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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.

Title:

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  https://www.asist.org/publications/bulletin/aprilmay-2017/big-datas-impact-on-privacy-for-librarians-and-information-professionals/

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 (https://data.europa.eu/euodp/home ). 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.

 

Method

 

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 (https://blog.stcloudstate.edu/ims?s=big+data) as well as academic libraries (https://blog.stcloudstate.edu/ims/2016/03/29/analytics-in-education/), 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.

 

 

References:

 

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. https://doi.org/10.1111/dsji.12125

Bail, C. A. (2014). The cultural environment: measuring culture with big data. Theory and Society, 43(3–4), 465–482. https://doi.org/10.1007/s11186-014-9216-5

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 http://firstmonday.org/ojs/index.php/fm/article/view/4879

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. https://doi.org/10.1109/ACCESS.2014.2325029

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. https://doi.org/10.14778/1687553.1687576

Daniel, B. (2015). Big Data and analytics in higher education: Opportunities and challenges. British Journal of Educational Technology, 46(5), 904–920. https://doi.org/10.1111/bjet.12230

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. https://doi.org/10.1145/2643132

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. https://doi.org/10.1108/LR-06-2015-0061

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. https://doi.org/10.1063/1.4907823

Dumbill, E. (2012). Making Sense of Big Data. Big Data, 1(1), 1–2. https://doi.org/10.1089/big.2012.1503

Eaton, M. (2017). Seeing Library Data: A Prototype Data Visualization Application for Librarians. Publications and Research. Retrieved from http://academicworks.cuny.edu/kb_pubs/115

Emanuel, J. (2013). Usability testing in libraries: methods, limitations, and implications. OCLC Systems & Services: International Digital Library Perspectives, 29(4), 204–217. https://doi.org/10.1108/OCLC-02-2013-0009

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. https://doi.org/10.1177/2043820613513121

Harper, L., & Oltmann, S. (2017, April 2). Big Data’s Impact on Privacy for Librarians and Information Professionals. Retrieved November 7, 2017, from https://www.asist.org/publications/bulletin/aprilmay-2017/big-datas-impact-on-privacy-for-librarians-and-information-professionals/

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. https://doi.org/10.1016/j.is.2014.07.006

Hwangbo, H. (2014, October 22). The future of collaboration: Large-scale visualization. Retrieved November 7, 2017, from http://usblogs.pwc.com/emerging-technology/the-future-of-collaboration-large-scale-visualization/

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. https://doi.org/10.1108/02640470510635746

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. https://doi.org/10.1016/j.ins.2014.01.015

Power, D. J. (2014). Using ‘Big Data’ for analytics and decision support. Journal of Decision Systems, 23(2), 222–228. https://doi.org/10.1080/12460125.2014.888848

Provost, F., & Fawcett, T. (2013). Data Science and its Relationship to Big Data and Data-Driven Decision Making. Big Data, 1(1), 51–59. https://doi.org/10.1089/big.2013.1508

Reilly, S. (2013, December 12). What does Horizon 2020 mean for research libraries? Retrieved November 7, 2017, from http://libereurope.eu/blog/2013/12/12/what-does-horizon-2020-mean-for-research-libraries/

Reyes, J. (2015). The skinny on big data in education: Learning analytics simplified. TechTrends: Linking Research & Practice to Improve Learning, 59(2), 75–80. https://doi.org/10.1007/s11528-015-0842-1

Schroeder, R. (2014). Big Data and the brave new world of social media research. Big Data & Society, 1(2), 2053951714563194. https://doi.org/10.1177/2053951714563194

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. https://doi.org/10.1002/meet.14504901187

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. https://doi.org/10.1111/jbl.12010

Weiss, A. (2018). Big-Data-Shocks-An-Introduction-to-Big-Data-for-Librarians-and-Information-Professionals. Rowman & Littlefield Publishers. Retrieved from https://rowman.com/ISBN/9781538103227/Big-Data-Shocks-An-Introduction-to-Big-Data-for-Librarians-and-Information-Professionals

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 https://docs.lib.purdue.edu/idcpubs/1

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. https://doi.org/10.1109/TKDE.2013.109

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). https://doi.org/10.1109/JCDL.2014.6970157

 

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more on big data





altmetrics library Lily Troia

Taking Altmetrics to the Next Level in Your Library’s Systems and Services

Instructor: Lily Troia, Engagement Manager, Altmetric
October 31, 2017, 1:00 pm – 2:30 pm Central time

Register here, courses are listed by date

This 90 minute webinar will bring participants up to speed on the current state of altmetrics, and focus in on changes across the scholarly ecosystem. Through sharing of use cases, tips, and open discussion, this session will help participants to develop a nuanced, strategic framework for incorporating and promoting wider adoption of altmetrics throughout the research lifecycle at their institution and beyond.

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https://www.force11.org/sites/default/files/d7/presentation/1/fsci_mt9_altmetrics_day1.pdf

Definition by National Information Standards Organization NISO (http://www.niso.org/home/): Altmetrics is a broad term that encapsulates the digital collection, creation, and use of multiple forms of assessment that are derived from activity and engagement among diverse stakeholders and scholarly outputs in the research ecosystem.”

Altmetrics are data that help us understand how often and by whom research objects are discussed, shared, and used on the social Web.”

PlumX Metrics – Plum Analytics

Altmetric Explorer

https://www.altmetric.com/login.php

How are researchers & institutions using Altmetric?

  • Research and evaluation services – Identify & track influential research; assess impact & reach
  • Grants and reporting – Target new grants & grantees; demonstrate value to stakeholders
  • Communications and reputation management – Track press/social media; connect to opinion leaders
  • Marketing and promotion – Highlight vital findings; benchmark campaigns and outreach
  • Collaboration and partnerships – Discover disciplinary intersections & collaborative opportunities

DISCOVERY • Find trending research • Unearth conversations among new audiences • Locate collaborators & research opportunities • Identify key opinion leaders • Uncover disciplinary intersection

SHOWCASING • Identifying research to share • Share top mentions • Impact on public policy • Real-time tracking • Identifying key researchers • Recognizing early-career researchers

REPORTING • Grant applications • Funder reporting • Impact requirements • Reputation management • Benchmarking and KPIs (Key performance indicators) • Recruitment & review • Integration into researcher profiles/repositories

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https://www.force11.org/sites/default/files/d7/presentation/1/fsci_mt9_altmetrics_day_2.pdf

https://www.force11.org/sites/default/files/d7/presentation/1/fsci_mt9_altmetrics_fridaysummary.pptx

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more on altmetrics in the library in this IMS blog
https://blog.stcloudstate.edu/ims?s=altmetrics+library

online learning attitudes

online learning attitudes

Students match their preference for hybrid learning with a belief that it is the most effective learning environment for them.

Despite the fact that faculty prefer teaching in a hybrid environment, they remain skeptical of online learning. Nearly half do not agree online 45% learning is effective.

https://library.educause.edu/~/media/files/library/2017/9/studentst2017infog.pdf

 

Students asked what technologies they wish their instructors used more, and we asked faculty what technologies they think could make them more effective instructors. Both agree that content and resource-focused technologies should be incorporated more and social media and tablets should be incorporated less.

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more on the use (or not) of ed technology in the classroom in this IMS blog
https://blog.stcloudstate.edu/ims/2017/04/03/use-of-laptops-in-the-classroom/

Robert Paxton

The Cultural Axis

The Nazi-Fascist New Order for European Culture

by Benjamin G. Martin
Harvard University Press, 370 pp., $39.95
“When I hear the word ‘culture,’ I reach for my revolver.”
Kultur, he explains (along with Bildung, or education), denoted in pre-unification Germany those qualities that the intellectuals and professionals of the small, isolated German middle class claimed for themselves in response to the disdain of the minor German nobles who employed them: intellectual achievement, of course, but also simple virtues like authenticity, honesty, and sincerity.
German courtiers, by contrast, according to the possessors of Kultur, had acquired “civilization” from their French tutors: manners, social polish, the cultivation of appearances. As the German middle class asserted itself in the nineteenth century, the particular virtues of Kultur became an important ingredient in national self-definition. The inferior values of “civilization” were no longer attributed to an erstwhile French-educated German nobility, but to the French themselves and to the West in general.
By 1914, the contrast between Kultur and Zivilisation had taken on a more aggressively nationalist tone. During World War I German patriotic propaganda vaunted the superiority of Germany’s supposedly rooted, organic, spiritual Kultur over the allegedly effete, shallow, cosmopolitan, materialist, Jewish-influenced “civilization” of Western Europe. Martin’s book shows how vigorously the Nazis applied this traditional construct.
Goebbels and Hitler were as obsessed with movies as American adolescents are today with social media.
Music was a realm that Germans felt particularly qualified to dominate. But first the German national musical scene had to be properly organized. In November 1933 Goebbels offered Richard Strauss the leadership of a Reich Music Chamber.
Goebbels organized in Düsseldorf in 1938 a presentation of “degenerate music” following the better-known 1937 exhibition of “degenerate art.”
As with music, the Nazis were able to attract writers outside the immediate orbit of the Nazi and Fascist parties by endorsing conservative literary styles against modernism, by mitigating copyright and royalty problems, and by offering sybaritic visits to Germany and public attention.
Painting and sculpture, curiously, do not figure in this account of the cultural fields that the Nazis and Fascists tried to reorganize “inter-nationally,” perhaps because they had not previously been organized on liberal democratic lines. Picasso and Kandinsky painted quietly in private and Jean Bazaine organized an exhibition with fellow modernists in 1941. Nazi cultural officials thought “degenerate” art appropriate for France.
Science would have made an interesting case study, a contrary one. Germany dominated the world of science before 1933. Germans won fifteen Nobel Prizes in physics, chemistry, and physiology or medicine between 1918 and 1933, more than any other nation. Far from capitalizing on this major soft power asset, Hitler destroyed it by imposing ideological conformity and expelling Jewish scientists such as the talented nuclear physicist Lise Meitner. The soft power of science is fragile, as Americans may yet find out.
American soft power thrived mostly through the profit motive and by offering popular entertainment to the young.

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The Original Axis of Evil

THE ANATOMY   OF FASCISM By Robert O. Paxton. 321 pp. New York: Alfred A. Knopf. $26.

fascism — unlike Communism, socialism, capitalism or conservatism — is a smear word more often used to brand one’s foes than it is a descriptor used to shed light on them.

World War I and the Bolshevik Revolution of 1917 contributed mightily to the advent of fascism. The war generated acute economic malaise, national humiliation and legions of restive veterans and unemployed youths who could be harnessed politically. The Bolshevik Revolution, but one symptom of the frustration with the old order, made conservative elites in Italy and Germany so fearful of Communism that anything — even fascism — came to seem preferable to a Marxist overthrow.

Paxton debunks the consoling fiction that Mussolini and Hitler seized power. Rather, conservative elites desperate to subdue leftist populist movements ”normalized” the fascists by inviting them to share power. It was the mob that flocked to fascism, but the elites who elevated it.

Fascist movements and regimes are different from military dictatorships and authoritarian regimes. They seek not to exclude, but rather to enlist, the masses. They often collapse the distinction between the public and private sphere (eliminating the latter). In the words of Robert Ley, the head of the Nazi Labor Office, the only private individual who existed in Nazi Germany was someone asleep.

t was this need to keep citizens intoxicated by fascism’s dynamism that made Mussolini and Hitler see war as both desirable and necessary. ”War is to men,” Mussolini insisted, ”as maternity is to women.”

For every official American attempt to link Islamic terrorism to fascism, there is an anti-Bush protest that applies the fascist label to Washington’s nationalist rhetoric, assault on civil liberties and warmaking.

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Is Fascism Back?

https://www.project-syndicate.org/onpoint/is-fascism-back-by-robert-o–paxton-2016-01

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Paxton, R. O. (1998). The five stages of fascism. Journal Of Modern History70(1), 1.

Paxton, R. O. (2012). The Civic Foundations of Fascism in Europe: Italy, Spain and Romania, 1870-1945. New Left Review, (74), 140-144.

Paxton, R. O. (2000). Nationalism, Anti-Semitism and Fascism in France (Book Review). Journal Of Modern History72(3), 814.

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more on history in this IMS blog
https://blog.stcloudstate.edu/ims?s=history

Relevant Relatable Reference Services

Topic: Booklist Webinar—Relevant, Relatable Reference Services in Your Library

Host: Booklist Online

Date and Time: Thursday, November 2, 2017 1:00 pm, Central Daylight Time (Chicago, GMT-05:00) Event number: 666 208 689 Registration ID: This event does not require a registration ID Event password: This event does not require a password.

https://alapublishing.webex.com/alapublishing/onstage/g.php?MTID=e85e288426f17320300c4c796440c5994

#referenceDesk @ALA_Booklist

1920 phone service arrives in the library, after decades of phone being around.

1969 William Katz redefines reference.

information as commodity. Faster/cheaper/better. Help doing things rather than finding things (Kenney)

the goal is not getting people to use the library services; it is helping library users accomplish something

not collections, but services.

the reference interaction : approachability; interest; listening/inquiring;

What can I help with; How can I help you? “I’d be happy to help you with that”

marketing is more then promotion. it is figuring out what the market wants you to do. define the market. how do you serve them. then one can figure out the service.

patrons: how and why patrons are seeking info; go where patrons go (social media). where do we go to help them (Snapchat). find benchmarks, make connections. Divine discontentment. my note: but this is a blasphemy, it is against MN nice!

how do we market ourselves? ROI or not? monetary formula to determine the profit against the investment. non profit institutions are not designed to make a profit; sometimes it is useful, sometimes not. Presenting data is good, but keep it simple

innovation, technological advancements. telepresence. VR. Facing disruption. change leadership, flexibility and mobility.

https://www.booklistonline.com/media/webinars/materials/2018/RelevantReference18_Slides.pdf

code4lib 2018

Code2LIB February 2018

http://2018.code4lib.org/

2018 Preconference Voting

10. The Virtualized Library: A Librarian’s Introduction to Docker and Virtual Machines
This session will introduce two major types of virtualization, virtual machines using tools like VirtualBox and Vagrant, and containers using Docker. The relative strengths and drawbacks of the two approaches will be discussed along with plenty of hands-on time. Though geared towards integrating these tools into a development workflow, the workshop should be useful for anyone interested in creating stable and reproducible computing environments, and examples will focus on library-specific tools like Archivematica and EZPaarse. With virtualization taking a lot of the pain out of installing and distributing software, alleviating many cross-platform issues, and becoming increasingly common in library and industry practices, now is a great time to get your feet wet.

(One three-hour session)

11. Digital Empathy: Creating Safe Spaces Online
User research is often focused on measures of the usability of online spaces. We look at search traffic, run card sorting and usability testing activities, and track how users navigate our spaces. Those results inform design decisions through the lens of information architecture. This is important, but doesn’t encompass everything a user needs in a space.

This workshop will focus on the other component of user experience design and user research: how to create spaces where users feel safe. Users bring their anxieties and stressors with them to our online spaces, but informed design choices can help to ameliorate that stress. This will ultimately lead to a more positive interaction between your institution and your users.

The presenters will discuss the theory behind empathetic design, delve deeply into using ethnographic research methods – including an opportunity for attendees to practice those ethnographic skills with student participants – and finish with the practical application of these results to ongoing and future projects.

(One three-hour session)

14. ARIA Basics: Making Your Web Content Sing Accessibility

https://dequeuniversity.com/assets/html/jquery-summit/html5/slides/landmarks.html
Are you a web developer or create web content? Do you add dynamic elements to your pages? If so, you should be concerned with making those dynamic elements accessible and usable to as many as possible. One of the most powerful tools currently available for making web pages accessible is ARIA, the Accessible Rich Internet Applications specification. This workshop will teach you the basics for leveraging the full power of ARIA to make great accessible web pages. Through several hands-on exercises, participants will come to understand the purpose and power of ARIA and how to apply it for a variety of different dynamic web elements. Topics will include semantic HTML, ARIA landmarks and roles, expanding/collapsing content, and modal dialog. Participants will also be taught some basic use of the screen reader NVDA for use in accessibility testing. Finally, the lessons will also emphasize learning how to keep on learning as HTML, JavaScript, and ARIA continue to evolve and expand.

Participants will need a basic background in HTML, CSS, and some JavaScript.

(One three-hour session)

18. Learning and Teaching Tech
Tech workshops pose two unique problems: finding skilled instructors for that content, and instructing that content well. Library hosted workshops are often a primary educational resource for solo learners, and many librarians utilize these workshops as a primary outreach platform. Tackling these two issues together often makes the most sense for our limited resources. Whether a programming language or software tool, learning tech to teach tech can be one of the best motivations for learning that tech skill or tool, but equally important is to learn how to teach and present tech well.

This hands-on workshop will guide participants through developing their own learning plan, reviewing essential pedagogy for teaching tech, and crafting a workshop of their choice. Each participant will leave with an actionable learning schedule, a prioritized list of resources to investigate, and an outline of a workshop they would like to teach.

(Two three-hour sessions)

23. Introduction to Omeka S
Omeka S represents a complete rewrite of Omeka Classic (aka the Omeka 2.x series), adhering to our fundamental principles of encouraging use of metadata standards, easy web publishing, and sharing cultural history. New objectives in Omeka S include multisite functionality and increased interaction with other systems. This workshop will compare and contrast Omeka S with Omeka Classic to highlight our emphasis on 1) modern metadata standards, 2) interoperability with other systems including Linked Open Data, 3) use of modern web standards, and 4) web publishing to meet the goals medium- to large-sized institutions.

In this workshop we will walk through Omeka S Item creation, with emphasis on LoD principles. We will also look at the features of Omeka S that ease metadata input and facilitate project-defined usage and workflows. In accordance with our commitment to interoperability, we will describe how the API for Omeka S can be deployed for data exchange and sharing between many systems. We will also describe how Omeka S promotes multiple site creation from one installation, in the interest of easy publishing with many objects in many contexts, and simplifying the work of IT departments.

(One three-hour session)

24. Getting started with static website generators
Have you been curious about static website generators? Have you been wondering who Jekyll and Hugo are? Then this workshop is for you

My notehttps://opensource.com/article/17/5/hugo-vs-jekyll

But this article isn’t about setting up a domain name and hosting for your website. It’s for the step after that, the actual making of that site. The typical choice for a lot of people would be to use something like WordPress. It’s a one-click install on most hosting providers, and there’s a gigantic market of plugins and themes available to choose from, depending on the type of site you’re trying to build. But not only is WordPress a bit overkill for most websites, it also gives you a dynamically generated site with a lot of moving parts. If you don’t keep all of those pieces up to date, they can pose a significant security risk and your site could get hijacked.

The alternative would be to have a static website, with nothing dynamically generated on the server side. Just good old HTML and CSS (and perhaps a bit of Javascript for flair). The downside to that option has been that you’ve been relegated to coding the whole thing by hand yourself. It’s doable, but you just want a place to share your work. You shouldn’t have to know all the idiosyncrasies of low-level web design (and the monumental headache of cross-browser compatibility) to do that.

Static website generators are tools used to build a website made up only of HTML, CSS, and JavaScript. Static websites, unlike dynamic sites built with tools like Drupal or WordPress, do not use databases or server-side scripting languages. Static websites have a number of benefits over dynamic sites, including reduced security vulnerabilities, simpler long-term maintenance, and easier preservation.

In this hands-on workshop, we’ll start by exploring static website generators, their components, some of the different options available, and their benefits and disadvantages. Then, we’ll work on making our own sites, and for those that would like to, get them online with GitHub pages. Familiarity with HTML, git, and command line basics will be helpful but are not required.

(One three-hour session)

26. Using Digital Media for Research and Instruction
To use digital media effectively in both research and instruction, you need to go beyond just the playback of media files. You need to be able to stream the media, divide that stream into different segments, provide descriptive analysis of each segment, order, re-order and compare different segments from the same or different streams and create web sites that can show the result of your analysis. In this workshop, we will use Omeka and several plugins for working with digital media, to show the potential of video streaming, segmentation and descriptive analysis for research and instruction.

(One three-hour session)

28. Spark in the Dark 101 https://zeppelin.apache.org/
This is an introductory session on Apache Spark, a framework for large-scale data processing (https://spark.apache.org/). We will introduce high level concepts around Spark, including how Spark execution works and it’s relationship to the other technologies for working with Big Data. Following this introduction to the theory and background, we will walk workshop participants through hands-on usage of spark-shell, Zeppelin notebooks, and Spark SQL for processing library data. The workshop will wrap up with use cases and demos for leveraging Spark within cultural heritage institutions and information organizations, connecting the building blocks learned to current projects in the real world.

(One three-hour session)

29. Introduction to Spotlight https://github.com/projectblacklight/spotlight
http://www.spotlighttechnology.com/4-OpenSource.htm
Spotlight is an open source application that extends the digital library ecosystem by providing a means for institutions to reuse digital content in easy-to-produce, attractive, and scholarly-oriented websites. Librarians, curators, and other content experts can build Spotlight exhibits to showcase digital collections using a self-service workflow for selection, arrangement, curation, and presentation.

This workshop will introduce the main features of Spotlight and present examples of Spotlight-built exhibits from the community of adopters. We’ll also describe the technical requirements for adopting Spotlight and highlight the potential to customize and extend Spotlight’s capabilities for their own needs while contributing to its growth as an open source project.

(One three-hour session)

31. Getting Started Visualizing your IoT Data in Tableau https://www.tableau.com/
The Internet of Things is a rising trend in library research. IoT sensors can be used for space assessment, service design, and environmental monitoring. IoT tools create lots of data that can be overwhelming and hard to interpret. Tableau Public (https://public.tableau.com/en-us/s/) is a data visualization tool that allows you to explore this information quickly and intuitively to find new insights.

This full-day workshop will teach you the basics of building your own own IoT sensor using a Raspberry Pi (https://www.raspberrypi.org/) in order to gather, manipulate, and visualize your data.

All are welcome, but some familiarity with Python is recommended.

(Two three-hour sessions)

32. Enabling Social Media Research and Archiving
Social media data represents a tremendous opportunity for memory institutions of all kinds, be they large academic research libraries, or small community archives. Researchers from a broad swath of disciplines have a great deal of interest in working with social media content, but they often lack access to datasets or the technical skills needed to create them. Further, it is clear that social media is already a crucial part of the historical record in areas ranging from events your local community to national elections. But attempts to build archives of social media data are largely nascent. This workshop will be both an introduction to collecting data from the APIs of social media platforms, as well as a discussion of the roles of libraries and archives in that collecting.

Assuming no prior experience, the workshop will begin with an explanation of how APIs operate. We will then focus specifically on the Twitter API, as Twitter is of significant interest to researchers and hosts an important segment of discourse. Through a combination of hands-on and demos, we will gain experience with a number of tools that support collecting social media data (e.g., Twarc, Social Feed Manager, DocNow, Twurl, and TAGS), as well as tools that enable sharing social media datasets (e.g., Hydrator, TweetSets, and the Tweet ID Catalog).

The workshop will then turn to a discussion of how to build a successful program enabling social media collecting at your institution. This might cover a variety of topics including outreach to campus researchers, collection development strategies, the relationship between social media archiving and web archiving, and how to get involved with the social media archiving community. This discussion will be framed by a focus on ethical considerations of social media data, including privacy and responsible data sharing.

Time permitting, we will provide a sampling of some approaches to social media data analysis, including Twarc Utils and Jupyter Notebooks.

(One three-hour session)

news RSS

Why RSS Still Beats Facebook and Twitter for Tracking News

What is RSS?

For the completely uninitiated, RSS is just a standardized way of presenting text and images in a feed that can be used by a variety of apps and web services. It is just like how Twitter has a standard way of presenting text and images that all the various Twitter clients understand.

As we’ve already alluded to, when you follow the news via social media, you’re relying on other people bringing you the news, unless you’re following individual news stories. RSS is like getting your newspaper of choice delivered to the front door rather than relying on heading down to the local bar to listen in on what everyone’s shouting about.

With only one page to visit rather than dozens to catch up on, you can spend less time aimlessly drifting around and more time catching up on the posts that matter.

It’s not just for news

Basically anything you might want to keep track of and not miss because of the cacophony of voices on social media,

The always-useful IFTTT (If This Then That) is fluent in RSS, giving you even more ways to make use of RSS. You can build applets to generate tweets or Facebook posts or Instagram updates from a particular feed. Zapier is another service that can take RSS feeds from anywhere in the web and plug them into other apps and platforms.

Finding an RSS reader

Digg ReaderFeedlyPanda is a clean and relatively young news aggregator,

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more on RSS in this IMS blog
https://blog.stcloudstate.edu/ims?s=rss

Grant America for Bulgaria

http://www.us4bg.org/areas/education/

Proposal |Project Title

The 21st Century Skills of the Academic Librarian in Bulgaria

Applicant:
Plamen Miltenoff, PhD, MLIS, http://web.stcloudstate.edu/pmiltenoff/faculty/
My experience and connections with the library organizations and professionals from Moldova, Bulgaria and Austria, as well as my 17+ years working at the St. Cloud State University library provides me with an opportunity for comparison and, consequently, proposal for collaborative practices with Bulgarian academic librarians.

Project Duration: one year

Problem Identification: Through the years, my work with faculty and librarians from Shoumen University (http://shu-bg.net/ ), Plovdiv University (https://uni-plovdiv.bg/), New Bulgarian University (https://nbu.bg/),  the American University (https://www.aubg.edu/) and Sofia University (https://www.uni-sofia.bg/) helped me identify differences and similarities in the work of the Bulgarian educational institutions and academia from abroad.

The role of the academic librarian in the educational process is different/limited in Bulgaria compared to the United States. During a collaboration on gamifying library instruction (http://web.stcloudstate.edu/pmiltenoff/bi/), the NBU librarians demonstrated their propensity to shift their campus role close to the campus role of American librarians, yet in general the Bulgarian library guild remains traditional in their view of their responsibilities toward the educational process on campus.

Project Objectives:

This proposal aims regular discussions among professionals from Bulgarian and American (possibly other nations) librarians to determine the framework regarding librarian’s responsibilities. Are academic librarians faculty members or staff? Do they have teaching or service (or both) responsibilities? What are 20th century academic librarians’ responsibilities are to be preserved? Updated? What are the 21st century responsibilities to be gained? What is the relationship between academic librarians and faculty? What is expected from an academic librarians to ensure learning happens? To benefit faculty’s teaching?
A comparison of academic library structures, job descriptions, models and discourses can lead to deep[er] analysis of existing structures and possible reorganizations to improve the role of the library in particular and the efficiency of the educational institution in general.
Comparisons of topics and syllabi: multiliteraices as successor of information literacy? Is the academic library the hub for technological innovations (e.g makerspaces, 3D printing, virtual reality/augmented reality) and if not, what is the academic library role in the process?
Other relevant topics / issues are expected to transpire during such discourse.

Project Description:

The project is organized in collaboration of synchronous and asynchronous character during the span of one academic year. Three synchronous sessions each semester (six sessions for the entire semester) will provide a forum through e-conferencing tools (e.g. Adobe Connect, WebEx, Skype, Google Hangout etc.) for live discussions and planning. Weekly asynchronous dialog through social media (e.g. blog, Facebook Group, Google Group etc.) will provide the platform/ hub/ forum daily/detailed preparation for the monthly synchronous meetings.

Most valuable feedback through the weekly asynchronous discussions will be voted by participants and three best weekly contributions will be awarded badges. At the end of the academic year, the three contributors with largest collection of badges will be awarded cost for registration fee, travel and lodging to an important European conference regarding libraries and education.

The experience and lessons from the process will be summed up, published and presented at local (Bulgarian), regional (Balkans) and international (European, U.S.) educational conferences and events. Similar cross-cultural experiences and studies will be research and comparison and future collaboration will be sought.

Impact:

  • The use of synchronous tools will provide technological and didactical practice for academic librarians; an experience they later can apply in their service to the campus community.
  • Same with the asynchronous tools / social media
  • The practice and experience of using social media for institutional purposes can help librarians figure out pertinent outreach to the recent and incoming students (Millennials and Gen Y)
  • The use of social media will provide transparency and participatory governing of the process.

Sustainability:

The lessons from such endeavor aim to bring closer collaboration and understanding between academic librarians and campus faculty. Such collaboration can be measured, as well as impact of improved teaching and improved learning. The measurements should convince university administration to further support the continues process of cross-cultural collaboration between academic librarians.

phones in the classroom

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.
Liz Kolb September 11, 2017

https://www.edutopia.org/article/3-tips-managing-phone-use-class
Ten is now the average age when children receive their first cell phones
Build a digital citizenship curriculum that includes mobile device use.

Ask your students questions such as:

  • What do you like to do on your cell phone and why? (If they don’t have one, what would they like to do?)
  • What are the most popular apps and websites you use?
  • What do you think are inappropriate ways that cell phones have been used?
  • What is poor cell phone etiquette? Why?
  • How can cell phones help you learn?
  • How can cell phones distract from your learning?
  • How do you feel about your cell phone and the activities you do on your phone?
  • What should teachers know about your cell phone use that you worry we do not understand?
  • Do you know how to use your cell phone to gather information, to collaborate on academic projects, to evaluate websites?
  • How can we work together to create a positive mobile mental health?

Using a Stoplight Management Approach

Post a red button on the classroom door: the cell phone parking lot.

Post a yellow button on the classroom door: Students know their cell phones should be on silent (vibrate) and placed face down in the upper right-hand corner of their desk. They will be using them in class, but not the whole time.

Post a green button on the classroom door: Students know they should have their phones turned on (either silenced or set on vibrate) and placed face up in ready position to use throughout the class.

Establishing a Class Contract

Ask your students to help you develop social norms for what is and is not appropriate cell phone use during green and yellow button times. Should they be allowed to go on their social media networks during class? Why or why not?

Ask them to brainstorm consequences and write them into a class contract.

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more on the use of smart phones in the classroom in this IMS blog
https://blog.stcloudstate.edu/ims?s=phone+classroom

Zello for library use

learning from real life experience

Today’s report on the use of Zello (http://www.marketwatch.com/story/houston-residents-and-civilians-turn-to-zello-app-to-coordinate-rescue-efforts-2017-08-29) by Houston residents during Hurricane Harvey has parallels with the organizational efforts of using Zello by the Venezuelan people (https://zello.com/channels/k/b2dDl) in 2014. (https://advox.globalvoices.org/2014/02/23/walkie-talkie-app-zello-blocked-in-venezuela/)

Zello, HeyTell and Voxer Make Your Smartphone a Walkie-Talkie (NYT, 2012) are apps for smart phones and mobile devices.
They are free.
They do much more than a physical walkie-talkie (e.g. send visuals, record messages)
They are more environment friendly, since do not require physical presence and so much battery power: https://www.compareninja.com/tables/single/60573

Yo is a similar messaging app: https://blog.stcloudstate.edu/ims/2014/07/09/social-media-yo/

Library and University use:

In 2014, we proposed to the middle management the consideration of Yo as alarm system:

From: Miltenoff, Plamen
Sent: Tuesday, July 08, 2014 9:17 PM
To: ??????, Mark A. <???????@stcloudstate.edu>
Subject: FW: Yo at LRS

Good evening Mark

Based on the article below:

http://www.businessinsider.com/yo-updates-on-israel-missile-attacks-2014-7

The upper management might consider fire and/or tornado alarm app for SCSU students similarly to the one, which the Israelis are using to back up their alarm system.

I am confident that some other US school is already thinking about the same and developing probably the app.

Thanks for considering…

Plamen

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From: Miltenoff, Plamen
Sent: Tuesday, July 8, 2014 8:59 PM
To: ???????, Colette ?????????
Cc: ??????, Joseph
Subject: Yo at LRS

Collette,

I am not sure if this news

http://www.businessinsider.com/yo-updates-on-israel-missile-attacks-2014-7

will increase your interest toward “Yo” since you said that you are not interested in politics

As shared with Joe several months ago about “Zello” being used in Venezuela  (http://www.huffingtonpost.ca/2014/02/21/venezuela-blocks-zello-ap_n_4830452.html ), ingenuity during political events can give us great ideas how to use social media apps in daily work

I would like to ask you again to consider testing Yo and sharing your ideas how we can apply it at LRS
It is worth checking the penetration of Yo among SCSU students and use it.

Thank you and lkng forward to hearing your opinion

Plamen

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benefits for the library and potentially for the campus:

  1. reduce financial cost: batteries for the walkie talkies and the wear off of the walkie talkie can be replaced by a virtual app (again, apps for each of the three potential candidates are free)
  2. environmentally friendly. Apps are virtual. Walkie talkies are physical
  3. improve productivity. walkie talkie allow only talk. Apps allow: audio, video (images) and text
  4. raise the level of critical thinking (increase productivity by proxy): the use of several media: text, visuals, audio will allow users to think in a wider diapason when troubleshooting and/or doing their tasks
  5. the library can be the sandbox to smooth out details of the application and lessons learned can help replace walkie talkies across campus with 21st century tools and increase productivity campus wide.

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previous posts on Zello in this IMS blog
https://blog.stcloudstate.edu/ims?s=zello

 

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