Searching for "social media policies"

ELI 2018 Key Issues Teaching Learning

Key Issues in Teaching and Learning

A roster of results since 2011 is here.

ELI 2018 key issues

1. Academic Transformation

2. Accessibility and UDL

3. Faculty Development

4. Privacy and Security

5. Digital and Information Literacies
Three Models of Digital Literacy: Universal, Creative, Literacy Across Disciplines

United States digital literacy frameworks tend to focus on educational policy details and personal empowerment, the latter encouraging learners to become more effective students, better creators, smarter information consumers, and more influential members of their community.

National policies are vitally important in European digital literacy work, unsurprising for a continent well populated with nation-states and struggling to redefine itself, while still trying to grow economies in the wake of the 2008 financial crisis and subsequent financial pressures

African digital literacy is more business-oriented.

Middle Eastern nations offer yet another variation, with a strong focus on media literacy. As with other regions, this can be a response to countries with strong state influence or control over local media. It can also represent a drive to produce more locally-sourced content, as opposed to consuming material from abroad, which may elicit criticism of neocolonialism or religious challenges.

p. 14 Digital literacy for Humanities: What does it mean to be digitally literate in history, literature, or philosophy? Creativity in these disciplines often involves textuality, given the large role writing plays in them, as, for example, in the Folger Shakespeare Library’s instructor’s guide. In the digital realm, this can include web-based writing through social media, along with the creation of multimedia projects through posters, presentations, and video. Information literacy remains a key part of digital literacy in the humanities. The digital humanities movement has not seen much connection with digital literacy, unfortunately, but their alignment seems likely, given the turn toward using digital technologies to explore humanities questions. That development could then foster a spread of other technologies and approaches to the rest of the humanities, including mapping, data visualization, text mining, web-based digital archives, and “distant reading” (working with very large bodies of texts). The digital humanities’ emphasis on making projects may also increase

Digital Literacy for Business: Digital literacy in this world is focused on manipulation of data, from spreadsheets to more advanced modeling software, leading up to degrees in management information systems. Management classes unsurprisingly focus on how to organize people working on and with digital tools.

Digital Literacy for Computer Science: Naturally, coding appears as a central competency within this discipline. Other aspects of the digital world feature prominently, including hardware and network architecture. Some courses housed within the computer science discipline offer a deeper examination of the impact of computing on society and politics, along with how to use digital tools. Media production plays a minor role here, beyond publications (posters, videos), as many institutions assign multimedia to other departments. Looking forward to a future when automation has become both more widespread and powerful, developing artificial intelligence projects will potentially play a role in computer science literacy.

6. Integrated Planning and Advising Systems for Student Success (iPASS)

7. Instructional Design

8. Online and Blended Learning

In traditional instruction, students’ first contact with new ideas happens in class, usually through direct instruction from the professor; after exposure to the basics, students are turned out of the classroom to tackle the most difficult tasks in learning — those that involve application, analysis, synthesis, and creativity — in their individual spaces. Flipped learning reverses this, by moving first contact with new concepts to the individual space and using the newly-expanded time in class for students to pursue difficult, higher-level tasks together, with the instructor as a guide.

Let’s take a look at some of the myths about flipped learning and try to find the facts.

Myth: Flipped learning is predicated on recording videos for students to watch before class.

Fact: Flipped learning does not require video. Although many real-life implementations of flipped learning use video, there’s nothing that says video must be used. In fact, one of the earliest instances of flipped learning — Eric Mazur’s peer instruction concept, used in Harvard physics classes — uses no video but rather an online text outfitted with social annotation software. And one of the most successful public instances of flipped learning, an edX course on numerical methods designed by Lorena Barba of George Washington University, uses precisely one video. Video is simply not necessary for flipped learning, and many alternatives to video can lead to effective flipped learning environments [].

Myth: Flipped learning replaces face-to-face teaching.

Fact: Flipped learning optimizes face-to-face teaching. Flipped learning may (but does not always) replace lectures in class, but this is not to say that it replaces teaching. Teaching and “telling” are not the same thing.

Myth: Flipped learning has no evidence to back up its effectiveness.

Fact: Flipped learning research is growing at an exponential pace and has been since at least 2014. That research — 131 peer-reviewed articles in the first half of 2017 alone — includes results from primary, secondary, and postsecondary education in nearly every discipline, most showing significant improvements in student learning, motivation, and critical thinking skills.

Myth: Flipped learning is a fad.

Fact: Flipped learning has been with us in the form defined here for nearly 20 years.

Myth: People have been doing flipped learning for centuries.

Fact: Flipped learning is not just a rebranding of old techniques. The basic concept of students doing individually active work to encounter new ideas that are then built upon in class is almost as old as the university itself. So flipped learning is, in a real sense, a modern means of returning higher education to its roots. Even so, flipped learning is different from these time-honored techniques.

Myth: Students and professors prefer lecture over flipped learning.

Fact: Students and professors embrace flipped learning once they understand the benefits. It’s true that professors often enjoy their lectures, and students often enjoy being lectured to. But the question is not who “enjoys” what, but rather what helps students learn the best.They know what the research says about the effectiveness of active learning

Assertion: Flipped learning provides a platform for implementing active learning in a way that works powerfully for students.

9. Evaluating Technology-based Instructional Innovations

Transitioning to an ROI lens requires three fundamental shifts
What is the total cost of my innovation, including both new spending and the use of existing resources?

What’s the unit I should measure that connects cost with a change in performance?

How might the expected change in student performance also support a more sustainable financial model?

The Exposure Approach: we don’t provide a way for participants to determine if they learned anything new or now have the confidence or competence to apply what they learned.

The Exemplar Approach: from ‘show and tell’ for adults to show, tell, do and learn.

The Tutorial Approach: Getting a group that can meet at the same time and place can be challenging. That is why many faculty report a preference for self-paced professional in simple self-assessment checks. We can add prompts that invite people to engage in some sort of follow up activity with a colleague. We can also add an elective option for faculty in a tutorial to actually create or do something with what they learned and then submit it for direct or narrative feedback.

The Course Approach: a non-credit format, these have the benefits of a more structured and lengthy learning experience, even if they are just three to five-week short courses that meet online or in-person once every week or two.involve badges, portfolios, peer assessment, self-assessment, or one-on-one feedback from a facilitator

The Academy Approach: like the course approach, is one that tends to be a deeper and more extended experience. People might gather in a cohort over a year or longer.Assessment through coaching and mentoring, the use of portfolios, peer feedback and much more can be easily incorporated to add a rich assessment element to such longer-term professional development programs.

The Mentoring Approach: The mentors often don’t set specific learning goals with the mentee. Instead, it is often a set of structured meetings, but also someone to whom mentees can turn with questions and tips along the way.

The Coaching Approach: A mentor tends to be a broader type of relationship with a person.A coaching relationship tends to be more focused upon specific goals, tasks or outcomes.

The Peer Approach:This can be done on a 1:1 basis or in small groups, where those who are teaching the same courses are able to compare notes on curricula and teaching models. They might give each other feedback on how to teach certain concepts, how to write syllabi, how to handle certain teaching and learning challenges, and much more. Faculty might sit in on each other’s courses, observe, and give feedback afterward.

The Self-Directed Approach:a self-assessment strategy such as setting goals and creating simple checklists and rubrics to monitor our progress. Or, we invite feedback from colleagues, often in a narrative and/or informal format. We might also create a portfolio of our work, or engage in some sort of learning journal that documents our thoughts, experiments, experiences, and learning along the way.

The Buffet Approach:

10. Open Education

Figure 1. A Model for Networked Education (Credit: Image by Catherine Cronin, building on
Interpretations of
Balancing Privacy and Openness (Credit: Image by Catherine Cronin. CC BY-SA)

11. Learning Analytics

12. Adaptive Teaching and Learning

13. Working with Emerging Technology

In 2014, administrators at Central Piedmont Community College (CPCC) in Charlotte, North Carolina, began talks with members of the North Carolina State Board of Community Colleges and North Carolina Community College System (NCCCS) leadership about starting a CBE program.

Building on an existing project at CPCC for identifying the elements of a digital learning environment (DLE), which was itself influenced by the EDUCAUSE publication The Next Generation Digital Learning Environment: A Report on Research,1 the committee reached consensus on a DLE concept and a shared lexicon: the “Digital Learning Environment Operational Definitions,

Figure 1. NC-CBE Digital Learning Environment

the intellectual dark web

Nuance: A Love Story. My affair with the intellectual dark web

Meghan Daum Aug 24

the standard set of middle-class Democratic Party values: Public safety nets were a force for good, corporate greed was a real threat, civil and reproductive rights were paramount.

I remember how good it felt to stand with my friends in our matching college sweatshirts shouting “never again!” and “my body, my choice!”

(hey, why shouldn’t Sarah Palin call herself a feminist?) brought angry letters from liberals as well as conservatives.

We would all go to the mat for women’s rights, gay rights, or pretty much any rights other than gun rights. We lived, for the most part, in big cities in blue states.

When Barack Obama came into the picture, we loved him with the delirium of crushed-out teenagers, perhaps less for his policies than for being the kind of person who also listens to NPR. We loved Hillary Clinton with the fraught resignation of a daughter’s love for her mother. We loved her even if we didn’t like her. We were liberals, after all. We were family.

Words like “mansplaining” and “gaslighting” were suddenly in heavy rotation, often invoked with such elasticity as to render them nearly meaningless. Similarly, the term “woke,” which originated in black activism, was being now used to draw a bright line between those on the right side of things and those on the wrong side of things.

From the Black Guys on Bloggingheads, YouTube’s algorithms bounced me along a path of similarly unapologetic thought criminals: the neuroscientist Sam Harris and his Waking Up podcast; Christina Hoff Sommers, aka “The Factual Feminist”; the comedian turned YouTube interviewer Dave Rubin; the counter-extremist activist Maajid Nawaz; and a cantankerous and then little-known Canadian psychology professor named Jordan Peterson, who railed against authoritarianism on both the left and right but reserved special disdain for postmodernism, which he believed was eroding rational thought on campuses and elsewhere.

the sudden national obsession with female endangerment on college campuses struck me much the same way it had in the early 1990s: well-intended but ultimately infantilizing to women and essentially unfeminist.

Weinstein and his wife, the evolutionary biologist Heather Heying, who also taught at Evergreen, would eventually leave the school and go on to become core members of the “intellectual dark web.”

Weinstein talked about intellectual “feebleness” in academia and in the media, about the demise of nuance, about still considering himself a progressive despite his feeling that the far left was no better at offering practical solutions to the world’s problems than the far right.

an American Enterprise Institute video of Sommers, the Factual Feminist, in conversation with the scholar and social critic Camille Paglia — “My generation fought for the freedom for women to risk getting raped!” I watched yet another video in which Paglia sat by herself and expounded volcanically about the patriarchal history of art (she was all for it).

the brothers sat down together for a two-hour, 47-minute interview on theRubin Report,

James Baldwin’s line, “I love America more than any other country in the world, and, exactly for this reason, I insist on the right to criticize her perpetually

Jordan Peterson Twelve Rules for Life: An Antidote for Chaos, is a sort of New and Improved Testament for the purpose-lacking young person (often but not always male) for whom tough-love directives like “clean up your room!” go down a lot easier when dispensed with a Jungian, evo-psych panache.

Quillette, a new online magazine that billed itself as “a platform for free thought”

the more honest we are about what we think, the more we’re alone with our thoughts. Just as you can’t fight Trumpism with tribalism, you can’t fight tribalism with a tribe.

Identity Politics New Tribalism and the Crisis of Democracy

Fukuyama, F. (2018). Against Identity Politics: The New Tribalism and the Crisis of Democracy. Foreign Affairs97(5), 90–114. Retrieved from

For the most part, twentieth-century politics was defined by economic issues. On the left, politics centered on workers, trade unions, social welfare programs, and redistributive policies. The right, by contrast, was primarily interested in reducing the size of government and promoting the private sector. Politics today, however, is defined less by economic or ideological concerns than by questions of identity. Now, in many democracies, the left focuses less on creating broad economic equality and more on promoting the interests of a wide variety of marginalized groups, such as ethnic minorities, immigrants and refugees, women, and lgbt people. The right, meanwhile, has redefined its core mission as the patriotic protection of traditional national identity, which is often explicitly connected to race, ethnicity,
or religion.

Again and again, groups have come to believe that their identities—whether national, religious, ethnic, sexual, gender, or otherwise—are not receiving adequate recognition. Identity politics is no longer a minor phenomenon, playing out only in the rarified confines of university campuses or providing a backdrop to low-stakes skirmishes in “culture wars” promoted by the mass media. Instead, identity politics has become a master concept that explains much of what is going on in global affairs.

Democratic societies are fracturing into segments based on ever-narrower identities,
threatening the possibility of deliberation and collective action by society as a whole. This is a road that leads only to state breakdown and, ultimately, failure. Unless such liberal democracies can work their way back to more universal understandings of human dignity,
they will doom themselves—and the world—to continuing conflict.

But in liberal democracies, equality under the law does not result in economic or social equality. Discrimination continues to exist against a wide variety of groups, and market economies produce large inequalities of outcome.

And the proportion of white working-class children growing up in single-parent families rose from 22 percent in 2000 to 36 percent in 2017.

Nationalists tell the disaffected that they have always been core members of a great
nation and that foreigners, immigrants, and elites have been conspiring to hold them down.

transforming liaison roles in research libraries

!*!*!*!*! — this article was pitched by Mark Vargas in the fall of 2013, back then dean of LRS and discussed at a faculty meeting at LRS in the same year—- !*!*!*!

New Roles for New Times: Transforming Liaison Roles in Research Libraries

(p. 4) Building strong relationships with faculty and other campus professionals, and establishing collaborative partnerships within and across institutions, are necessary building blocks to librarians’ success. In a traditional liaison model, librarians use their subject knowledge to select books and journals and teach guest lectures.

“Liaisons cannot be experts themselves in each new capability, but knowing when to call in a colleague, or how to describe appropriate expert capabilities to faculty, will be key to the new liaison role.

six trends in the development of new roles for library liaisons
user engagement is a driving factor
what users do (research, teaching, and learning) rather than on what librarians do (collections, reference, library instruction).
In addition, an ALA-accredited master’s degree in library science is no longer strictly required.
In a networked world, local collections as ends in themselves make learning fragmentary and incomplete. (p. 5)
A multi-institutional approach is the only one that now makes sense.
Scholars already collaborate; libraries need to make it easier for them to do so.
but they also advise and collaborate on issues of copyright, scholarly communication, data management, knowledge management, and information literacy. The base level of knowledge that a liaison must possess is much broader than familiarity with a reference collection or facility with online searching; instead, they must constantly keep up with evolving pedagogies and research methods, rapidly developing tools, technologies, and ever-changing policies that facilitate and inform teaching, learning, and research in their assigned disciplines.
In many research libraries, programmatic efforts with information literacy have been too narrowly defined. It is not unusual for libraries to focus on freshman writing programs and a series of “one-shot” or invited guest lectures in individual courses. While many librarians have become excellent teachers, traditional one-shot, in-person instructional sessions can vary in quality depending on the training librarians have received in this arena; and they neither scale well nor do they necessarily address broader curricular goals. Librarians at many institutions are now focusing on collaborating with faculty to develop thoughtful assignments and provide online instructional materials that are built into key courses within a curriculum and provide scaffolding to help students develop library research skills over the course of their academic careers.
And many libraries stated that they lack instructional designers and/or educational technologists on their staff, limiting the development of interactive online learning modules and tutorials. (my note: or just ignore the desire by unites such as IMS to help).

(p. 7). This move away from supervision allows the librarians to focus on their liaison responsibilities rather than on the day-to-day operations of a library and its attendant personnel needs.

effectively support teaching, (1.) learning, and research; (2.) identify opportunities for further development of tools and services; (3.) and connect students, staff, and faculty to deeper expertise when needed.

At many institutions, therefore, the conversation has focused on how to supplement and support the liaison model with other staff.

At many institutions, therefore, the conversation has focused on how to supplement and support the liaison model with other staff.

the hybrid exists within the liaison structure, where liaisons also devote a portion of their time (e.g., 20% or more) to an additional area of expertise, for example digital humanities and scholarly communication, and may work with liaisons across all disciplinary areas. (my note: and at the SCSU library, the librarians firmly opposed the request for a second master’s degree)

functional specialists who do not have liaison assignments to specific academic departments but instead serve as “superliaisons” to other librarians and to the entire campus. Current specialist areas of expertise include copyright, geographic information systems (GIS), media production and integration, distributed education or e-learning, data management, emerging technologies, user experience, instructional design, and bioinformatics. (everything in italics is currently done by IMS faculty).

divided into five areas of functional specialization: information resources and collections management; information literacy, instruction, and curriculum development; discovery and access; archival and special collections; scholarly communication and the research enterprise.

E-Scholarship Collaborative, a Research Support Services Collaborative (p. 8).

p. 9. managing alerts and feeds, personal archiving, and using social networking for teaching and professional development

p. 10. new initiatives in humanistic research and teaching are changing the nature and frequency of partnerships between faculty and the Libraries. In particular, cross-disciplinary Humanities Laboratories (, supported by the John Hope Franklin Humanities Institute and the Andrew W. Mellon Foundation-funded Humanities Writ Large project, have allowed liaisons to partner with faculty to develop and curate new forms of scholarship.

consultations on a range of topics, such as how to use social media to effectively communicate academic research and how to mark up historical texts using the Text Encoding Initiative (TEI) guidelines

p. 10.
The RLUK report identified a wide skills gap in nine key areas where future involvement of liaisons is considered important now and expected to grow

p. 11. Media literacy, and facilitating the integration of media into courses, is an area in which research libraries can play a lead role at their institutions. (my note: yet still suppressed or outright denied to IMS to conducts such efforts)

Purdue Academic Course Transformation, or IMPACT ( The program’s purpose is to make foundational courses at Purdue more student-centered and participatory. Librarians are key members of interdepartmental teams that “work with Purdue instructors to redesign courses by applying evidence-based educational practices” and offer “learning solutions” that help students engage with and critically evaluate information. (my note: as offered by Keith and myself to Miguel, the vice provost for undergrads, who left; then offered to First Year Experience faculty, but ignored by Christine Metzo; then offered again to Glenn Davis, who bounced it back to Christine Metzo).

p. 15. The NCSU Libraries Fellows Program offers new librarians a two-year appointment during which they develop expertise in a functional area and contribute to an innovative initiative of strategic importance. NCSU Libraries typically have four to six fellows at a time, bringing in people with needed skills and working to find ongoing positions when they have a particularly good match. Purdue Libraries have experimented with offering two-year visiting assistant professor positions. And the University of Minnesota has hired a second CLIR fellow for a two-year digital humanities project; the first CLIR fellow now holds an ongoing position as a curator in Archives and Special Collections. The CLIR Fellowship is a postdoctoral program that hires recent PhD graduates (non-librarians), allowing them to explore alternative careers and allowing the libraries to benefit from their discipline-specific expertise.

ECAR Study of Undergraduate Students and Information Technology, 2017

ECAR Study of Undergraduate Students and Information Technology, 2017

  • Students would like their instructors to use more technology in their classes.Technologies that provide students with something (e.g., lecture capture, early-alert systems, LMS, search tools) are more desired than those that require students to give something (e.g., social media, use of their own devices, in-class polling tools). We speculate that sound pedagogy and technology use tied to specific learning outcomes and goals may improve the desirability of the latter.
  • Students reported that faculty are banning or discouraging the use of laptops, tablets, and (especially) smartphones more often than in previous years. Some students reported using their devices (especially their smartphones) for nonclass activities, which might explain the instructor policies they are experiencing. However, they also reported using their devices for productive classroom activities (e.g., taking notes, researching additional sources of information, and instructor-directed activities).

more on ECAR studies in this IMS blog

corporate monopoly or public control net neutrality

Net Neutrality is just the beginning

Interview with Victor Pickard

Victor Pickard, associate professor of communication at the University Pennsylvania’s Annenberg School, whose research focuses on internet policy and the political economy of media.

with each new victory for the American telecommunications oligopoly, that digital optimism fades further from view.


Net neutrality protections are essentially safeguards that prevent internet service providers (ISPs) from interfering with the internet. Net neutrality gives the FCC the regulatory authority to prevent ISPs like Comcast and Verizon from slowing down or blocking certain types of content. It also prevents them from offering what’s known as paid prioritization, where an ISP could let particular websites or content creators pay more for faster streaming and download times. With paid prioritization an ISP could shake down a company like Netflix or an individual website owner, coercing them to pay more in order to be in the fast lane.

Net neutrality often gets treated as a sort of technocratic squabble over ownership and control of internet pipes. But in fact it speaks to a core social contract between government, corporations, and the public. What it really comes down to is, how can members of the public obtain information and services, and express ourselves creatively and politically, without interference from massive corporations?

Should we think of the internet as a good, a service, an infrastructure, or something else?

It’s all of the above.

The internet has been radically privatized. It wasn’t inevitable, but through policy decisions over the years, the internet has become increasingly commodified. Meanwhile it’s really difficult to imagine living in modern society without fast internet services — it’s no longer a luxury but a necessity for everything ranging from education to health to livelihood. The “digital divide” is a phrase that sounds like it’s from the 1990s, but it’s still very relevant. Somewhere around one fifth of American households don’t have access to wireline broadband services. It’s a social problem. We should be thinking about the internet as a public service and subsidizing it to make sure that everyone has access.

In your recent book on media democracy, you discuss the rise of what you call “corporate libertarianism.” What is corporate libertarianism and how does it relate to net neutrality?

Corporate libertarianism is an ideological project that has origins at a core moment in the 1940s. It sees corporations as having individual freedoms, like those in the First Amendment, which they can use to shield themselves from public interest oversight and regulation. It’s also often connected to this assumption that the government should never intervene in markets, and media markets in particular. (My note: Milton Friedman)

Of course, this is a libertarian mythology — the government is always involved. The question ought to be how it should be involved. Under corporate libertarianism it’s assumed that the government should only be involved in ways that enhance profit maximization for communication oligopolies.

There are clear dangers associated with vertical integration, where the company that owns the pipes is able to control the dissemination of information, and able to set the terms by which we access that information.
There have been cases like this already. In 2005, the company Telus, which is the second largest telecommunications company in Canada, began blocking access to a server that hosted a website that supported a labor strike against Telus.

Net neutrality is just one part of the story. What other regulations, policies and interventions could resist corporate control of the internet?

Roughly half of Americans live in communities that have access to only one ISP.  My note: Ha Ha Ha, “pick me, pick me,” as Dori from “Finding Nemo” will say… Charter, whatever they will rename themselves again, is the crass example in Central MN.

Strategies to contain and confront monopolies:

  • break them up, and to prevent monopolies and oligopolies from happening in the first place by blocking mergers and acquisitions.
  • if we’re not going to outright nationalize them then we want to heavily regulate them, and enforce some kind of social contract where they’re compelled to provide a public service in exchange for the right to operate.
  • create public alternatives, like municipal wireless networks that can circumvent and compete with corporate monopolies. There’s a growing number of these publicly owned and governed internet infrastructures, and building more is crucial.

more on #netNeutrality in this IMS blog

IRDL proposal

Applications for the 2018 Institute will be accepted between December 1, 2017 and January 27, 2018. Scholars accepted to the program will be notified in early March 2018.


Learning to Harness Big Data in an Academic Library

Abstract (200)

Research on Big Data per se, as well as on the importance and organization of the process of Big Data collection and analysis, is well underway. The complexity of the process comprising “Big Data,” however, deprives organizations of ubiquitous “blue print.” The planning, structuring, administration and execution of the process of adopting Big Data in an organization, being that a corporate one or an educational one, remains an elusive one. No less elusive is the adoption of the Big Data practices among libraries themselves. Seeking the commonalities and differences in the adoption of Big Data practices among libraries may be a suitable start to help libraries transition to the adoption of Big Data and restructuring organizational and daily activities based on Big Data decisions.
Introduction to the problem. Limitations

The redefinition of humanities scholarship has received major attention in higher education. The advent of digital humanities challenges aspects of academic librarianship. Data literacy is a critical need for digital humanities in academia. The March 2016 Library Juice Academy Webinar led by John Russel exemplifies the efforts to help librarians become versed in obtaining programming skills, and respectively, handling data. Those are first steps on a rather long path of building a robust infrastructure to collect, analyze, and interpret data intelligently, so it can be utilized to restructure daily and strategic activities. Since the phenomenon of Big Data is young, there is a lack of blueprints on the organization of such infrastructure. A collection and sharing of best practices is an efficient approach to establishing a feasible plan for setting a library infrastructure for collection, analysis, and implementation of Big Data.
Limitations. This research can only organize the results from the responses of librarians and research into how libraries present themselves to the world in this arena. It may be able to make some rudimentary recommendations. However, based on each library’s specific goals and tasks, further research and work will be needed.



Research Literature

“Big data is like teenage sex: everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it…”
– Dan Ariely, 2013

Big Data is becoming an omnipresent term. It is widespread among different disciplines in academia (De Mauro, Greco, & Grimaldi, 2016). This leads to “inconsistency in meanings and necessity for formal definitions” (De Mauro et al, 2016, p. 122). Similarly, to De Mauro et al (2016), Hashem, Yaqoob, Anuar, Mokhtar, Gani and Ullah Khan (2015) seek standardization of definitions. The main connected “themes” of this phenomenon must be identified and the connections to Library Science must be sought. A prerequisite for a comprehensive definition is the identification of Big Data methods. Bughin, Chui, Manyika (2011), Chen et al. (2012) and De Mauro et al (2015) single out the methods to complete the process of building a comprehensive definition.

In conjunction with identifying the methods, volume, velocity, and variety, as defined by Laney (2001), are the three properties of Big Data accepted across the literature. Daniel (2015) defines three stages in big data: collection, analysis, and visualization. According to Daniel, (2015), Big Data in higher education “connotes the interpretation of a wide range of administrative and operational data” (p. 910) and according to Hilbert (2013), as cited in Daniel (2015), Big Data “delivers a cost-effective prospect to improve decision making” (p. 911).

The importance of understanding the process of Big Data analytics is well understood in academic libraries. An example of such “administrative and operational” use for cost-effective improvement of decision making are the Finch & Flenner (2016) and Eaton (2017) case studies of the use of data visualization to assess an academic library collection and restructure the acquisition process. Sugimoto, Ding & Thelwall (2012) call for the discussion of Big Data for libraries. According to the 2017 NMC Horizon Report “Big Data has become a major focus of academic and research libraries due to the rapid evolution of data mining technologies and the proliferation of data sources like mobile devices and social media” (Adams, Becker, et al., 2017, p. 38).

Power (2014) elaborates on the complexity of Big Data in regard to decision-making and offers ideas for organizations on building a system to deal with Big Data. As explained by Boyd and Crawford (2012) and cited in De Mauro et al (2016), there is a danger of a new digital divide among organizations with different access and ability to process data. Moreover, Big Data impacts current organizational entities in their ability to reconsider their structure and organization. The complexity of institutions’ performance under the impact of Big Data is further complicated by the change of human behavior, because, arguably, Big Data affects human behavior itself (Schroeder, 2014).

De Mauro et al (2015) touch on the impact of Dig Data on libraries. The reorganization of academic libraries considering Big Data and the handling of Big Data by libraries is in a close conjunction with the reorganization of the entire campus and the handling of Big Data by the educational institution. In additional to the disruption posed by the Big Data phenomenon, higher education is facing global changes of economic, technological, social, and educational character. Daniel (2015) uses a chart to illustrate the complexity of these global trends. Parallel to the Big Data developments in America and Asia, the European Union is offering access to an EU open data portal ( ). Moreover, the Association of European Research Libraries expects under the H2020 program to increase “the digitization of cultural heritage, digital preservation, research data sharing, open access policies and the interoperability of research infrastructures” (Reilly, 2013).

The challenges posed by Big Data to human and social behavior (Schroeder, 2014) are no less significant to the impact of Big Data on learning. Cohen, Dolan, Dunlap, Hellerstein, & Welton (2009) propose a road map for “more conservative organizations” (p. 1492) to overcome their reservations and/or inability to handle Big Data and adopt a practical approach to the complexity of Big Data. Two Chinese researchers assert deep learning as the “set of machine learning techniques that learn multiple levels of representation in deep architectures (Chen & Lin, 2014, p. 515). Deep learning requires “new ways of thinking and transformative solutions (Chen & Lin, 2014, p. 523). Another pair of researchers from China present a broad overview of the various societal, business and administrative applications of Big Data, including a detailed account and definitions of the processes and tools accompanying Big Data analytics.  The American counterparts of these Chinese researchers are of the same opinion when it comes to “think about the core principles and concepts that underline the techniques, and also the systematic thinking” (Provost and Fawcett, 2013, p. 58). De Mauro, Greco, and Grimaldi (2016), similarly to Provost and Fawcett (2013) draw attention to the urgent necessity to train new types of specialists to work with such data. As early as 2012, Davenport and Patil (2012), as cited in Mauro et al (2016), envisioned hybrid specialists able to manage both technological knowledge and academic research. Similarly, Provost and Fawcett (2013) mention the efforts of “academic institutions scrambling to put together programs to train data scientists” (p. 51). Further, Asomoah, Sharda, Zadeh & Kalgotra (2017) share a specific plan on the design and delivery of a big data analytics course. At the same time, librarians working with data acknowledge the shortcomings in the profession, since librarians “are practitioners first and generally do not view usability as a primary job responsibility, usually lack the depth of research skills needed to carry out a fully valid” data-based research (Emanuel, 2013, p. 207).

Borgman (2015) devotes an entire book to data and scholarly research and goes beyond the already well-established facts regarding the importance of Big Data, the implications of Big Data and the technical, societal, and educational impact and complications posed by Big Data. Borgman elucidates the importance of knowledge infrastructure and the necessity to understand the importance and complexity of building such infrastructure, in order to be able to take advantage of Big Data. In a similar fashion, a team of Chinese scholars draws attention to the complexity of data mining and Big Data and the necessity to approach the issue in an organized fashion (Wu, Xhu, Wu, Ding, 2014).

Bruns (2013) shifts the conversation from the “macro” architecture of Big Data, as focused by Borgman (2015) and Wu et al (2014) and ponders over the influx and unprecedented opportunities for humanities in academia with the advent of Big Data. Does the seemingly ubiquitous omnipresence of Big Data mean for humanities a “railroading” into “scientificity”? How will research and publishing change with the advent of Big Data across academic disciplines?

Reyes (2015) shares her “skinny” approach to Big Data in education. She presents a comprehensive structure for educational institutions to shift “traditional” analytics to “learner-centered” analytics (p. 75) and identifies the participants in the Big Data process in the organization. The model is applicable for library use.

Being a new and unchartered territory, Big Data and Big Data analytics can pose ethical issues. Willis (2013) focusses on Big Data application in education, namely the ethical questions for higher education administrators and the expectations of Big Data analytics to predict students’ success.  Daries, Reich, Waldo, Young, and Whittinghill (2014) discuss rather similar issues regarding the balance between data and student privacy regulations. The privacy issues accompanying data are also discussed by Tene and Polonetsky, (2013).

Privacy issues are habitually connected to security and surveillance issues. Andrejevic and Gates (2014) point out in a decision making “generated by data mining, the focus is not on particular individuals but on aggregate outcomes” (p. 195). Van Dijck (2014) goes into further details regarding the perils posed by metadata and data to the society, in particular to the privacy of citizens. Bail (2014) addresses the same issue regarding the impact of Big Data on societal issues, but underlines the leading roles of cultural sociologists and their theories for the correct application of Big Data.

Library organizations have been traditional proponents of core democratic values such as protection of privacy and elucidation of related ethical questions (Miltenoff & Hauptman, 2005). In recent books about Big Data and libraries, ethical issues are important part of the discussion (Weiss, 2018). Library blogs also discuss these issues (Harper & Oltmann, 2017). An academic library’s role is to educate its patrons about those values. Sugimoto et al (2012) reflect on the need for discussion about Big Data in Library and Information Science. They clearly draw attention to the library “tradition of organizing, managing, retrieving, collecting, describing, and preserving information” (p.1) as well as library and information science being “a historically interdisciplinary and collaborative field, absorbing the knowledge of multiple domains and bringing the tools, techniques, and theories” (p. 1). Sugimoto et al (2012) sought a wide discussion among the library profession regarding the implications of Big Data on the profession, no differently from the activities in other fields (e.g., Wixom, Ariyachandra, Douglas, Goul, Gupta, Iyer, Kulkami, Mooney, Phillips-Wren, Turetken, 2014). A current Andrew Mellon Foundation grant for Visualizing Digital Scholarship in Libraries seeks an opportunity to view “both macro and micro perspectives, multi-user collaboration and real-time data interaction, and a limitless number of visualization possibilities – critical capabilities for rapidly understanding today’s large data sets (Hwangbo, 2014).

The importance of the library with its traditional roles, as described by Sugimoto et al (2012) may continue, considering the Big Data platform proposed by Wu, Wu, Khabsa, Williams, Chen, Huang, Tuarob, Choudhury, Ororbia, Mitra, & Giles (2014). Such platforms will continue to emerge and be improved, with librarians as the ultimate drivers of such platforms and as the mediators between the patrons and the data generated by such platforms.

Every library needs to find its place in the large organization and in society in regard to this very new and very powerful phenomenon called Big Data. Libraries might not have the trained staff to become a leader in the process of organizing and building the complex mechanism of this new knowledge architecture, but librarians must educate and train themselves to be worthy participants in this new establishment.




The study will be cleared by the SCSU IRB.
The survey will collect responses from library population and it readiness to use and use of Big Data.  Send survey URL to (academic?) libraries around the world.

Data will be processed through SPSS. Open ended results will be processed manually. The preliminary research design presupposes a mixed method approach.

The study will include the use of closed-ended survey response questions and open-ended questions.  The first part of the study (close ended, quantitative questions) will be completed online through online survey. Participants will be asked to complete the survey using a link they receive through e-mail.

Mixed methods research was defined by Johnson and Onwuegbuzie (2004) as “the class of research where the researcher mixes or combines quantitative and qualitative research techniques, methods, approaches, concepts, or language into a single study” (Johnson & Onwuegbuzie, 2004 , p. 17).  Quantitative and qualitative methods can be combined, if used to complement each other because the methods can measure different aspects of the research questions (Sale, Lohfeld, & Brazil, 2002).


Sampling design


  • Online survey of 10-15 question, with 3-5 demographic and the rest regarding the use of tools.
  • 1-2 open-ended questions at the end of the survey to probe for follow-up mixed method approach (an opportunity for qualitative study)
  • data analysis techniques: survey results will be exported to SPSS and analyzed accordingly. The final survey design will determine the appropriate statistical approach.


Project Schedule


Complete literature review and identify areas of interest – two months

Prepare and test instrument (survey) – month

IRB and other details – month

Generate a list of potential libraries to distribute survey – month

Contact libraries. Follow up and contact again, if necessary (low turnaround) – month

Collect, analyze data – two months

Write out data findings – month

Complete manuscript – month

Proofreading and other details – month


Significance of the work 

While it has been widely acknowledged that Big Data (and its handling) is changing higher education ( as well as academic libraries (, it remains nebulous how Big Data is handled in the academic library and, respectively, how it is related to the handling of Big Data on campus. Moreover, the visualization of Big Data between units on campus remains in progress, along with any policymaking based on the analysis of such data (hence the need for comprehensive visualization).


This research will aim to gain an understanding on: a. how librarians are handling Big Data; b. how are they relating their Big Data output to the campus output of Big Data and c. how librarians in particular and campus administration in general are tuning their practices based on the analysis.

Based on the survey returns (if there is a statistically significant return), this research might consider juxtaposing the practices from academic libraries, to practices from special libraries (especially corporate libraries), public and school libraries.





Adams Becker, S., Cummins M, Davis, A., Freeman, A., Giesinger Hall, C., Ananthanarayanan, V., … Wolfson, N. (2017). NMC Horizon Report: 2017 Library Edition.

Andrejevic, M., & Gates, K. (2014). Big Data Surveillance: Introduction. Surveillance & Society, 12(2), 185–196.

Asamoah, D. A., Sharda, R., Hassan Zadeh, A., & Kalgotra, P. (2017). Preparing a Data Scientist: A Pedagogic Experience in Designing a Big Data Analytics Course. Decision Sciences Journal of Innovative Education, 15(2), 161–190.

Bail, C. A. (2014). The cultural environment: measuring culture with big data. Theory and Society, 43(3–4), 465–482.

Borgman, C. L. (2015). Big Data, Little Data, No Data: Scholarship in the Networked World. MIT Press.

Bruns, A. (2013). Faster than the speed of print: Reconciling ‘big data’ social media analysis and academic scholarship. First Monday, 18(10). Retrieved from

Bughin, J., Chui, M., & Manyika, J. (2010). Clouds, big data, and smart assets: Ten tech-enabled business trends to watch. McKinsey Quarterly, 56(1), 75–86.

Chen, X. W., & Lin, X. (2014). Big Data Deep Learning: Challenges and Perspectives. IEEE Access, 2, 514–525.

Cohen, J., Dolan, B., Dunlap, M., Hellerstein, J. M., & Welton, C. (2009). MAD Skills: New Analysis Practices for Big Data. Proc. VLDB Endow., 2(2), 1481–1492.

Daniel, B. (2015). Big Data and analytics in higher education: Opportunities and challenges. British Journal of Educational Technology, 46(5), 904–920.

Daries, J. P., Reich, J., Waldo, J., Young, E. M., Whittinghill, J., Ho, A. D., … Chuang, I. (2014). Privacy, Anonymity, and Big Data in the Social Sciences. Commun. ACM, 57(9), 56–63.

De Mauro, A. D., Greco, M., & Grimaldi, M. (2016). A formal definition of Big Data based on its essential features. Library Review, 65(3), 122–135.

De Mauro, A., Greco, M., & Grimaldi, M. (2015). What is big data? A consensual definition and a review of key research topics. AIP Conference Proceedings, 1644(1), 97–104.

Dumbill, E. (2012). Making Sense of Big Data. Big Data, 1(1), 1–2.

Eaton, M. (2017). Seeing Library Data: A Prototype Data Visualization Application for Librarians. Publications and Research. Retrieved from

Emanuel, J. (2013). Usability testing in libraries: methods, limitations, and implications. OCLC Systems & Services: International Digital Library Perspectives, 29(4), 204–217.

Graham, M., & Shelton, T. (2013). Geography and the future of big data, big data and the future of geography. Dialogues in Human Geography, 3(3), 255–261.

Harper, L., & Oltmann, S. (2017, April 2). Big Data’s Impact on Privacy for Librarians and Information Professionals. Retrieved November 7, 2017, from

Hashem, I. A. T., Yaqoob, I., Anuar, N. B., Mokhtar, S., Gani, A., & Ullah Khan, S. (2015). The rise of “big data” on cloud computing: Review and open research issues. Information Systems, 47(Supplement C), 98–115.

Hwangbo, H. (2014, October 22). The future of collaboration: Large-scale visualization. Retrieved November 7, 2017, from

Laney, D. (2001, February 6). 3D Data Management: Controlling Data Volume, Velocity, and Variety.

Miltenoff, P., & Hauptman, R. (2005). Ethical dilemmas in libraries: an international perspective. The Electronic Library, 23(6), 664–670.

Philip Chen, C. L., & Zhang, C.-Y. (2014). Data-intensive applications, challenges, techniques and technologies: A survey on Big Data. Information Sciences, 275(Supplement C), 314–347.

Power, D. J. (2014). Using ‘Big Data’ for analytics and decision support. Journal of Decision Systems, 23(2), 222–228.

Provost, F., & Fawcett, T. (2013). Data Science and its Relationship to Big Data and Data-Driven Decision Making. Big Data, 1(1), 51–59.

Reilly, S. (2013, December 12). What does Horizon 2020 mean for research libraries? Retrieved November 7, 2017, from

Reyes, J. (2015). The skinny on big data in education: Learning analytics simplified. TechTrends: Linking Research & Practice to Improve Learning, 59(2), 75–80.

Schroeder, R. (2014). Big Data and the brave new world of social media research. Big Data & Society, 1(2), 2053951714563194.

Sugimoto, C. R., Ding, Y., & Thelwall, M. (2012). Library and information science in the big data era: Funding, projects, and future [a panel proposal]. Proceedings of the American Society for Information Science and Technology, 49(1), 1–3.

Tene, O., & Polonetsky, J. (2012). Big Data for All: Privacy and User Control in the Age of Analytics. Northwestern Journal of Technology and Intellectual Property, 11, [xxvii]-274.

van Dijck, J. (2014). Datafication, dataism and dataveillance: Big Data between scientific paradigm and ideology. Surveillance & Society; Newcastle upon Tyne, 12(2), 197–208.

Waller, M. A., & Fawcett, S. E. (2013). Data Science, Predictive Analytics, and Big Data: A Revolution That Will Transform Supply Chain Design and Management. Journal of Business Logistics, 34(2), 77–84.

Weiss, A. (2018). Big-Data-Shocks-An-Introduction-to-Big-Data-for-Librarians-and-Information-Professionals. Rowman & Littlefield Publishers. Retrieved from

West, D. M. (2012). Big data for education: Data mining, data analytics, and web dashboards. Governance Studies at Brookings, 4, 1–0.

Willis, J. (2013). Ethics, Big Data, and Analytics: A Model for Application. Educause Review Online. Retrieved from

Wixom, B., Ariyachandra, T., Douglas, D. E., Goul, M., Gupta, B., Iyer, L. S., … Turetken, O. (2014). The current state of business intelligence in academia: The arrival of big data. CAIS, 34, 1.

Wu, X., Zhu, X., Wu, G. Q., & Ding, W. (2014). Data mining with big data. IEEE Transactions on Knowledge and Data Engineering, 26(1), 97–107.

Wu, Z., Wu, J., Khabsa, M., Williams, K., Chen, H. H., Huang, W., … Giles, C. L. (2014). Towards building a scholarly big data platform: Challenges, lessons and opportunities. In IEEE/ACM Joint Conference on Digital Libraries (pp. 117–126).


more on big data

NMC digital literacy

NMC Releases Second Horizon Project Strategic Brief on Digital Literacy

NMC Releases Second Horizon Project Strategic Brief on Digital Literacy

The New Media Consortium (NMC) has released Digital Literacy in Higher Education, Part II: An NMC Horizon Project Strategic Brief, a follow-up to its 2016 strategic brief on digital literacy.

PDF available here.

But what does it really mean to be digitally literate, and which standards do we use?” said Dr. Eden Dahlstrom, NMC Executive Director. “This report sheds light on the meaning and impact of digital literacy using cross-cultural and multi-disciplinary approaches, highlighting frameworks and exemplars in practice.

NMC’s report has identified a need for institutions and thought leaders to consider the ways in which content creation is unequally expressed throughout the world. In an examination of digital literacy within European, Middle Eastern, and African nations (EMEA), research has surfaced unequal access to information technology based on inequalities of economics, gender, race, and political divides.

2020 2015
1. Complex Problem Solving 1. Complex Problem Solving
2. Critical Thinking 2. Coordinating with Others
3. Creativity 3. People  Management
4. People  Management 4. Critical Thinking
5. Coordinating with Others 5. Negotiation
6. Emotional  Intelligence 6. Quality Control
7. Judgment and Decision Making 7. Service  Orientation
8. Service  Orientation 8. Judgment and Decision Making
9. Negotiation 9. Active Listening
10. Cognitive  Flexibility 10. Creativity

Digital tools themselves are merely enablers, pushing the envelope of  what learners can create. No longer is it acceptable for students to be passive consumers of content; they can contribute to the local and global knowledge ecosystem, learning through the act of producing and discussing rich media, applications, and objects. In the words of many institutional mission statements, students do not have to wait until they graduate to change the world.

Using readily available  digital  content  creation tools (e.g., video production and editing, web and graphic tools), students are evolving into digital storytellers,

digital literacy now encompasses the important skills of being able to coordinate with others to create something truly original that neither mind would fathom independently.

The ability to discern credible from inaccurate resources is foundational to digital literacy. my note: #Fakenews

A lack of broad consensus on the meaning of digital literacy still hinders its uptake, although a growing  body  of research is helping higher education professionals better navigate the continuous adjustments to the field brought about by emerging pedagogies and technologies.

Information literacy is a nearly universal component within these digital literacy frameworks. Critically finding, assessing, and using digital content within the vast and sometimes chaotic internet appears as a vital skill in almost every account, including those published beyond libraries. In contrast, media literacy is less widely included in digital literacy publications,  possibly  due  to  a  focus  on  scholarly, rather than popular, materials. Digital literacies ultimately combine information and media literacy.

United States digital literacy frameworks tend to  focus  on  educational  policy details and personal empowerment,  the  latter  encouraging  learners  to  become  more  effective students, better creators, smarter information consumers, and more influential members of their community.

National policies are vitally important in European digital literacy work, unsurprising for a continent well populated with nation-states and struggling to redefine itself… this recommendation for Balkan digital strategy: “Media and information education (with an emphasis on critical thinking and switching from consumption to action) should start at early ages, but address all ages.”

African digital literacy is more business-oriented. Frameworks often speak to job skills and digital entrepreneurship. New skills and professions are emphasized, symbolized by the call for “new collar” positions.

Middle Eastern nations offer yet another variation, with a strong focus on media literacy. As with other regions, this can be a response to countries with strong state influence or control over local media. It can  also  represent  a  drive  to  produce  more  locally-sourced  content,  as  opposed  to  consuming

Digital literacy is a complex phenomenon in 2017, when considered internationally. Nations  and regions are creating ways to help their populations grapple with the digital revolution that are shaped by their local situations. In doing so, they cut across the genealogy of digital literacies, touching on its historical components: information literacy, digital skills, and media literacy.









How Does Digital Literacy Change Pedagogy?

Students are not all digital natives, and do not necessarily have the same level of capabilities. Some need to be taught to use online tools (such as how to navigate a LMS) for learning. However, once digital literacy skills for staff and students are explicitly recognized as important for learning and teaching, critical drivers for pedagogical change are in place.

Pedagogy that uses an inquiry based/problem solving approach is a great framework to enhance the use and practice of digital skills/capabilities in the classroom.

The current gap between students’ information literacy skills and their need  to  internalize  digital literacy competencies creates an opportunity for academic librarians to support students  in  the pursuit of civic online reasoning at the core of NMC’s multimodal model of three digital literacies. Academic librarians need a new strategy that evolves information literacy to an expanded role educating digitally literate students. Let’s build a new model in which academic librarians are  entrepreneurial collaborators with faculty,55  supporting  their  classroom  efforts  to  help  students become responsible sharers and commentators of news on social media.

“Digital literacy is not just about ensuring that students can use the latest technologies, but also developing skills to select the right tools for a particular context to deepen their learning outcomes and engage in creative problem-solving”

There is a disconnect between how students experience and interact with technology in their personal lives and how they use technology in their roles as  students.  Yes, students are digitally savvy, and yes,  universities  have  a  role  in  questioning  (insightfully  of  course) their sometimes brash digital savviness. We have a situation where students are expecting more, but (as I see it) cannot provide a clear demand, while faculty are unable to walk in  the  shoes  of  the students.


more on digital literacy in this IMS blog

Privacy & Security in Today’s Library

Privacy & Security in Today’s Library by Amigos Library Services

The virtuality of privacy and security on the from Plamen Miltenoff

From: Jodie Borgerding []
Sent: Wednesday, July 05, 2017 3:07 PM
To: Miltenoff, Plamen <>
Cc: Nicole Walsh <WALSH@AMIGOS.ORG>
Subject: Proposal Submission for Privacy & Security Conference

Hi Plamen,

Thank you for your recent presentation proposal for the online conference, Privacy & Security in Today’s Library, presented by Amigos Library Services. Your proposal, The role of the library in teaching with technology unsupported by campus IT: the privacy and security issues of the “third-party,” has been accepted. I just wanted to confirm that you are still available to present on September 21, 2017 and if you have a time preference for your presentation (11 am, 12 pm, or 2 pm Central). If you are no longer able to participate, please let me know.

Nicole will be touch with you shortly with additional details and a speaker’s agreement.

Please let me know if you have any questions.


Jodie Borgerding Consulting & Education Services Manager Amigos Library Services 1190 Meramec Station Road, Suite 207 | Ballwin, MO  63021-6902 800-843-8482 x2897 | 972-340-2897(direct) |



Dr. Plamen Miltenoff is an Information Specialist and Professor at St. Cloud State University. His education includes several graduate degrees in history and Library and Information Science and terminal degrees in education and psychology.

His professional interests encompass social media, multimedia, Web development and design, gaming and gamification, and learning environments (LEs).

Dr. Miltenoff organized and taught classes such as LIB 290 “Social Media in Global Context” ( and LIB 490/590 “Digital Storytelling” ( where issues of privacy and security are discussed.

Twitter handle @SCSUtechinstruc

Facebook page:

The virtuality of privacy and security on the modern campus:

The role of the library in teaching with technology unsupported by campus IT: the privacy and security issues of the “third-party software” teaching and learning

Abstract/Summary of Your Proposed Session

The virtualization reality changes rapidly all aspects of learning and teaching: from equipment to methodology, just when faculty have finalized their syllabus, they have to start a new, if they want to keep abreast with content changes and upgrades and engagement of a very different student fabric – Millennials.

Mainframes are replaced by microcomputers, microcomputers by smart phones and tablets, hard drives by cloud storage and wearables by IoT. The pace of hardware, software and application upgrade is becoming unbearable for students and faculty. Content creation and methodology becomes useless by the speed of becoming obsolete. In such environment, faculty students and IT staff barely can devote time and energy to deal with the rapidly increasing vulnerability connected with privacy and security.

In an effort to streamline ever-becoming-scarce resources, campus IT “standardizes” campus use of applications. Those are the applications, which IT chooses to troubleshoot campus-wide. Those are the applications recommended to faculty and students to use.

In an unprecedented burgeoning amount of applications, specifically for mobile devices, it is difficult to constraint faculty and students to use campus IT sanctioned applications, especially considering the rapid pace of such applications becoming obsolete. Faculty and students often “stray” away and go with their own choice. Such decision exposes faculty and students, personally, and the campus, institutionally, at risk. In a recent post by THE Journal, attention on campuses is drown to the fact that cyberattacks shift now from mobile devices to IoT and campus often are struggling even with their capability to guarantee cybersecurity of mobile devices on campus. Further, the use of third-party application might be in conflict with the FERPA campus-mandated policies. Such policies are lengthy and complex to absorb, both by faculty and students and often are excessively restrictive in terms of innovative ways to improve methodology and pedagogy of teaching and learning. The current procedure of faculty and students proposing new applications is a lengthy and cumbersome bureaucratic process, which often render the end-users’ proposals obsolete by the time the process is vetted.

Where/what is the balance between safeguarding privacy on campus and fostering security without stifling innovation and creativity? Can the library be the campus hub for education about privacy and security, the sandbox for testing and innovation and the body to expedite decision-making?


The pace of changes in teaching and learning is becoming impossible to sustain: equipment evolves in accelerated pace, the methodology of teaching and learning cannot catch up with the equipment changes and atop, there are constant content updates. In an even-shrinking budget, faculty, students and IT staff barely can address the issues above, less time and energy left to address the increasing concerns about privacy and security.

In an unprecedented burgeoning amount of applications, specifically for mobile devices, it is difficult to constraint faculty and students to use campus IT sanctioned applications, especially considering the rapid pace of such applications becoming obsolete. Faculty and students often “stray” away and go with their own choice. Such decision exposes faculty and students, personally, and the campus, institutionally, at risk. In a recent post by THE Journal (, attention on campuses is drawn to the fact of cyberattacks shifting from mobile devices to IoT but campus still struggling to guarantee cybersecurity of mobile devices on campus. Further, the use of third-party applications might be in conflict with the FERPA campus-mandated policies. Such policies are lengthy and complex to absorb, both by faculty and students and often are excessively restrictive in terms of innovative ways to improve methodology and pedagogy of teaching and learning. The current procedure of faculty and students proposing new applications is a lengthy and cumbersome bureaucratic process, which often render the end-users’ proposals obsolete by the time the process is vetted.

Where/what is the balance between safeguarding privacy on campus and fostering security without stifling innovation and creativity? Can the library be the campus hub for education about privacy and security, the sandbox for testing and innovation and the body to expedite decision-making?

Anything else you would like to add

3 take-aways from this session:

  • Discuss and form an opinion about the education-pertinent issues of privacy and security from the broad campus perspective, versus the narrow library one
  • Discuss and form an opinion about the role of the library on campus in terms of the greater issues of privacy and security

Re-examine the thin red line of the balance between standardization and innovation; between the need for security and privacy protection a


chat – slide 4, privacy. please take 2 min and share your definition of privacy on campus. Does it differ between faculty and students?  what are the main characteristics to determine privacy

chat – slide 5, security. please take 2 min and share your definition of security on campus regarding electronic activities. Who’s responsibility is security? IT issue [only]?

poles: slide 6, technology unsupported by campus IT, is it worth considering? 1. i am a great believer in my freedom of choice 2. I firmly follow rules and this applies to the use of computer tools and applications 3. Whatever…

chat –  slide 6, why third party applications? pros and cons. E.g. pros – familiarity with third party versus campus-required

pole, slide 6, appsmashing. App smashing is the ability to combine mobile apps in your teaching process. How do you feel about it? 1. The force is with us 2. Nonsense…

pole slide 7 third party apps and the comfort of faculty. How do you see the freedom of using third party apps? 1. All I want, thank you 2. I would rather follow the rules 3. Indifference is my middle name

pole slide 8 Technology standardization? 1. yes, 2. no, 3. indifferent

chat slide 9 if the two major issues colliding in this instance are: standardization versus third party and they have impact on privacy and security, how would you argue for the one or the other?

notes from the conference



Measuring Library Vendor Cyber Security: Seven Easy Questions Every Librarian Can Ask

Bill Walker:


more on security in education in this IMS blog

more on privacy in education in this IMS blog

use of laptops phones in the classroom

Why I’m Asking You Not to / Use Laptops

++++++++++ against: ++++++++++++++++

research showing how laptops can be more of a distraction than a learning enabler. Purdue University even started blocking streaming websites such as Netflix, HBO, Hulu and Pandora.

But others say banning laptops can be counterproductive, arguing these devices can create opportunity for students to discover more information during class or collaborate. And that certain tools and technologies are necessary for learners who struggle in a traditional lecture format.


Supiano, B. (2019, April 7). Digital Distraction Is a Problem Far Beyond the Classroom. But Professors Can Still Help. The Chronicle of Higher Education. Retrieved from
Flanigan, who studies self-regulation, or the processes students use to achieve their learning goals, began researching digital distraction after confronting it in the classroom as a graduate instructor.
Digital distraction tempts all of us, almost everywhere. That’s the premise of Digital Minimalism: Choosing a Focused Life in a Noisy World by Cal Newport, an associate professor of computer science at Georgetown University.

The professor is upset. The professor has taken action, by banning laptops.
Bruff, whose next book, Intentional Tech: Principles to Guide the Use of Educational Technology in College Teaching, is set to be published this fall, is among the experts who think that’s a mistake. Why? Well, for one thing, he said, students are “going to have to graduate and get jobs and use laptops without being on Facebook all day.” The classroom should help prepare them for that.

 When Volk teaches a course with 50 or 60 students, he said, “the idea is to keep them moving.”Shifting the focal point away from the professor can help, too. “If they are in a small group with their colleagues,” Volk said, “very rarely will I see them on their laptops doing things they shouldn’t be.”
Professors may not see themselves as performers, but if they can’t get students’ attention, nothing else they do matters. “Learning doesn’t happen without attention,” said Lang, who is writing a book about digital distraction, Teaching Distracted Minds.
One aspect of distraction Lang plans to cover in his book is its history. It’s possible, he said, to regard our smartphones as either too similar or dissimilar from the distractions of the past. And it’s important, he said, to remember how new this technology really is, and how much we still don’t know about it.

Study: Use of digital devices in class affects students’ long-term retention of information

  • A new study conducted by researchers at Rutgers University reveals that students who are distracted by texts, games, or videos while taking lecture notes on digital devices are far more likely to have their long-term memory affected and to perform more poorly on exams, even if short-term memory is not impacted, EdSurge reports.
  • Exam performance was not only poorer for students using the devices, but also for other students in classes that permitted the devices because of the distraction factor, the study found.
  • After conducting the study, Arnold Glass, the lead researcher, changed his own policy and no longer allows his students to take notes on digital devices.
A nationally representative Gallup poll conducted in March showed that 42% of K-12 teachers feel that the use of digital devices in the classroom are “mostly helpful” for students, while only 28% feel they are “mostly harmful.” Yet 69% of those same teachers feel the devices have a harmful impact on student mental health and 55% feel they negatively affect student physical health.
 According to a 2016 study of college students, student waste about 20% of their class time for “non-class” purposes — texting, emailing, or using social media more than 11 times in a typical day. In K-12, increased dependence on digital devices often interferes with homework completion as well.
Though the new study focused on long-term retention, past studies have also shown that indicate a negative correlation between use of digital devices during class and exam scores. A 2015 study by the London School of Economics revealed that pupils in schools that banned cell phones performed better on exams and that the differences were most notable for low-performing students.

By Jack Grove Twitter: @jgro_the  April 4, 2017

Using laptops in class harms academic performance, study warns. Researchers say students who use computers score half a grade lower than those who write notes

findings, published in the journal Economics of Education Review in a paper, based on an analysis of the grades of about 5,600 students at a private US liberal arts college, found that using a laptop appeared to harm the grades of male and low-performing students most significantly.

While the authors were unable to definitively say why laptop use caused a “significant negative effect in grades”, the authors believe that classroom “cyber-slacking” plays a major role in lower achievement, with wi-fi-enabled computers providing numerous distractions for students.

April 07, 2006

A Law Professor Bans Laptops From the Classroom


Classroom Confrontation Over Student’s Laptop Use Leads to Professor’s Arrest

June 02, 2006

The Fight for Classroom Attention: Professor vs. Laptop

Some instructors ban computers or shut off Internet access, bringing complaints from students

Classroom Confrontation Over Student’s Laptop Use Leads to Professor’s Arrest

by Anne Curza

Laptop multitasking hinders classroom learning for both users and nearby peers

March 13, 2017

The Distracted Classroom

Welcome, Freshmen. Look at Me When I Talk to You.

October 28, 2015

Memorization, Cheating, and Technology. What can we do to stem the increased use of phones and laptops to cheat on exams in class?

+++++++++++++++ for +++++++++++++

intrinsic motivation:

The learning experience is different in schools that assign laptops, a survey finds

The learning experience is different in schools that assign laptops, a survey finds

High schoolers assigned a laptop or a Chromebook were more likely to take notes in class, do internet research, create documents to share, collaborate with their peers on projects, check their grades and get reminders about tests or homework due dates.


Blended Learning – the idea of incorporating technology into the every day experience of education – can save time, raise engagement, and increase student retention.

Lets face it, our students are addicted to their phones. Like…drugs addicted. It is not just a bad habit, it is hard wired in their brains(literally) to have the constant stimulation of their phones.

If you are interested in the research, there is a lot out there to read about how it happens and how bad it is.

Scientific American article published about a recent study of nomophobia – on adults (yes, many of us are addicted too).


Best Practices for Laptops in the Classroom

September 11, 2016

No, Banning Laptops Is Not the Answer. And it’s just as pointless to condemn any ban on electronic devices in the classroom


Don’t Ban Laptops in the Classroom

Use of Laptops in the Classroom: Research and Best Practices. Tomorrow’s Teaching and Learning


On Not Banning Laptops in the Classroom

+++++++++++++   neutral / observation +++++++++++++++

F January 26, 2001

Colleges Differ on Costs and Benefits of ‘Ubiquitous’ Computing

“Bring Your Own Device” Policies?

June 13, 2014, 2:40 pm By Robert Talbert

Three issues with the case for banning laptops

3 Tips for Managing Phone Use in Class

Setting cell phone expectations early is key to accessing the learning potential of these devices and minimizing the distraction factor.

more on mobile learning in this IMS blog

1 2 3 4 5