Nearly 200 colleges face federal civil rights investigations opened in 2019 about whether they are accessible and communicate effectively to people with disabilities.
As a result, colleges are rolling out social media accessibility standards and training communications staff members to take advantage of built-in accessibility tools in platforms including YouTube, Facebook and Twitter.
For example, last fall, a blind man filed 50 lawsuits against colleges whose websites he said didn’t work with his screen reader. And on August 21, in Payan v. Los Angeles Community College District, the Federal District Court for the Central District of California ruled that Los Angeles Community College failed to provide a blind student with “meaningful access to his course materials” via MyMathLab, software developed by Pearson, in a timely manner.
California State University at Long Beach, for instance, advises posting main information first and hashtags last to make messages clear for people using screen readers. The University of Minnesota calls for indicating whether hyperlinks point to [AUDIO], [PIC], or [VIDEO]. This summer, leaders at the College of William & Mary held a training workshopfor the institution’s communications staff in response to an Office for Civil Rights investigation.
at a session on the umbrella concept of “mixed reality” (abbreviated XR) here Thursday, attendees had some questions for the panel’s VR/AR/XR evangelists: Can these tools help students learn? Can institutions with limited budgets pull off ambitious projects? Can skeptical faculty members be convinced to experiment with unfamiliar technology?
Yale has landed on a “hub model” for project development — instructors propose projects and partner with students with technological capabilities to tap into a centralized pool of equipment and funding. (My note: this is what I suggest in my Chapter 2 of Arnheim, Eliot & Rose (2012) Lib Guides)
Several panelists said they had already been getting started on mixed reality initiatives prior to the infusion of support from Educause and HP, which helped them settle on a direction
While 3-D printing might seem to lend itself more naturally to the hard sciences, Yale’s humanities departments have cottoned to the technology as a portal to answering tough philosophical questions.
institutions would be better served forgoing an early investment in hardware and instead gravitating toward free online products like Unity, Organon and You by Sharecare, all of which allow users to create 3-D experiences from their desktop computers.
XR technologies encompassing 3D simulations, modeling, and production.
This project sought to identify
current innovative uses of these 3D technologies,
how these uses are currently impacting teaching and learning, and
what this information can tell us about possible future uses for these technologies in higher education.
p. 5 Extended reality (XR) technologies, which encompass virtual reality (VR) and augmented reality (AR), are already having a dramatic impact on pedagogy in higher education. XR is a general term that covers a wide range of technologies along a continuum, with the real world at one end and fully immersive simulations at the other.
p. 6The Campus of the Future project was an exploratory evaluation of 3D technologies for instruction and research in higher education: VR, AR, 3D scanning, and 3D printing. The project sought to identify interesting and novel uses of 3D technology
p. 7 HP would provide the hardware, and EDUCAUSE would provide the methodological expertise to conduct an evaluation research project investigating the potential uses of 3D technologies in higher education learning and research.
The institutions that participated in the Campus of the Future project were selected because they were already on the cutting edge of integrating 3D technology into pedagogy. These institutions were therefore not representative, nor were they intended to be representative, of the state of higher education in the United States. These institutions were selected precisely because they already had a set of use cases for 3D technology available for study
p. 9 At some institutions, the group participating in the project was an academic unit (e.g., the Newhouse School of Communications at Syracuse University; the Graduate School of Education at Harvard University). At these institutions, the 3D technology provided by HP was deployed for use more or less exclusively by students and faculty affiliated with the particular academic unit.
p. 10 definitions
there is not universal agreement on the definitions of these
terms or on the scope of these technologies. Also, all of these technologies
currently exist in an active marketplace and, as in many rapidly changing markets, there is a tendency for companies to invent neologisms around 3D technology.
A 3D scanner is not a single device but rather a combination of hardware and
software. There are generally two pieces of hardware: a laser scanner and a digital
camera. The laser scanner bounces laser beams off the surface of an object to
determine its shape and contours.
p. 11 definitions
Virtual reality means that the wearer is completely immersed in a computer
simulation. Several types of VR headsets are currently available, but all involve
a lightweight helmet with a display in front of the eyes (see figure 2). In some
cases, this display may simply be a smartphone (e.g., Google Cardboard); in other
cases, two displays—one for each eye—are integrated into the headset (e.g., HTC
Vive). Most commercially available VR rigs also include handheld controllers
that enable the user to interact with the simulation by moving the controllers
in space and clicking on finger triggers or buttons.
p. 12 definitions
Augmented reality provides an “overlay” of some type over the real world through
the use of a headset or even a smartphone.
In an active technology marketplace, there is a tendency for new terms to be
invented rapidly and for existing terms to be used loosely. This is currently
happening in the VR and AR market space. The HP VR rig and the HTC Vive
unit are marketed as being immersive, meaning that the user is fully immersed in
a simulation—virtual reality. Many currently available AR headsets, however, are
marketed not as AR but rather as MR (mixed reality). These MR headsets have a
display in front of the eyes as well as a pair of front-mounted cameras; they are
therefore capable of supporting both VR and AR functionality.
p. 13 Implementation
Technical difficulties.
Technical issues can generally be divided into two broad categories: hardware
problems and software problems. There is, of course, a common third category:
human error.
p. 15 the technology learning curve
The well-known diffusion of innovations theoretical framework articulates five
adopter categories: innovators, early adopters, early majority, late majority, and
laggards. Everett M. Rogers, Diffusion of Innovations, 5th ed. (New York: Simon and Schuster, 2003).
It is also likely that staff in the campus IT unit or center for teaching and learning already know who (at least some of) these individuals are, since such faculty members are likely to already have had contact with these campus units.
Students may of course also be innovators and early adopters, and in fact
several participating institutions found that some of the most creative uses of 3D technology arose from student projects
p. 30 Zeynep Tufekci, in her book Twitter and Tear Gas
definition: There is no necessary distinction between AR and VR; indeed, much research
on the subject is based on a conception of a “virtuality continuum” from entirely
real to entirely virtual, where AR lies somewhere between those ends of the
spectrum. Paul Milgram and Fumio Kishino, “A Taxonomy of Mixed Reality Visual Displays,” IEICE Transactions on Information Systems, vol. E77-D, no. 12 (1994); Steve Mann, “Through the Glass, Lightly,” IEEE Technology and Society Magazine 31, no. 3 (2012): 10–14.
For the future of 3D technology in higher education to be realized, that
technology must become as much a part of higher education as any technology:
the learning management system (LMS), the projector, the classroom. New
technologies and practices generally enter institutions of higher education as
initiatives. Several active learning classroom initiatives are currently under
way,36 for example, as well as a multi-institution open educational resources
(OER) degree initiative.37
p. 32 Storytelling
Some scholars have argued that all human communication
is based on storytelling;41 certainly advertisers have long recognized that
storytelling makes for effective persuasion,42 and a growing body of research
shows that narrative is effective for teaching even topics that are not generally
thought of as having a natural story, for example, in the sciences.43
p. 33 accessibility
The experience of Gallaudet University highlights one of the most important
areas for development in 3D technology: accessibility for users with disabilities.
p. 34 instructional design
For that to be the case, 3D technologies must be incorporated into the
instructional design process for building and redesigning courses. And for that
to be the case, it is necessary for faculty and instructional designers to be familiar
with the capabilities of 3D technologies. And for that to be the case, it may not be necessary but would certainly be helpful for instructional designers to collaborate closely with the staff in campus IT units who support and maintain this hardware.
Every institution of higher education has a slightly different organizational structure, of course, but these two campus units are often siloed. This siloing may lead to considerable friction in conducting the most basic organizational tasks, such as setting up meetings and apportioning responsibilities for shared tasks. Nevertheless, IT units and centers for teaching and learning are almost compelled to collaborate in order to support faculty who want to integrate 3D technology into their teaching. It is necessary to bring the instructional design expertise of a center for teaching and learning to bear on integrating 3D technology into an instructor’s teaching (My note: and where does this place SCSU?) Therefore, one of the most critical areas in which IT units and centers for teaching and learning can collaborate is in assisting instructors to develop this integration and to develop learning objects that use 3D technology. p. 35 For 3D technology to really gain traction in higher education, it will need to be easier for instructors to deploy without such a large support team.
p. 35 Sites such as Thingiverse, Sketchfab, and Google Poly are libraries of freely
available, user-created 3D models.
ClassVR is a tool that enables the simultaneous delivery of a simulation to
multiple headsets, though the simulation itself may still be single-user.
p. 37 data management:
An institutional repository is a collection of an institution’s intellectual output, often consisting of preprint journal articles and conference papers and the data sets behind them.49 An institutional repository is often maintained by either the library or a partnership between the library and the campus IT unit. An institutional repository therefore has the advantage of the long-term curatorial approach of librarianship combined with the systematic backup management of the IT unit. (My note: leaves me wonder where does this put SCSU)
Sharing data sets is critical for collaboration and increasingly the default for
scholarship. Data is as much a product of scholarship as publications, and there
is a growing sentiment among scholars that it should therefore be made public.50
https://www-wired-com.cdn.ampproject.org/c/s/www.wired.com/story/187-things-the-blockchain-is-supposed-to-fix/amp
Blockchains, which use advanced cryptography to store information across networks of computers, could eliminate the need for trusted third parties, like banks, in transactions, legal agreements, and other contracts. The most ardent blockchain-heads believe it has the power to reshape the global financial system, and possibly even the internet as we know it.
Now, as the technology expands from a fringe hacker toy to legitimate business applications, opportunists have flooded the field. Some of the seekers are mercenaries pitching shady or fraudulent tokens, others are businesses looking to cash in on a hot trend, and still others are true believers in the revolutionary and disruptive powers of distributed networks.
Mentions of blockchains and digital currencies on corporate earnings calls doubled in 2017 over the year prior, according to Fortune. Last week at Consensus, the country’s largest blockchain conference, 100 sponsors, including top corporate consulting firms and law firms, hawked their wares.
Here is a noncomprehensive list of the ways blockchain promoters say they will change the world. They run the spectrum from industry-specific (a blockchain project designed to increase blockchain adoption) to global ambitions (fixing the global supply chain’s apparent $9 trillion cash flow issue).
Things Blockchain Technology Will Fix
Bots with nefarious intent
Skynet
People not taking their medicine
Device storage that could be used for bitcoin mining
Can We Please Stop Talking About Generations as if They Are a Thing?
Millennials are not all narcissists and boomers are not inherently selfish. The research on generations is flawed. DAVID COSTANZA
APRIL 13, 2018 9:00 AM
We spend a lot of time debating the characteristics of generations—are baby boomers really selfish and entitled, are millennials really narcissists, and the latest, has the next generation (whatever it is going to be called) already been ruined by cellphones? Many academics—and many consultants—argue that generations are distinct and that organizations, educators, and even parents need to accommodate them. These classifications are often met with resistance from those they supposedly represent, as most people dislike being represented by overgeneralizations, and these disputes only fuel the debate around this contentious topic.
In short, the science shows that generations are not a thing.
It is important to be clear what not a thing means. It does not mean that people today are the same as people 80 years ago or that anything else is static. Times change and so do people. However, the idea that distinct generations capture and represent these changes is unsupported.
What is a generation? Those who promote the concept define it as a group of people who are roughly the same age and who were influenced by a set of significant events. These experiences supposedly create commonalities, making those in the group more similar to each other and more different from other groups now and from groups of the same age in the past.
In line with the definition, there is a commonly held perception that people growing up around the same time and in the same place must have some sort of universally shared set of experiences and characteristics. It helps that the idea of generations intuitively makes sense. But the science does not support it. In fact, most of the research findings showing distinct generations are explained by other causes, have serious scientific flaws, or both.
Numerousbooks, articles, and pundits have claimed that millennials are much more narcissistic than young people in the past.
on average, millennials are no more narcissistic now than Xers or boomers were when they were in their 20s, and one study has even found they might be less so than generations past. While millennials today may be more narcissistic than Xers or boomers are today, that is because young people are pretty narcissistic regardless of when they are young. This too is an age effect.
Final example. Research shows that millennials joining the Army now show more pride in their service than boomers or Xers did when they joined 20-plus years ago. Is this a generational effect? Nope. Everyone in the military now shows more pride on average than 20 years ago because of 9/11. The terrorist attack increased military pride across the board. This is known as a period effect and it doesn’t have anything to do with generations.
Another problem—identifying true generational effects is methodologically very hard. The only way to do it would be to collect data from multiple longitudinal panels. Individuals in the first panel would be measured at the start of the study and then in subsequent years with new panels added every year thereafter, allowing assessment of whether people were changing because they were getting older (age effects), because of what was happening around them (period effects), or because of their generation (cohort effects). Unfortunately, such data sets pretty much do not exist. Thus, we’re never really able to determine why a change occurred.
According to one national-culture model, people from the United States are, on average, relatively individualistic, indulgent, and uncomfortable with hierarchical order. My note: RIchard Nisbett sides with Hofstede and Minkov: https://blog.stcloudstate.edu/ims/2016/06/14/cultural-differences/
Conversely, people from China are generally group-oriented, restrained, and comfortable with hierarchy. However, these countries are so large and diverse that they each have millions of individuals who are more similar to the “averages” of the other country than to their own.
Given these design and data issues, it is not surprising that researchers have tried a variety of different statistical techniques to massage (aka torture) the data in an attempt to find generational differences. Studies showing generational differences have used statistical techniques like analysis of variance (ANOVA) and cross-temporal meta-analysis (CTMA), neither of which is capable of actually attributing the differences to generations.
The statistical challenge derives from the problem we have already raised—generations (i.e., cohorts) are defined by age and period. As such, mathematically separating age, period, and cohort effects is very difficult because they are inherently confounded with one another. Their linear dependency creates what is known as an identification problem, and unless one has access to multiple longitudinal panels like I described above, it is impossible to statistically isolate the unique effect of any one factor.
Are some millennials narcissistic? Are some boomers selfish? Sure, but there are many who are not and whose profiles mirror othergenerations.
First, relying on flawed generational science leads to poor advice and bad decisions. An analogy: Women live longer than men, on average. Why? They engage in fewer risky behaviors, take better care of themselves, and have two X chromosomes, giving them backups in case of mutations. But if you are a man and you go to the doctor and ask how to live longer, she doesn’t tell you, “Be a woman.” She says eat better, exercise, and don’t do stupid stuff. Knowing the why guides the recommendation.
Now imagine you are a manager trying to retain your supposedly job-hopping, commitment-averse millennial employees and you know that Xers and boomers are less likely to leave their jobs. If you are that manager, you wouldn’t tell your millennial employees to “be a boomer” or “grow older” (nor would you decide to hire boomers or Xers rather than millennials—remember that individuals vary within populations). Instead, you should focus on addressing benefits, work conditions, and other factors that are reasons for leaving.
Second, this focus on generational distinctions wastes resources. Take the millennials-as-commitment-averse-job-hoppers stereotype. Based on this belief, consultants sell businesses on how to recruit and retain this mercurial generation. But are all (or even most) millennials job-hopping commitment avoiders? Survey research shows that millennials and Xers at the same point in their careers are equally likely to stay with their current employer for five or more years (22 percent v. 21.8 percent). It makes no sense for organizations to spend time and money changing HR policies when employees are just as likely to stick around today as they were 15 years ago.
Third, generations perpetuate stereotyping. Ask millennials if they are narcissistic job-hoppers and most of them will rightly be offended. Treat boomers like materialistic achievement seekers and see how it affects their work quality and commitment. We finally are starting to recognize that those within any specific group of people are varied individuals, and we should remember those same principles in this context too. We are (mostly) past it being acceptable to stereotype and discriminate against women, minorities, and the disabled. Why is it OK to do so to millennials or boomers?
The solutions are fairly straightforward, albeit challenging, to implement. To start, we need to focus on the why when talking about whether groups of people differ. The reasons why any generation should be different have only been generally discussed, and the theoretical mechanism that supposedly creates generations has not been fully fleshed out.
Next, we need to quit using these nonsensical generations labels, because they don’t mean anything. The start and end years are somewhat arbitrary anyway. The original conceptualization of social generations started with a biological generational interval of about 20 years, which historians, sociologists and demographers (for one example, see Strauss and Howe, 1991) then retrofitted with various significant historical events that defined the period.
The problem with this is twofold. First, such events do not occur in nice, neat 20-year intervals. Second, not everyone agrees on what the key events were for each generation, so the start and end dates also move around depending on what people think they were. One review found that start and end dates for boomers, Xers, and millennials varied by as many as nine years, and often four to five, depending on the study and the researcher. As with the statistical problem, how can distinct generations be a thing if simply defining when they start and when they end varies so much from study to study?
In the end, the core scientific problem is that the pop press, consultants, and even some academics who are committed to generations don’t focus on the whys. They have a vested interest in selling the whats(Generation Me has reportedly sold more than 115,000 copies, and Google “generations consultants” and see how many firms are dedicated to promulgating these distinctions), but without the science behind them, any prescriptions are worthless or even harmful
David Costanza is an associate professor of organizational sciences at George Washington University and a senior consortium fellow for the U.S. Army Research Institute. He researches, teaches, and consults in the areas of generations, leadership, culture, and organizational performance.
Guardtime – This company is creating “keyless” signature systems using blockchain which is currently used to secure the health records of one million Estonian citizens.
REMME is a decentralized authentication system which aims to replace logins and passwords with SSL certificates stored on a blockchain.
Healthcare
Gem – This startup is working with the Centre for Disease Control to put disease outbreak data onto a blockchain which it says will increase the effectiveness of disaster relief and response.
SimplyVital Health – Has two health-related blockchain products in development, ConnectingCare which tracks the progress of patients after they leave the hospital, and Health Nexus, which aims to provide decentralized blockchain patient records.
MedRec – An MIT project involving blockchain electronic medical records designed to manage authentication, confidentiality and data sharing.
Financial services
ABRA – A cryptocurrency wallet which uses the Bitcoin blockchain to hold and track balances stored in different currencies.
Bank Hapoalim – A collaboration between the Israeli bank and Microsoft to create a blockchain system for managing bank guarantees.
Barclays – Barclays has launched a number of blockchain initiatives involving tracking financial transactions, compliance and combating fraud. It states that “Our belief …is that blockchain is a fundamental part of the new operating system for the planet.”
Maersk – The shipping and transport consortium has unveiled plans for a blockchain solution for streamlining marine insurance.
Aeternity – Allows the creation of smart contracts which become active when network consensus agrees that conditions have been met – allowing for automated payments to be made when parties agree that conditions have been met, for example.
Augur – Allows the creation of blockchain-based predictions markets for the trading of derivatives and other financial instruments in a decentralized ecosystem.
Manufacturing and industrial
Provenance – This project aims to provide a blockchain-based provenance record of transparency within supply chains.
Jiocoin – India’s biggest conglomerate, Reliance Industries, has said that it is developing a blockchain-based supply chain logistics platform along with its own cryptocurrency, Jiocoin.
Hijro – Previously known as Fluent, aims to create a blockchain framework for collaborating on prototyping and proof-of-concept.
SKUChain – Another blockchain system for allowing tracking and tracing of goods as they pass through a supply chain.
Blockverify – A blockchain platform which focuses on anti-counterfeit measures, with initial use cases in the diamond, pharmaceuticals and luxury goods markets.
Transactivgrid – A business-led community project based in Brooklyn allowing members to locally produce and cell energy, with the goal of reducing costs involved in energy distribution.
STORJ.io – Distributed and encrypted cloud storage, which allows users to share unused hard drive space.
Government
Dubai – Dubai has set sights on becoming the world’s first blockchain-powered state. In 2016 representatives of 30 government departments formed a committee dedicated to investigating opportunities across health records, shipping, business registration and preventing the spread of conflict diamonds.
Estonia – The Estonian government has partnered with Ericsson on an initiative involving creating a new data center to move public records onto the blockchain. 20
South Korea – Samsung is creating blockchain solutions for the South Korean government which will be put to use in public safety and transport applications.
Govcoin – The UK Department of Work and Pensions is investigating using blockchain technology to record and administer benefit payments.
Democracy.earth – This is an open-source project aiming to enable the creation of democratically structured organizations, and potentially even states or nations, using blockchain tools.
Followmyvote.com – Allows the creation of secure, transparent voting systems, reducing opportunities for voter fraud and increasing turnout through improved accessibility to democracy.
Charity
Bitgive – This service aims to provide greater transparency to charity donations and clearer links between giving and project outcomes. It is working with established charities including Save The Children, The Water Project and Medic Mobile.
Retail
OpenBazaar – OpenBazaar is an attempt to build a decentralized market where goods and services can be traded with no middle-man.
Loyyal – This is a blockchain-based universal loyalty framework, which aims to allow consumers to combine and trade loyalty rewards in new ways, and retailers to offer more sophisticated loyalty packages.
Blockpoint.io – Allows retailers to build payment systems around blockchain currencies such as Bitcoin, as well as blockchain derived gift cards and loyalty schemes.
Real Estate
Ubiquity – This startup is creating a blockchain-driven system for tracking the complicated legal process which creates friction and expense in real estate transfer.
Transport and Tourism
IBM Blockchain Solutions – IBM has said it will go public with a number of non-finance related blockchain initiatives with global partners in 2018. This video envisages how efficiencies could be driven in the vehicle leasing industry.
Arcade City – An application which aims to beat Uber at their own game by moving ride sharing and car hiring onto the blockchain.
La’Zooz – A community-owned platform for synchronizing empty seats with passengers in need of a lift in real-time.
Webjet – The online travel portal is developing a blockchain solution to allow stock of empty hotel rooms to be efficiently tracked and traded, with payment fairly routed to the network of middle-men sites involved in filling last-minute vacancies.
Media
Kodak – Kodak recently sent its stock soaring after announcing that it is developing a blockchain system for tracking intellectual property rights and payments to photographers.
Ujomusic – Founded by singer-songwriter Imogen Heap to record and track royalties for musicians, as well as allowing them to create a record of ownership of their work.
It is exciting to see all these developments. I am sure not all of these will make it into successful long-term ventures but if they indicate one thing, then it is the vast potential the blockchain technology is offering.
what is shall and what does it do. language close to computers, fast.
what is “bash” . cd, ls
shell job is a translator between the binory code, the middle name. several types of shells, with slight differences. one natively installed on MAC and Unix. born-again shell
bash commands: cd change director, ls – list; ls -F if it does not work: man ls (manual for LS); colon lower left corner tells you can scrool; q for escape; ls -ltr
arguments is colloquially used with different names. options, flags, parameters
cd .. – move up one directory . pwd : see the content cd data_shell/ – go down one directory
cd ~ – brings me al the way up . $HOME (universally defined variable
the default behavior of cd is to bring to home directory.
the core shall commands accept the same shell commands (letters)
$ du -h . gives me the size of the files. ctrl C to stop
$ clear . – clear the entire screen, scroll up to go back to previous command
man history $ history $! pwd (to go to pwd . $ history | grep history (piping)
$ cat (and the file name) – standard output
$ cat ../
+++++++++++++++
how to edit and delete files
to create new folder: $ mkdir . – make directory
text editors – nano, vim (UNIX text editors) . $ nano draft.txt . ctrl O (save) ctr X (exit) .
$ vim . shift esc (key) and in command line – wq (write quit) or just “q”
$ mv draft.txt ../data . (move files)
to remove $ rm thesis/: $ man rm
copy files $cp $ touch . (touches the file, creates if new)
C and C++. scripting purposes in microbiology (instructor). libraries, packages alongside Python, which can extend its functionality. numpy and scipy (numeric and science python). Python for academic libraries?
going out of python $ quit () . python expect beginning and end parenthesis
new terminal needed after installation. anaconda 5.0.1
python 3 is complete redesign, not only an update.
python is object oriented and i can define the objects
python creates its own types of objects (which we model) and those are called “DataFrame”
method applied it is an attribute to data that already exists. – difference from function
data.info() . is function – it does not take any arguments
whereas
data.columns . is a method
print (data.T) . transpose. not easy in Excel, but very easy in Python
data = pandas.read_csv(‘/Users/plamen_local/Desktop/data/gapminder_gdp_oceania.csv’ , index_col=’country’)
data.loc[‘Australia’].plot()
plt.xticks(rotation=10)
GD plot 2 is the most well known library.
xelatex is a PDF engine. reST restructured text like Markdown. google what is the best PDF engine with Jupyter
four loops . any computer language will have the concept of “for” loop. In Python: 1. whenever we create a “for” loop, that line must end with a single colon
2. indentation. any “if” statement in the “for” loop, gets indented
metadata: counts of papers by yer, researcher, institution, province, region and country. scientific fields subfields
metadata in one-credit course as a topic:
publisher – suppliers =- Elsevier processes – Scopus Data
h-index: The h-index is an author-level metric that attempts to measure both the productivity and citation impact of the publications of a scientist or scholar. The index is based on the set of the scientist’s most cited papers and the number of citations that they have received in other publications.
The era of e-science demands new skill sets and competencies of researchers to ensure their work is accessible, discoverable and reusable. Librarians are naturally positioned to assist in this education as part of their liaison and information literacy services.
Research data literacy and the library
Christian Lauersen, University of Copenhagen; Sarah Wright, Cornell University; Anita de Waard, Elsevier
Data Literacy: access, assess, manipulate, summarize and present data
Statistical Literacy: think critically about basic stats in everyday media
Information Literacy: think critically about concepts; read, interpret, evaluate information
data information literacy: the ability to use, understand and manage data. the skills needed through the whole data life cycle.
Shield, Milo. “Information literacy, statistical literacy and data literacy.” I ASSIST Quarterly 28. 2/3 (2004): 6-11.
Carlson, J., Fosmire, M., Miller, C. C., & Nelson, M. S. (2011). Determining data information literacy needs: A study of students and research faculty. Portal: Libraries & the Academy, 11(2), 629-657.
embedded librarianship,
Courses developed: NTRESS 6600 research data management seminar. six sessions, one-credit mini course
NEW ROLESFOR LIbRARIANS: DATAMANAgEMENTAND CURATION
the capacity to manage and curate research data has not kept pace with the ability to produce them (Hey & Hey, 2006). In recognition of this gap, the NSF and other funding agencies are now mandating that every grant proposal must include a DMP (NSF, 2010). These mandates highlight the benefits of producing well-described data that can be shared, understood, and reused by oth-ers, but they generally offer little in the way of guidance or instruction on how to address the inherent issues and challenges researchers face in complying. Even with increasing expecta-tions from funding agencies and research com-munities, such as the announcement by the White House for all federal funding agencies to better share research data (Holdren, 2013), the lack of data curation services tailored for the “small sciences,” the single investigators or small labs that typically comprise science prac-tice at universities, has been identified as a bar-rier in making research data more widely avail-able (Cragin, Palmer, Carlson, & Witt, 2010).Academic libraries, which support the re-search and teaching activities of their home institutions, are recognizing the need to de-velop services and resources in support of the evolving demands of the information age. The curation of research data is an area that librar-ians are well suited to address, and a num-ber of academic libraries are taking action to build capacity in this area (Soehner, Steeves, & Ward, 2010)
REIMAgININg AN ExISTINg ROLEOF LIbRARIANS: TEAChINg INFORMATION LITERACY SkILLS
By combining the use-based standards of information literacy with skill development across the whole data life cycle, we sought to support the practices of science by develop-ing a DIL curriculum and providing training for higher education students and research-ers. We increased ca-pacity and enabled comparative work by involving several insti-tutions in developing instruction in DIL. Finally, we grounded the instruction in the real-world needs as articu-lated by active researchers and their students from a variety of fields
Chapter 1 The development of the 12 DIL competencies is explained, and a brief compari-son is performed between DIL and information literacy, as defined by the 2000 ACRL standards.
chapter 2 thinking and approaches toward engaging researchers and students with the 12 competencies, a re-view of the literature on a variety of educational approaches to teaching data management and curation to students, and an articulation of our key assumptions in forming the DIL project.
chapter 4 because these lon-gitudinal data cannot be reproduced, acquiring the skills necessary to work with databases and to handle data entry was described as essential. Interventions took place in a classroom set-ting through a spring 2013 semester one-credit course entitled Managing Data to Facilitate Your Research taught by this DIL team.
chapter 5 embedded librar-ian approach of working with the teaching as-sistants (TAs) to develop tools and resources to teach undergraduate students data management skills as a part of their EPICS experience.
Lack of organization and documentation presents a bar-rier to (a) successfully transferring code to new students who will continue its development, (b) delivering code and other project outputs to the community client, and (c) the center ad-ministration’s ability to understand and evalu-ate the impact on student learning.
skill sessions to deliver instruction to team lead-ers, crafted a rubric for measuring the quality of documenting code and other data, served as critics in student design reviews, and attended student lab sessions to observe and consult on student work
chapter 6 Although the faculty researcher had created formal policies on data management practices for his lab, this case study demonstrated that students’ adherence to these guidelines was limited at best. Similar patterns arose in discus-sions concerning the quality of metadata. This case study addressed a situation in which stu-dents are at least somewhat aware of the need to manage their data;
chapter 7 University of Minnesota team to design and implement a hybrid course to teach DIL com-petencies to graduate students in civil engi-neering.
stu-dents’ abilities to understand and track issues affecting the quality of the data, the transfer of data from their custody to the custody of the lab upon graduation, and the steps neces-sary to maintain the value and utility of the data over time.
This project was launched because there is a lack of consensus across the field about how to define digital literacy and implement effective programs. A survey was disseminated throughout the NMC community of higher education leaders and practitioners to understand how digital literacy initiatives are impacting their campuses. The NMC’s research examines the current landscape to illuminate multiple models of digital literacy — universal literacy, creative literacy, and literacy across disciplines — around which dedicated programs can proliferate a spectrum of skills and competencies.
p. 8-10 examples across US universities on digital literacy organization
p. 12 Where does support for digital literacy come from your institution? Individual people
p. 13. campus libraries must be deeply embedded in course curriculum. While libraries have always supported academic institutions, librarians can play a more critical role in the development of digital literacy skills. Historically, these types of programs have been implemented in “one-off” segments, which are experienced apart from a student’s normal studies and often delivered in a one-size-fits-all method. However, an increasing number of academic libraries are supporting a more integrated approach that delivers continuous skill development and assessment over time to both students and faculty. This requires deeper involvement with departments and agreeing on common definitions of what capacities should be achieved, and the most effective pedagogical method. Librarians are tasked with broadening their role in the co-design of curriculum and improving their instruction techniques to work alongside faculty toward the common goal of training students to be savvy digital researchers. University of Arizona Libraries, for example, found that a key step in this transition required collaborating on a common instructional philosophy.