Libraries supporting social inclusion for refugees and immigrants
UNESCO emphasizes the importance of social inclusion for international
migrants and encourages cities and local governments to “ensure social rights
for migrants to adequate housing, education, health and social care, welfare
and decent standard of living according to basic needs such as food, energy
and water.” Libraries can play an important role in helping new arrivals
acclimate and thrive in a new community.
Do you have a story to share about how your library, on its own or in
collaboration with community organizations, is providing social services and
support for refugees and immigrants? Do you have advice on creating successful
programming to support refugees and immigrants?
Proposal to the SCSU library administration:
Good afternoon,
I will be submitting a proposal about my individual work in that area:
In the fall of 2015, I organized a campus-wide meeting, including St. Cloud community members, on refugees and migrants, by inviting one Syrian and one Somali refugees:
I also reached out across campus (e.g. Dan Wildeson with the Holocaust Center, Geoffrey Tabakin, Stephen Philion).
I organized also the online presence by delivering the personal stories of three refugees:
I also maintain a FB group for the class and in conjunction with the blog (you need to request permission to enter the FB group): https://www.facebook.com/groups/hons221
I am formally proposing / requesting to transition my individual efforts and offering the library to support me in expanding my acitivies on this topic
Here is my rational:
If not on campus, at least in the library, I am the only refugee and for that matter an immigrant. I have the understanding and the compassion of someone, who personally have experienced the hardship of being and immigrant and refugee.
I have amounted information and experience presenting the information and engaging the audience in a discussion regarding a rather controversial (for St. Cloud) issue
I have the experience and skills to conduct such discussions both F2F and online
Based on my rational, here are activities I am proposing:
The library supports a monthly F2F meetings, where I am taking the responsibility to host students with refugee and/or migrant status and facilitate a conversation among those students and other students, faculty, staff, who would like to learn more about the topic and discuss related issues.
Library support constitutes of: e.g. necessary information willingly and actively shared at Reference and Circulation desk. Library faculty and staff willingly and actively promoting the information regarding this opportunity when occasions arise.
The library supports my campus-wide efforts to engage faculty, staff and students. Engagement includes: e.g., proposals to faculty to present in their classes on including refugees and immigrants but related to their classes; assisting students with research and bibliography on their papers related to refugees and immigrants; assisting faculty and students with presentations including refugees and immigrants etc.
Library support constitutes of: e.g. necessary information willingly and actively shared at Reference and Circulation desk. Library faculty and staff willingly and actively promoting the information regarding this opportunity when occasions arise.
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.
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
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.
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
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
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
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
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
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
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
Minecraft for Higher Ed? Try it. Pros, Cons, Recommendations?
Description: Why Minecraft, the online video game? How can Minecraft improve learning for higher education? We’ll begin with a live demo in which all can participate (see “Minecraft for Free”). We’ll review “Examples, Not Rumors” of successful adaptations and USES of Minecraft for teaching/learning in higher education. Especially those submitted in advance And we’ll try to extract from these activities a few recommendations/questions/requests re Minecraft in higher education.
Callaghan, N. (2016). Investigating the role of Minecraft in educational learning environments. Educational Media International, 53(4), 244-260. doi:10.1080/09523987.2016.1254877
Noelene Callaghan dissects the evolution in Australian education from a global perspective. She rightfully draws attention (p. 245) to inevitable changes in the educational world, which still remain ignored: e.g., the demise of “traditional” LMS (Educase is calling for their replacement with digital learning environments https://blog.stcloudstate.edu/ims/2017/07/06/next-gen-digital-learning-environment/ and so does the corporate world of learning: https://blog.stcloudstate.edu/ims/2017/03/28/digital-learning/ ), the inevitability of BYOD (mainly by the “budget restrictions and sustainability challenges” (p. 245); by the assertion of cloud computing, and, last but not least, by the gamification of education.
p. 245 literature review. In my paper, I am offering more comprehensive literature review. While Callaghan focuses on the positive, my attempt is to list both pros and cons: http://scsu.mn/1F008Re
246 General use of massive multiplayer online role playing games (MMORPGs)
levels of interaction have grown dramatically and have led to the creation of general use of massive multiplayer online role playing games (MMORPGs)
247 In teaching and learning environments, affordances associated with edugames within a project-based learning (PBL) environment permit:
These affordances develop both social and cognitive abilities of students
Nebel, S., Schneider, S., Beege, M., Kolda, F., Mackiewicz, V., & Rey, G. (2017). You cannot do this alone! Increasing task interdependence in cooperative educational videogames to encourage collaboration. Educational Technology Research & Development, 65(4), 993-1014. doi:10.1007/s11423-017-9511-8
Abrams, S. S., & Rowsell, J. (2017). Emotionally Crafted Experiences: Layering Literacies in Minecraft. Reading Teacher, 70(4), 501-506.
Nebel, S., Schneider, S., & Daniel Rey, G. (2016). Mining Learning and Crafting Scientific Experiments: A Literature Review on the Use of Minecraft in Education and Research. Source: Journal of Educational Technology & Society, 19(192), 355–366. Retrieved from http://www.jstor.org/stable/jeductechsoci.19.2.355
Cipollone, M., Schifter, C. C., & Moffat, R. A. (2014). Minecraft as a Creative Tool: A Case Study. International Journal Of Game-Based Learning, 4(2), 1-14.
Niemeyer, D. J., & Gerber, H. R. (2015). Maker culture and Minecraft : implications for the future of learning. Educational Media International, 52(3), 216-226. doi:10.1080/09523987.2015.1075103
Nebel, S., Schneider, S., & Daniel Rey, G. (2016). Mining Learning and Crafting Scientific Experiments: A Literature Review on the Use of Minecraft in Education and Research. Journal of Educational Technology & Society, 19(192), 355–366. Retrieved from http://www.jstor.org/stable/jeductechsoci.19.2.355
Wilkinson, B., Williams, N., & Armstrong, P. (2013). Improving Student Understanding, Application and Synthesis of Computer Programming Concepts with Minecraft. In The European Conference on Technology in the Classroom 2013. Retrieved from http://iafor.info/archives/offprints/ectc2013-offprints/ECTC2013_0477.pdf
Uusi-Mäkelä, M., & Uusi-Mäkelä, M. (2014). Immersive Language Learning with Games: Finding Flow in MinecraftEdu. EdMedia: World Conference on Educational Media and Technology (Vol. 2014). Association for the Advancement of Computing in Education (AACE). Retrieved from https://www.learntechlib.org/noaccess/148409/
Birt, J., & Hovorka, D. (2014). Effect of mixed media visualization on learner perceptions and outcomes. In 25th Australasian Conference on Information Systems (pp. 1–10). Retrieved from http://epublications.bond.edu.au/fsd_papers/74
Al Washmi, R., Bana, J., Knight, I., Benson, E., Afolabi, O., Kerr, A., Hopkins, G. (2014). Design of a Math Learning Game Using a Minecraft Mod. https://doi.org/10.13140/2.1.4660.4809
University libraries have held collections of books and printed material throughout their existence and continue to be perceived as repositories for physical collections. Other non-print specialized collections of interest have been held in various departments on campus such as Anthropology, Art, and Biology due to the unique needs of the collections and their usage. With the advent of electronic media, it becomes possible to store these non-print collections in a central place, such as the Libray.
The skills needed to curate artifacts from an archeological excavation, biological specimens from various life forms, and sculpture work are very different, making it difficult for smaller university libraries to properly hold, curate, and make available such collections. In addition, faculty in the various departments tend to want those collections near their coursework and research, so it can be readily available to students and researchers. With the expansion of online learning, the need for such availability becomes increasingly pronounced.
With the advent of 3 dimensional (3D) scanners, it has become possible for a smaller library to hold digital representations of these collections in an archive that can be curated from the various departments by experts in the discipline. The Library can then make the digital representations available to other researchers, students, and the public through kiosks in the Library or via the Internet. Current methods to scan and store an artifact in 3Dstill require expertise not often found in a Library.
We propose to use existing technology to build an easy-to-use system to scan smaller artifacts in 3D. The project will include purchase and installation of a workstation in the Library where the artifact collection can be accessed using a large touch-screen monitor, and a portable, easy-to-use 3D scanning station. Curators of collections from various departments on the St. Cloud State University campus can check out the scanning station, connect to power and Internet where the collection is located, and scan their collection into the libraries digital archives, making the collection easily available to students, other researchers and the public.
The project would include assembly of two workstations previously mentioned and potentially develop the robotic scanner. Software would be produced to automate the workflow from the scanner to archiving the digital representation and then make the collection available on the Internet.
This project would be a collaboration between the St. Cloud State University Library (https://www.stcloudstate.edu/library/ and Visualization Laboratory (https://www.facebook.com/SCSUVizLab/). The project would use the expertise and services of the St. Cloud State Visualization Laboratory. Dr. Plamen Miltenoff, a faculty with the Library will coordinate the Library initiatives related to the use of the 3D scanner. Mark Gill, Visualization Engineer, and Dr. Mark Petzold, Associate Professor of Electrical and Computer Engineering will lead a group of students in developing the software to automate the scanning, storage, and retrieval of the 3D models. The Visualization Lab has already had success in 3D scanning objects for other departments and in creating interactive displays allowing retrieval of various digital content, including 3D scanned objects such animal skulls and video. A collaboration between the Library, VizLab and the Center for Teaching and Learning (, https://www.stcloudstate.edu/teaching/) will enable campus faculty to overcome technical and financial obstacles. It will promote the VizLab across campus, while sharing its technical resources with the Library and making those resources widely available across campus. Such work across silos will expose the necessity (if any) of standardization and will help faculty embrace stronger collaborative practices as well as spur the process of reproduction of best practices across disciplines.
Budget:
Hardware
Cost
42” Touch Screen Monitor
$2200
Monitor Mount
$400
2 Computer Workstations
$5000
Installation
$500
Cart for Mobile 3D Scanner
$1000
3D Scanner (either purchase or develop in-house)
$2000
Total
$11100
The budget covers two computer workstations. One will be installed in the library as a way to access the digital catalog, and will include a 42 inch touch screen monitor mounted to a wall or stand. This installation will provide students a way to interact with the models in a more natural way. The second workstation would be mounted on a mobile cart and connected to the 3D scanner. This would allow collection curators from different parts of campus to check out the scanner and scan their collections. The ability to bring the scanner to the collection would increase the likelihood the collections to be scanned into the library collection.
The 3D scanner would either be purchased off-the shelf or designed by a student team from the Engineering Department. A solution will be sought to use and minimize the amount of training the operator would need. If the scanner is developed in-house, a simple optical scanner such as an XBox Kinect device and a turntable or robotic arm will be used. Support for the XBox Kinect is built into Microsoft Visual Studio, thus creating the interface efficient and costeffective.
Dr. Miltenoff is part of a workgroup within the academic library, which works with faculty, students and staff on the application of new technologies in education. Dr. Miltenoff’s most recent research with Mark Gill is on the impact of Video 360 on students during library orientation:http://web.stcloudstate.edu/pmiltenoff/bi/
Mark Petzold, Ph.D. mcpetzold@stcloudstate.edu
320-308-4182
Dr. Petzold is an Associate Professor in Electrical and Computer Engineering. His current projects involve visualization of meteorological data in a virtual reality environment and research into student retention issues. He is co-PI on a $5 million NSF S-STEM grant which gives scholarships to low income students and investigates issues around student transitions to college.
Mr. Gill is a Visualization Engineer for the College of Science and Engineering and runs the Visualization Laboratory. He has worked for several major universities as well as Stennis Space Center and Mechdyne, Inc. He holds a Masters of Science in Software Engineering.
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University of Nevada, Reno and Pennsylvania State University 41 campus libraries to include collaborative spaces where faculty and students gather to transform virtual ideas into reality.
Maker Commons in the Modern Library 6 REASONS 3D PRINTERS SHOULD BE IN YOUR LIBRARY
1. Librarians Know How to Share 2. Librarians Work Well with IT People 3. Librarians Serve Everybody 4. Librarians Can Fill Learning Gaps 5. Librarians like Student Workers 6. Librarians are Cross-Discipline
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
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.
David Demaine, S., Lemmer, C. A., Keele, B. J., & Alcasid, H. (2015). Using Digital Badges to Enhance Research Instruction in Academic Libraries. In B. L. Eden (Ed.), Enhancing Teaching and Learning in the 21st-Century Academic Library: Successful Innovations That Make a Difference (2015th ed.). Retrieved from https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2882671
At their best, badges can create a sort of interactive e-resume.
the librarian may be invited into the classroom, or the students may be sent to the Iibrary for a single research lesson on databases and search tem1s- not enough for truly high-quality research. A better alternative may be that the professor require the students to complete a series of badges- designed, implemented, and managed by the librarian- that build thorough research skills and ultimately produce a better paper.
Meta- badges are s impl y badges that indicate comp letion o f multiple related badges.
Authentication (determining that the badge has not been altered) and validation/verification (checking that the badge has actually been earned and issued by the stated issuer) are major concerns. lt is also important, particularly in the academic context, to make sure that the badge does not come to replace the learning it represents. A badge is a symbol that other skills and knowledge exist in this individual’s portfolio of skills and talents. Therefore, badges awarded in the educational context must reflect time and effort and be based on vetted standards, or they will become empty symbols
Digital credentialing recognizes “learning of many kinds which are acquired beyond formal education institutions .. . ; it proliferates and disperses author- ity over what learning to recognize; and it provides a means of translation and commensuration across multiple spheres” (Oineck, 2012, p. I)
University digital badge projects are rarely a top-down undertaking. Typi- cally, digital badge programs arise from collaborative efforts “of people agi- tating from the middle” (Raths, 2013).
metadata: counts of papers by yer, researcher, institution, province, region and country. scientific fields subfields
metadata in one-credit course as a topic:
publisher – suppliers =- Elsevier processes – Scopus Data
h-index: The h-index is an author-level metric that attempts to measure both the productivity and citation impact of the publications of a scientist or scholar. The index is based on the set of the scientist’s most cited papers and the number of citations that they have received in other publications.
The era of e-science demands new skill sets and competencies of researchers to ensure their work is accessible, discoverable and reusable. Librarians are naturally positioned to assist in this education as part of their liaison and information literacy services.
Research data literacy and the library
Christian Lauersen, University of Copenhagen; Sarah Wright, Cornell University; Anita de Waard, Elsevier
Data Literacy: access, assess, manipulate, summarize and present data
Statistical Literacy: think critically about basic stats in everyday media
Information Literacy: think critically about concepts; read, interpret, evaluate information
data information literacy: the ability to use, understand and manage data. the skills needed through the whole data life cycle.
Shield, Milo. “Information literacy, statistical literacy and data literacy.” I ASSIST Quarterly 28. 2/3 (2004): 6-11.
Carlson, J., Fosmire, M., Miller, C. C., & Nelson, M. S. (2011). Determining data information literacy needs: A study of students and research faculty. Portal: Libraries & the Academy, 11(2), 629-657.
embedded librarianship,
Courses developed: NTRESS 6600 research data management seminar. six sessions, one-credit mini course
NEW ROLESFOR LIbRARIANS: DATAMANAgEMENTAND CURATION
the capacity to manage and curate research data has not kept pace with the ability to produce them (Hey & Hey, 2006). In recognition of this gap, the NSF and other funding agencies are now mandating that every grant proposal must include a DMP (NSF, 2010). These mandates highlight the benefits of producing well-described data that can be shared, understood, and reused by oth-ers, but they generally offer little in the way of guidance or instruction on how to address the inherent issues and challenges researchers face in complying. Even with increasing expecta-tions from funding agencies and research com-munities, such as the announcement by the White House for all federal funding agencies to better share research data (Holdren, 2013), the lack of data curation services tailored for the “small sciences,” the single investigators or small labs that typically comprise science prac-tice at universities, has been identified as a bar-rier in making research data more widely avail-able (Cragin, Palmer, Carlson, & Witt, 2010).Academic libraries, which support the re-search and teaching activities of their home institutions, are recognizing the need to de-velop services and resources in support of the evolving demands of the information age. The curation of research data is an area that librar-ians are well suited to address, and a num-ber of academic libraries are taking action to build capacity in this area (Soehner, Steeves, & Ward, 2010)
REIMAgININg AN ExISTINg ROLEOF LIbRARIANS: TEAChINg INFORMATION LITERACY SkILLS
By combining the use-based standards of information literacy with skill development across the whole data life cycle, we sought to support the practices of science by develop-ing a DIL curriculum and providing training for higher education students and research-ers. We increased ca-pacity and enabled comparative work by involving several insti-tutions in developing instruction in DIL. Finally, we grounded the instruction in the real-world needs as articu-lated by active researchers and their students from a variety of fields
Chapter 1 The development of the 12 DIL competencies is explained, and a brief compari-son is performed between DIL and information literacy, as defined by the 2000 ACRL standards.
chapter 2 thinking and approaches toward engaging researchers and students with the 12 competencies, a re-view of the literature on a variety of educational approaches to teaching data management and curation to students, and an articulation of our key assumptions in forming the DIL project.
chapter 4 because these lon-gitudinal data cannot be reproduced, acquiring the skills necessary to work with databases and to handle data entry was described as essential. Interventions took place in a classroom set-ting through a spring 2013 semester one-credit course entitled Managing Data to Facilitate Your Research taught by this DIL team.
chapter 5 embedded librar-ian approach of working with the teaching as-sistants (TAs) to develop tools and resources to teach undergraduate students data management skills as a part of their EPICS experience.
Lack of organization and documentation presents a bar-rier to (a) successfully transferring code to new students who will continue its development, (b) delivering code and other project outputs to the community client, and (c) the center ad-ministration’s ability to understand and evalu-ate the impact on student learning.
skill sessions to deliver instruction to team lead-ers, crafted a rubric for measuring the quality of documenting code and other data, served as critics in student design reviews, and attended student lab sessions to observe and consult on student work
chapter 6 Although the faculty researcher had created formal policies on data management practices for his lab, this case study demonstrated that students’ adherence to these guidelines was limited at best. Similar patterns arose in discus-sions concerning the quality of metadata. This case study addressed a situation in which stu-dents are at least somewhat aware of the need to manage their data;
chapter 7 University of Minnesota team to design and implement a hybrid course to teach DIL com-petencies to graduate students in civil engi-neering.
stu-dents’ abilities to understand and track issues affecting the quality of the data, the transfer of data from their custody to the custody of the lab upon graduation, and the steps neces-sary to maintain the value and utility of the data over time.
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.
Pay close attention to your website’s analytics. Where are visitors going? How long are they staying? When do they leave? Are they finding where they want to go while they are there?
92 percent of Americans 18-29 years old own a smartphone. They will interact with your site from their phone. If it is frustrating, they will be frustrated with the school. The site needs a responsive design that will allow it to adapt to the size of any screen.
implement A/B testing to make sure the new design is improving on functionality and not just aesthetics. Also, make sure your website is ADA compliant.
Education is expensive. If we can reduce textbook costs, students may be able to take more classes, complete their programs more quickly, and be more successful. Once faculty have participated in an introductory webinar, they may review an open textbook that is located in the Open Textbook Library (open.umn.edu). Working with the Open Textbook Network and Library, faculty will receive a $200.00 honorarium once the review is completed.
Round 1
September 7, 2017
Round 4: Deadline to register for open textbook webinar
