becomes possible”
programming competence is not equivalent to competence in analytical methods. It might allow students to prepare data for some future analysis and to produce visual, tabular, numerical, or even interactive summaries; Humanities Data in R gives a fuller survey of the possibilities of exploratory data analysis than the other texts.[15]Yet students who have focused on programming will have to rely on their intuition when it comes to interpreting exploratory results. Intuition gives only a weak basis for arguing about whether apparent trends, groupings, or principles of variation are supported by the data.
From Humanities to Scholarship: Librarians, Labor, and the Digital
First hired as a “digital humanities librarian,” I saw my title changed within less than a year to “digital scholarship librarian,” with a subject specialty later appended (American History). Some three-plus years later at a different institution, I now find myself a digital-less “religion and theology librarian.” At the same time, in this position, my experience and expertise in digital humanities (or “digital scholarship”) are assumed, and any associated duties are already baked into the job description itself.
Jonathan Senchyne has written about the need to reimagine library and information science graduate education and develop its capacity to recognize, accommodate, and help train future library-based digital humanists in both computational research methods and discipline-focused humanities content (368–76). However, less attention has been paid to tracking where these digital humanities and digital scholarship librarians come from, the consequences and opportunities that arise from sourcing librarians from multiple professional and educational stations, and the more ontological issues associated with the nature of their labor—that is, what is understood as work for the digital humanist in the library and what librarians could be doing.
ExLibris Report: “Exploring the Challenges of Researchers and Research Offices”
COVID-19 has affected research funding significantly, with STEM fields seeing an increase in funding, while in the humanities, social sciences, and arts, funding is declining.
Funding remains a key challenge for researchers.
The showcasing of research and expertiseis increasing inimportance
Research office members and researchers differ in the way in which they measure research impact.
The administrative burden on researchers continues to be a major challenge. Seven out of 10 researchers spend at least 30% of their time on administrative tasks. The core expertise of libraries and research offices is still underutilized.
Interdisciplinary collaboration is high on researchers’ agenda, with 37% of researchers saying that most or all of their work involves interdisciplinary collaboration. This figure aligns somewhat with research office priorities; 25% of research office leaders stated that promoting interdisciplinary collaboration is a priority.
Researchers expect more from their library than in 2020. Although 61% of researchers expressed satisfaction with the support they receive from their institution’s library, they expect more assistance than in 2020, especially with data-related services and services such as publication depositing.
Collaboration between research offices and libraries has risen in 2021.
an interdisciplinary group of librarians and researchers from Virginia Tech, Indiana University, and the University of Oklahoma convened to develop a series of three national forums on this topic, funded by the Institute for Museum and Library Services (IMLS), as a project titled Developing Library Strategy for 3D and Virtual Reality Collection Development and Reuse (LIB3DVR) [8]
in addition to these ethical and legal concerns, there are also intellectual property issues identified that could impact how VR content is used in the future.
3.Participants identified a range of possible preservation strategies for dealing with these challenges and preservation considerations. Selection and documentation were seen as important activities for ensuring the long-term preservation of 3D/VR content.
Acquisitions and partnerships are a cornerstone of Byju’s early learning programs: It bought Palo Alto-based Osmo in 2019, which combines digital learning with manipulatives, an approach the companies call “phygital.” For instance: Using a tablet’s camera and Osmo’s artificial intelligence software, the system tracks what a child is doing on a (physical) worksheet and responds accordingly to right and wrong answers. “It’s almost like having a teacher looking over you, My note: this can be come disastrous when combined with the China’s “social credit” system.
By contrast, Byju’s FutureSchool (launched in the U.S. this past spring) aims to offer one-to-one tutoring sessions starting with coding (based in part on WhiteHat Jr., which it acquired in August 2020) and eventually including music, fine arts and English to students in the U.S., Brazil, the U.K., Indonesia and others. The company has recruited 11,000 teachers in India to staff the sessions
In mid-July, Byju’s bought California-based reading platform Epic for $500 million. That product opens up a path for Byju’s to schools. Epic offers a digital library of more than 40,000 books for students ages 12 and under. Consumers pay about $80 a year for the library. It’s free to schools. Epic says that more than 1 million teachers in 90 percent of U.S. elementary schools have signed up for accounts.
That raises provocative questions for U.S. educators. Among them:
How will products originally developed for the consumer market fit the needs of schools, particularly those that serve disadvantaged students?
Will there be more development dollars poured into products that appeal to consumers—and less into products that consumers typically skip (say, middle school civics or history curriculum?)
How much of an investment will giants such as Byju’s put into researching the effectiveness of its products? In the past most consumers have been less concerned than professional educators about the “research” behind the learning products they buy. Currently Gokulnath says the company most closely tracks metrics such as “engagement” (how much time students spend on the product) and “renewals” (how many customers reup after a year’s use of the product.)
How will products designed for home users influence parents considering whether to continue to school at home in the wake of viral pandemics?
AI is being used to monitor students and their work. The most prominent uses of AI in higher education are attached to applications designed to protect or preserve academic integrity through the use of plagiarism-detection software (60%) and proctoring applications (42%) (see figure 1).
The chatbots are coming! A sizable percentage (36%) of respondents reported that chatbots and digital assistants are in use at least somewhat on their campuses, with another 17% reporting that their institutions are in the planning, piloting, and initial stages of use (see figure 2). The use of chatbots in higher education by admissions, student affairs, career services, and other student success and support units is not entirely new, but the pandemic has likely contributed to an increase in their use as they help students get efficient, relevant, and correct answers to their questions without long waits.Footnote10 Chatbots may also liberate staff from repeatedly responding to the same questions and reduce errors by deploying updates immediately and universally.
AI is being used for student success tools such as identifying students who are at-risk academically (22%) and sending early academic warnings (16%); another 14% reported that their institutions are in the stage of planning, piloting, and initial usage of AI for these tasks.
Nearly three-quarters of respondents said that ineffective data management and integration (72%) and insufficient technical expertise (71%) present at least a moderate challenge to AI implementation. Financial concerns (67%) and immature data governance (66%) also pose challenges. Insufficient leadership support (56%) is a foundational challenge that is related to each of the previous listed challenges in this group.
Current use of AI
Chatbots for informational and technical support, HR benefits questions, parking questions, service desk questions, and student tutoring
Research applications, conducting systematic reviews and meta-analyses, and data science research (my italics)
Library services (my italics)
Recruitment of prospective students
Providing individual instructional material pathways, assessment feedback, and adaptive learning software
Proctoring and plagiarism detection
Student engagement support and nudging, monitoring well-being, and predicting likelihood of disengaging the institution