Publisher / Organization: Athabasca University Press
Year founded: 2000
Description: The International Review of Research in Open and Distributed Learning disseminates original research, theory, and best practice in open and distributed learning worldwide.
Publisher / Organization: The University of Illinois at Chicago- University Library
Year founded: 1996
Description: First Monday is among the very first open access journals in the EdTech field. The journal’s subject matter encompasses the full range of Internet issues, including educational technologies, social media and web search. Contributors are urged via author guidelines to use simple explanations and less complex sentences and to be mindful that a large proportion of their readers are not part of academia and do not have English as a first language.
Academic Management: University of Catalonia (UOC)
Year founded: 2004
Description: This journal aims to: provide a vehicle for scholarly presentation and exchange of information between professionals, researchers and practitioners in the technology-enhanced education field; contribute to the advancement of scientific knowledge regarding the use of technology and computers in higher education; and inform readers about the latest developments in the application of information technologies (ITs) in higher education learning, training, research and management.
Description: Online Learning promotes the development and dissemination of new knowledge at the intersection of pedagogy, emerging technology, policy, and practice in online environments. The journal has been published for over 20 years as the Journal of Asynchronous Learning Networks (JALN) and recently merged with the Journal of Online Learning and Teaching (JOLT).
Publisher / Organization: International Forum of Educational Technology & Society
Year founded:1998
Description: Educational Technology & Society seeks academic articles on the issues affecting the developers of educational systems and educators who implement and manage these systems. Articles should discuss the perspectives of both communities – the programmers and the instructors. The journal is currently still accepting submissions for ongoing special issues, but will cease publication in the future as the editors feel that the field of EdTech is saturated with high quality publications.
Description: The Australasian Journal of Educational Technology aims to promote research and scholarship on the integration of technology in tertiary education, promote effective practice, and inform policy. The goal is to advance understanding of educational technology in post-school education settings, including higher and further education, lifelong learning, and training.
DESCRIPTION: The Internet and Higher Education is devoted to addressing contemporary issues and future developments related to online learning, teaching, and administration on the Internet in post-secondary settings. Articles should significantly address innovative deployments of Internet technology in instruction and report on research to demonstrate the effects of information technology on instruction in various contexts in higher education.
Publisher / Organization: British Educational Research Association (BERA)
YEAR FOUNDED: 1970
DESCRIPTION: The journal publishes theoretical perspectives, methodological developments and empirical research that demonstrate whether and how applications of instructional/educational technology systems, networks, tools and resources lead to improvements in formal and non-formal education at all levels, from early years through to higher, technical and vocational education, professional development and corporate training.
Description: Computers & Education aims to increase knowledge and understanding of ways in which digital technology can enhance education, through the publication of high quality research, which extends theory and practice.
Description: TechTrends targets professionals in the educational communication and technology field. It provides a vehicle that fosters the exchange of important and current information among professional practitioners. Among the topics addressed are the management of media and programs, the application of educational technology principles and techniques to instructional programs, and corporate and military training.
Description: Advances in technology and the growth of e-learning to provide educators and trainers with unique opportunities to enhance learning and teaching in corporate, government, healthcare, and higher education. IJEL serves as a forum to facilitate the international exchange of information on the current research, development, and practice of e-learning in these sectors.
Led by an Editorial Review Board of leaders in the field of e-Learning, the Journal is designed for the following audiences: researchers, developers, and practitioners in corporate, government, healthcare, and higher education. IJEL is a peer-reviewed journal.
Description: JCMST is a highly respected scholarly journal which offers an in-depth forum for the interchange of information in the fields of science, mathematics, and computer science. JCMST is the only periodical devoted specifically to using information technology in the teaching of mathematics and science.
Just as researchers build reputation over time that can be depicted (in part) through quantitative measures such as h-index and i10-index, journals are also compared based on the number of citations they receive..
Description: The Journal of Interactive Learning Research (JILR) publishes papers related to the underlying theory, design, implementation, effectiveness, and impact on education and training of the following interactive learning environments: authoring systems, cognitive tools for learning computer-assisted language learning computer-based assessment systems, computer-based training computer-mediated communications, computer-supported collaborative learning distributed learning environments, electronic performance support systems interactive learning environments, interactive multimedia systems interactive simulations and games, intelligent agents on the Internet intelligent tutoring systems, microworlds, virtual reality based learning systems.
Description: JEMH is designed to provide a multi-disciplinary forum to present and discuss research, development and applications of multimedia and hypermedia in education. It contributes to the advancement of the theory and practice of learning and teaching in environments that integrate images, sound, text, and data.
Publisher / Organization: Society for Information Technology and Teacher Education (SITE)
Year founded: 1997
Description: JTATE serves as a forum for the exchange of knowledge about the use of information technology in teacher education. Journal content covers preservice and inservice teacher education, graduate programs in areas such as curriculum and instruction, educational administration, staff development instructional technology, and educational computing.
Publisher / Organization: Association for the Advancement of Computing in Education (AACE)
YEAR FOUNDED: 2015
DESCRIPTION: The Journal of Online Learning Research (JOLR) is a peer-reviewed, international journal devoted to the theoretical, empirical, and pragmatic understanding of technologies and their impact on primary and secondary pedagogy and policy in primary and secondary (K-12) online and blended environments. JOLR is focused on publishing manuscripts that address online learning, catering particularly to the educators who research, practice, design, and/or administer in primary and secondary schooling in online settings. However, the journal also serves those educators who have chosen to blend online learning tools and strategies in their face-to-face classroom.
The most commonly used index to measure the relative importance of journals is the annual Journal Citation Reports (JCR). This report is published by Clarivate Analytics (previously Thomson Reuters).
SCImago Journal Rank (SJR indicator) measures the influence of journals based on the number of citations the articles in the journal receive and the importance or prestige of the journals where such citations come from. The SJR indicator is a free journal metric which uses an algorithm similar to PageRank and provides an open access alternative to the journal impact factor in the Web of Science Journal Citation Report. The portal draws from the information contained in the Scopus database (Elsevier B.V.).
Introduced by Google in 2004, Scholar is a freely accessible search engine that indexes the full text or metadata of scholarly publications across an array of publishing formats and disciplines.
Introduced by Elsevier in 2004, Scopus is an abstract and citation database that covers nearly 18,000 titles from more than 5,000 publishers. It offers journal metrics that go beyond just journals to include most serial titles, including supplements, special issues and conference proceedings. Scopus offers useful information such as the total number of citations, the total number of articles published, and the percent of articles cited.
Anne-Wil Harzing:
“Citations are not just a reflection of the impact that a particular piece of academic work has generated. Citations can be used to tell stories about academics, journals and fields of research, but they can also be used to distort stories”.
Harzing, A.-W. (2013). The publish or perish book: Your guide to effective and responsible citation analysis. http://harzing.com/popbook/index.htm
ResearchGate is a social networking site for scientists and researchers to share papers, ask and answer questions, and find collaborators. The community was founded in May 2008. Today it has over 14 million members.
Google Scholar allows users to search for digital or physical copies of articles, whether online or in libraries. It indexes “full-text journal articles, technical reports, preprints, theses, books, and other documents, including selected Web pages that are deemed to be ‘scholarly. It comprises an estimated 160 million documents.
Academia.edu is a social-networking platform for academics to share research papers. You can upload your own work, and follow the updates of your peers. Founded in 2008, the network currently has 59 million users, and adding 20 million documents.
The ORCHID (Open Researcher and Contributor ID) is a nonproprietary alphanumeric code to uniquely identify scientific and other academic authors and contributors. It provides a persistent identity for humans, similar to content-related entities on digital networks that utilize digital object identifiers (DOIs). The organization offers an open and independent registry intended to be the de facto standard for contributor identification in research and academic publishing.
The Scopus Author Identifier assigns a unique number to groups of documents written by the same author via an algorithm that matches authorship based on a certain criteria. If a document cannot be confidently matched with an author identifier, it is grouped separately. In this case, you may see more than one entry for the same author.
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more on metrics in this iMS blog
Over the past 10 years, new learning management systems (LMSs) have sprung on the scene to rival the Blackboards and Moodles of old. On the EdSurge Product Index alone, 56 products self-identify and fall into the LMS category. And with certain established companies like Pearson pulling out of the LMS ranks, where do you start?
As University of Central Florida’s Associate Vice President of Distributed Learning, Tom Cavanagh, wrote in an article for EDUCAUSE, “every institute has a unique set of instructional and infrastructure circumstances to consider when deciding on an LMS,” but at the same time, “all institutions face certain common requirements”—whether a small charter school, a private university or a large public school district.
The LMS Checklist
#1: Is the platform straightforward and user-friendly?
#2: Who do we want to have access to this platform, and can we adjust what they can see?
#3: Can the instructor and student(s) talk to and communicate with each other easily?
“Students and faculty live a significant portion of their daily lives online in social media spaces,” writes University of Central Florida’s Tom Cavanagh in his article on the LMS selection process. “Are your students and faculty interested in these sorts of interplatform connections?”
#5: Does this platform plug in with all of the other platforms we have?
“Given the pace of change and the plethora of options with educational technology, it’s very difficult for any LMS vendor to keep up with stand-alone tools that will always outperform built-in tools,” explains Michael Truong, executive director of innovative teaching and technology at Azusa Pacific University. According to Truong, “no LMS will be able to compete directly with tools like Piazza (discussion forum), Socrative (quizzing), EdPuzzle (video annotation), etc.”
As a result, Truong says, “The best way to ‘prepare’ for future technological changes is to go with an LMS that plays well with external tools.”
2018 Special Focus: Education in a Time of Austerity and Social Turbulence 21–23 June 2018 University of Athens, Athens, Greece http://thelearner.com/2018-conference
Theme 8: Technologies in Learning
Technology and human values: learning through and about technology
Crossing the digital divide: access to learning in, and about, the digital world
New tools for learning: online digitally mediated learning
Virtual worlds, virtual classrooms: interactive, self-paced and autonomous learning
Ubiquitous learning: using the affordances of the new mediaDistance learning: reducing the distance
Theme 9: Literacies Learning
Defining new literacies
Languages of power: literacy’s role in social access
Instructional responses to individual differences in literacy learning
The visual and the verbal: Multiliteracies and multimodal communications
Literacy in learning: language in learning across the subject areas
The changing role of libraries in literacies learning
Languages education and second language learning
Multilingual learning for a multicultural world
The arts and design in multimodal learning
The computer, internet, and digital media: educational challenges and responses
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PROPOSAL: Paper presentation in a Themed Session
Title
Virtual Reality and Gamification in the Educational Process: The Experience from an Academic Library
short description
VR, AR and Mixed Reality, as well as gaming and gamification are proposed as sandbox opportunity to transition from a lecture-type instruction to constructivist-based methods.
long description
The NMC New Horizon Report 2017 predicts a rapid application of Video360 in K12. Millennials are leaving college, Gen Z students are our next patrons. Higher Education needs to meet its new students on “their playground.” A collaboration by a librarian and VR specialist is testing the opportunities to apply 360 degree movies and VR in academic library orientation. The team seeks to bank on the inheriting interest of young patrons toward these technologies and their inextricable part of a rapidly becoming traditional gaming environment. A “low-end,” inexpensive and more mobile Google Cardboard solution was preferred to HTC Vive, Microsoft HoloLens or comparable hi-end VR, AR and mixed reality products.
The team relies on the constructivist theory of assisting students in building their knowledge in their own pace and on their own terms, rather than being lectured and/or being guided by a librarian during a traditional library orientation tour. Using inexpensive Google Cardboard goggles, students can explore a realistic set up of the actual library and familiarize themselves with its services. Students were polled on the effectiveness of such approach as well as on their inclination to entertain more comprehensive version of library orientation. Based on the lessons from this experiment, the team intends to pursue also a standardized approach to introducing VR to other campus services, thus bringing down further the cost of VR projects on campus. The project is considered a sandbox for academic instruction across campus. The same concept can be applied for [e.g., Chemistry, Physics, Biology) lab tours; for classes, which anticipate preliminary orientation process.
Following the VR orientation, the traditional students’ library instruction, usually conducted in a room, is replaced by a dynamic gamified library instruction. Students are split in groups of three and conduct a “scavenger hunt”; students use a jQuery-generated Web site on their mobile devices to advance through “hoops” of standard information literacy test. E.g., they need to walk to the Reference Desk, collect specific information and log their findings in the Web site. The idea follows the strong interest in the educational world toward gaming and gamification of the educational process. This library orientation approach applies the three principles for gamification: empowers learners; teaches problem solving and increases understanding.
Similarly to the experience with VR for library orientation, this library instruction process is used as a sandbox and has been successfully replicated by other instructors in their classes.
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
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Librarians in universities, colleges, and community colleges can establish, assess, and link
academic library outcomes to institutional outcomes related to the following areas:
student enrollment, student retention and graduation rates, student success, student
achievement, student learning, student engagement, faculty research productivity,
faculty teaching, service, and overarching institutional quality.
Assessment management systems help higher education educators, including librarians, manage their outcomes, record and maintain data on each outcome, facilitate connections to
similar outcomes throughout an institution, and generate reports.
Assessment management systems are helpful for documenting progress toward
strategic/organizational goals, but their real strength lies in managing learning
outcomes assessments.
to determine the impact of library interactions on users, libraries can collect data on how individual users engage with library resources and services.
increase library impact on student enrollment.
p. 13-14improved student retention and graduation rates. High -impact practices include: first -year seminars and experiences, common intellectual experiences, learning communities, writing – intensive courses, collaborative assignments and projects, undergraduate research, Value of Academic Libraries diversity/global learning, service learning/community -based learning, internships, capstone courses and projects
p. 14
Libraries support students’ ability to do well in internships, secure job placements, earn salaries, gain acceptance to graduate/professional schools, and obtain marketable skills.
librarians can investigate correlations between student library interactions and their GPA well as conduct test item audits of major professional/educational tests to determine correlations between library services or resources and specific test items.
p. 15 Review course content, readings, reserves, and assignments.
Track and increase library contributions to faculty research productivity.
Continue to investigate library impact on faculty grant proposals and funding, a means of generating institutional income. Librarians contribute to faculty grant proposals in a number of ways.
Demonstrate and improve library support of faculty teaching.
p. 20 Internal Focus: ROI – lib value = perceived benefits / perceived costs
production of a commodity – value=quantity of commodity produced × price per unit of commodity
p. 21 External focus
a fourth definition of value focuses on library impact on users. It asks, “What is the library trying to achieve? How can librarians tell if they have made a difference?” In universities, colleges, and community colleges, libraries impact learning, teaching, research, and service. A main method for measuring impact is to “observe what the [users] are actually doing and what they are producing as a result”
A fifth definition of value is based on user perceptions of the library in relation to competing alternatives. A related definition is “desired value” or “what a [user] wants to have happen when interacting with a [library] and/or using a [library’s] product or service” (Flint, Woodruff and Fisher Gardial 2002) . Both “impact” and “competing alternatives” approaches to value require libraries to gain new understanding of their users’ goals as well as the results of their interactions with academic libraries.
p. 23 Increasingly, academic library value is linked to service, rather than products. Because information products are generally produced outside of libraries, library value is increasingly invested in service aspects and librarian expertise.
service delivery supported by librarian expertise is an important library value.
p. 25 methodology based only on literature? weak!
p. 26 review and analysis of the literature: language and literature are old (e.g. educational administrators vs ed leaders).
G government often sees higher education as unresponsive to these economic demands. Other stakeholder groups —students, pa rents, communities, employers, and graduate/professional schools —expect higher education to make impacts in ways that are not primarily financial.
p. 29
Because institutional missions vary (Keeling, et al. 2008, 86; Fraser, McClure and
Leahy 2002, 512), the methods by which academic libraries contribute value vary as
well. Consequently, each academic library must determine the unique ways in which they contribute to the mission of their institution and use that information to guide planning and decision making (Hernon and Altman, Assessing Service Quality 1998, 31) . For example, the University of Minnesota Libraries has rewritten their mission and vision to increase alignment with their overarching institution’s goals and emphasis on strategic engagement (Lougee 2009, allow institutional missions to guide library assessment
Assessment vs. Research
In community colleges, colleges, and universities, assessment is about defining the
purpose of higher education and determining the nature of quality (Astin 1987)
.
Academic libraries serve a number of purposes, often to the point of being
overextended.
Assessment “strives to know…what is” and then uses that information to change the
status quo (Keeling, et al. 2008, 28); in contrast, research is designed to test
hypotheses. Assessment focuses on observations of change; research is concerned with the degree of correlation or causation among variables (Keeling, et al. 2008, 35) . Assessment “virtually always occurs in a political context ,” while research attempts to be apolitical” (Upcraft and Schuh 2002, 19) .
p. 31 Assessment seeks to document observations, but research seeks to prove or disprove ideas. Assessors have to complete assessment projects, even when there are significant design flaws (e.g., resource limitations, time limitations, organizational contexts, design limitations, or political contexts); whereas researchers can start over (Upcraft and Schuh 2002, 19) . Assessors cannot always attain “perfect” studies, but must make do with “good enough” (Upcraft and Schuh 2002, 18) . Of course, assessments should be well planned, be based on clear outcomes (Gorman 2009, 9- 10) , and use appropriate methods (Keeling, et al. 2008, 39) ; but they “must be comfortable with saying ‘after’ as well as ‘as a result of’…experiences” (Ke eling, et al. 2008, 35) .
Two multiple measure approaches are most significant for library assessment: 1) triangulation “where multiple methods are used to find areas of convergence of data from different methods with an aim of overcoming the biases or limitations of data gathered from any one particular method” (Keeling, et al. 2008, 53) and 2) complementary mixed methods , which “seek to use data from multiple methods to build upon each other by clarifying, enhancing, or illuminating findings between or among methods” (Keeling, et al. 2008, 53) .
p. 34 Academic libraries can help higher education institutions retain and graduate students, a keystone part of institutional missions (Mezick 2007, 561) , but the challenge lies in determining how libraries can contribute and then document their contribution
p. 35. Student Engagement: In recent years, academic libraries have been transformed to provide “technology and content ubiquity” as well as individualized support My Note: I read the “technology and content ubiquity” as digital literacy / metaliteracies, where basic technology instructional sessions (everything that IMS offers for years) is included, but this library still clenches to information literacy only.
In the past, academic libraries functioned primarily as information repositories; now they are becoming learning enterprises (Bennett 2009, 194) . This shift requires academic librarians to embed library services and resources in the teaching and learning activities of their institutions (Lewis 2007) . In the new paradigm, librarians focus on information skills, not information access (Bundy 2004, 3); they think like educators, not service providers (Bennett 2009, 194) .
p. 38. For librarians, the main content area of student learning is information literacy; however, they are not alone in their interest in student inform ation literacy skills (Oakleaf, Are They Learning? 2011). My note: Yep. it was. 20 years ago. Metaliteracies is now.
p. 41 surrogates for student learning in Table 3.
p. 42 strategic planning for learning:
According to Kantor, the university library “exists to benefit the students of the educational institution as individuals ” (Library as an Information Utility 1976 , 101) . In contrast, academic libraries tend to assess learning outcomes using groups of students
p. 45 Assessment Management Systems
Tk20
Each assessment management system has a slightly different set of capabilities. Some guide outcomes creation, some develop rubrics, some score student work, or support student portfolios. All manage, maintain, and report assessment data
p. 46 faculty teaching
However, as online collections grow and discovery tools evolve, that role has become less critical (Schonfeld and Housewright 2010; Housewright and Schonfeld, Ithaka’s 2006 Studies of Key Stakeholders 2008, 256) . Now, libraries serve as research consultants, project managers, technical support professionals, purchasers , and archivists (Housewright, Themes of Change 2009, 256; Case 2008) .
Librarians can count citations of faculty publications (Dominguez 2005)
.
+++++++++++++
Tenopir, C. (2012). Beyond usage: measuring library outcomes and value. Library Management, 33(1/2), 5-13.
methods that can be used to measure the value of library products and services. (Oakleaf, 2010; Tenopir and King, 2007): three main categories
Implicit value. Measuring usage through downloads or usage logs provide an implicit measure of value. It is assumed that because libraries are used, they are of value to the users. Usage of e-resources is relatively easy to measure on an ongoing basis and is especially useful in collection development decisions and comparison of specific journal titles or use across subject disciplines.
do not show purpose, satisfaction, or outcomes of use (or whether what is downloaded is actually read).
Explicit methods of measuring value include qualitative interview techniques that ask faculty members, students, or others specifically about the value or outcomes attributed to their use of the library collections or services and surveys or interviews that focus on a specific (critical) incident of use.
Derived values, such as Return on Investment (ROI), use multiple types of data collected on both the returns (benefits) and the library and user costs (investment) to explain value in monetary terms.
The New Media Consortium (NMC) has released Digital Literacy in Higher Education, Part II: An NMC Horizon Project Strategic Brief, a follow-up to its 2016 strategic brief on digital literacy.
But what does it really mean to be digitally literate, and which standards do we use?” said Dr. Eden Dahlstrom, NMC Executive Director. “This report sheds light on the meaning and impact of digital literacy using cross-cultural and multi-disciplinary approaches, highlighting frameworks and exemplars in practice.
NMC’s report has identified a need for institutions and thought leaders to consider the ways in which content creation is unequally expressed throughout the world. In an examination of digital literacy within European, Middle Eastern, and African nations (EMEA), research has surfaced unequal access to information technology based on inequalities of economics, gender, race, and political divides.
2020
2015
1.
Complex Problem Solving
1.
Complex Problem Solving
2.
Critical Thinking
2.
Coordinating with Others
3.
Creativity
3.
People Management
4.
People Management
4.
Critical Thinking
5.
Coordinating with Others
5.
Negotiation
6.
Emotional Intelligence
6.
Quality Control
7.
Judgment and Decision Making
7.
Service Orientation
8.
Service Orientation
8.
Judgment and Decision Making
9.
Negotiation
9.
Active Listening
10.
Cognitive Flexibility
10.
Creativity
Digital tools themselves are merely enablers, pushing the envelope of what learners can create. No longer is it acceptable for students to be passive consumers of content; they can contribute to the local and global knowledge ecosystem, learning through the act of producing and discussing rich media, applications, and objects. In the words of many institutional mission statements, students do not have to wait until they graduate to change the world.
Using readily available digital content creation tools (e.g., video production and editing, web and graphic tools), students are evolving into digital storytellers,
digital literacy now encompasses the important skills of being able to coordinate with others to create something truly original that neither mind would fathom independently.
The ability to discern credible from inaccurate resources is foundational to digital literacy. my note: #Fakenews
A lack of broad consensus on the meaning of digital literacy still hinders its uptake, although a growing body of research is helping higher education professionals better navigate the continuous adjustments to the field brought about by emerging pedagogies and technologies.
Information literacy is a nearly universal component within these digital literacy frameworks. Critically finding, assessing, and using digital content within the vast and sometimes chaotic internet appears as a vital skill in almost every account, including those published beyond libraries. In contrast, media literacy is less widely included in digital literacy publications, possibly due to a focus on scholarly, rather than popular, materials. Digital literacies ultimately combine information and media literacy.
United States digital literacy frameworks tend to focus on educational policy details and personal empowerment, the latter encouraging learners to become more effective students, better creators, smarter information consumers, and more influential members of their community.
National policies are vitally important in European digital literacy work, unsurprising for a continent well populated with nation-states and struggling to redefine itself… this recommendation for Balkan digital strategy: “Media and information education (with an emphasis on critical thinking and switching from consumption to action) should start at early ages, but address all ages.”
African digital literacy is more business-oriented. Frameworks often speak to job skills and digital entrepreneurship. New skills and professions are emphasized, symbolized by the call for “new collar” positions.
Middle Eastern nations offer yet another variation, with a strong focus on media literacy. As with other regions, this can be a response to countries with strong state influence or control over local media. It can also represent a drive to produce more locally-sourced content, as opposed to consuming
Digital literacy is a complex phenomenon in 2017, when considered internationally. Nations and regions are creating ways to help their populations grapple with the digital revolution that are shaped by their local situations. In doing so, they cut across the genealogy of digital literacies, touching on its historical components: information literacy, digital skills, and media literacy.
Students are not all digital natives, and do not necessarily have the same level of capabilities. Some need to be taught to use online tools (such as how to navigate a LMS) for learning. However, once digital literacy skills for staff and students are explicitly recognized as important for learning and teaching, critical drivers for pedagogical change are in place.
Pedagogy that uses an inquiry based/problem solving approach is a great framework to enhance the use and practice of digital skills/capabilities in the classroom.
The current gap between students’ information literacy skills and their need to internalize digital literacy competencies creates an opportunity for academic librarians to support students in the pursuit of civic online reasoning at the core of NMC’s multimodal model of three digital literacies. Academic librarians need a new strategy that evolves information literacy to an expanded role educating digitally literate students. Let’s build a new model in which academic librarians are entrepreneurial collaborators with faculty,55 supporting their classroom efforts to help students become responsible sharers and commentators of news on social media.
“Digital literacy is not just about ensuring that students can use the latest technologies, but also developing skills to select the right tools for a particular context to deepen their learning outcomes and engage in creative problem-solving”
There is a disconnect between how students experience and interact with technology in their personal lives and how they use technology in their roles as students. Yes, students are digitally savvy, and yes, universities have a role in questioning (insightfully of course) their sometimes brash digital savviness. We have a situation where students are expecting more, but (as I see it) cannot provide a clear demand, while faculty are unable to walk in the shoes of the students.
From attending class to talking with peers and professors, and from going to the local bookstore to having everything on a laptop in a dorm room, students on campus typically have a more “organic” learning experience than an online student who may not know how to best access these features of a higher education in an entirely mobile setting.
The essentials for getting started
Computer terms (Android) (Apple): Online learning means you’ll need to know basic computer technology terms. Both apps are free and break down terms ranging from words like “cache” to “hex code,” all in layman’s language.
Mint (Android) (Apple): Online learning students are usually financially savvy, looking for less expensive alternatives to traditional four-year tuition. This app allows students to keep careful track of personal finances and spending.
Study Tracker (Android) (Apple): These paid apps help track the time spent on courses, tasks and projects to help online students better manage their time and be able to visualize unique study patterns with the aim of ultimately improving efficiency.
Wi-Fi Finder (Android) (Apple): It’s a no-brainer: If you’re learning online and on-the-go, you’ll probably need to find a connection!
To access actual courses (LMS)
Blackboard Mobile (Android) (Apple): Access all courses that are integrated with Blackboard’s LMS.
Canvas (Android) (Apple). Access all courses integrated with Canvas by Instructure.
Moodle (Android) (Apple): Access all courses integrated with this open-source learning platform.
My note: No D2L in this list, folks; choose carefully in 2018, when MnSCU renews its D2L license
For access to files and remote annotation
Documents to Go (Android) (Apple): Students can access the full Microsoft Office suite, as well as edit and create new files without requiring a cloud app for syncing.
Dropbox (Android) (Apple): This app allows students to access any-size files from their computer anytime, anywhere. My Note: Google Drive, SCSU File space as alternatives.
iAnnotate (Android) (Apple): Read, edit and share PDFs, DOCs, PPTs, and image files.
Instapaper (Android) (Apple): Recall websites for research purposes; strip away clutter for an optimized view of content; and read anywhere, since no internet connection is needed.
Marvin (Apple): A completely customizable eBook reader that includes DRM-free books, customizable formats, layouts, and reading gestures, as well as highlighting and annotations tools. Considered one of the best replacements for the Stanza app, which is now discontinued.
Pocket (Android): An app that allows students to save websites, blog posts, videos, and other online resources to access at a later time. It also saves the information to the device, meaning no internet connection is needed.
Wolfram Alpha (Android) (Apple): Considered the scholar’s version of Google, this app is a search engine that reveals precise information for natural-language searches. For example, if you ask “What is the graduation rate for Harvard?” the engine will bring up exact numbers with citations and suggestions for similar queries.
For online communication with peers and profs
Dragon Dictation (Android) (Apple): Create text messages, social media posts, blog posts and more by using your voice (speech-to-text). According to the company, Dragon Dictation is up to five times faster than typing on the keyboard.
Evernote (Android) (Apple): Whenever you look at a list of education apps, Evernote is usually listed. This app allows students to scribble notes, capture text, send notes to computers and other users, and much more for ultimate multi-media communication.
Hangouts (Android) (Apple): Google’s social network shines for its own online video chat solution, which lets teachers, students and third-party experts easily videoconference in groups—it’s even been used to broadcast presenters live to packed auditoriums. My note: desktopsharing is THE most important part. Alternatives: SCSU subscription for Adobe Connect. Skype also has desktopsharing capabilities
Quora (Android) (Apple): Ask questions to experts including astronauts, police officers, lawyers, and much more to receive industry-insider responses.
Smartsheet (Android) (Apple): An app that allows students to create task lists and assign deadlines to share with remote group/team members.
Tom’s planner (Web): A Gantt chart-based, online planning tool that uses color-coded charts to reveal work completed and many more features for project management.
The finding is good news for colleges and universities focused on digital transformation — whether that means implementing new classroom technologies, transitioning services to the cloud or building out the back-end infrastructure needed to support students’ increasing bandwidth demands.
Children who use smartphones, tablets, and video games for more than seven hours a day are more likely to experience premature thinning of the cortex, the outermost layer of the brain that processes thought and action, a 2018 study found. https://t.co/OJe6ZTBVkx
But others say banning laptops can be counterproductive, arguing these devices can create opportunity for students to discover more information during class or collaborate. And that certain tools and technologies are necessary for learners who struggle in a traditional lecture format.
Flanigan, who studies self-regulation, or the processes students use to achieve their learning goals, began researching digital distraction after confronting it in the classroom as a graduate instructor.
Digital distraction tempts all of us, almost everywhere. That’s the premise of Digital Minimalism: Choosing a Focused Life in a Noisy World by Cal Newport, an associate professor of computer science at Georgetown University.
The professor is upset. The professor has taken action, by banning laptops.
Bruff, whose next book, Intentional Tech: Principles to Guide the Use of Educational Technology in College Teaching, is set to be published this fall, is among the experts who think that’s a mistake. Why? Well, for one thing, he said, students are “going to have to graduate and get jobs and use laptops without being on Facebook all day.” The classroom should help prepare them for that.
When Volk teaches a course with 50 or 60 students, he said, “the idea is to keep them moving.”Shifting the focal point away from the professor can help, too. “If they are in a small group with their colleagues,” Volk said, “very rarely will I see them on their laptops doing things they shouldn’t be.”
Professors may not see themselves as performers, but if they can’t get students’ attention, nothing else they do matters. “Learning doesn’t happen without attention,” said Lang, who is writing a book about digital distraction, Teaching Distracted Minds.
One aspect of distraction Lang plans to cover in his book is its history. It’s possible, he said, to regard our smartphones as either too similar or dissimilar from the distractions of the past. And it’s important, he said, to remember how new this technology really is, and how much we still don’t know about it.
++++++++++
Study: Use of digital devices in class affects students’ long-term retention of information
A new study conducted by researchers at Rutgers University reveals that students who are distracted by texts, games, or videos while taking lecture notes on digital devices are far more likely to have their long-term memory affected and to perform more poorly on exams, even if short-term memory is not impacted, EdSurge reports.
Exam performance was not only poorer for students using the devices, but also for other students in classes that permitted the devices because of the distraction factor, the study found.
After conducting the study, Arnold Glass, the lead researcher, changed his own policy and no longer allows his students to take notes on digital devices.
A nationally representative Gallup poll conducted in March showed that 42% of K-12 teachers feel that the use of digital devices in the classroom are “mostly helpful” for students, while only 28% feel they are “mostly harmful.” Yet 69% of those same teachers feel the devices have a harmful impact on student mental health and 55% feel they negatively affect student physical health.
According to a 2016 study of college students, student waste about 20% of their class time for “non-class” purposes — texting, emailing, or using social media more than 11 times in a typical day. In K-12, increased dependence on digital devices often interferes with homework completion as well.
Though the new study focused on long-term retention, past studies have also shown that indicate a negative correlation between use of digital devices during class and exam scores. A 2015 study by the London School of Economics revealed that pupils in schools that banned cell phones performed better on exams and that the differences were most notable for low-performing students.
Using laptops in class harms academic performance, study warns. Researchers say students who use computers score half a grade lower than those who write notes
findings, published in the journal Economics of Education Review in a paper, based on an analysis of the grades of about 5,600 students at a private US liberal arts college, found that using a laptop appeared to harm the grades of male and low-performing students most significantly.
While the authors were unable to definitively say why laptop use caused a “significant negative effect in grades”, the authors believe that classroom “cyber-slacking” plays a major role in lower achievement, with wi-fi-enabled computers providing numerous distractions for students.
High schoolers assigned a laptop or a Chromebook were more likely to take notes in class, do internet research, create documents to share, collaborate with their peers on projects, check their grades and get reminders about tests or homework due dates.
Blended Learning – the idea of incorporating technology into the every day experience of education – can save time, raise engagement, and increase student retention.
Lets face it, our students are addicted to their phones. Like…drugs addicted. It is not just a bad habit, it is hard wired in their brains(literally) to have the constant stimulation of their phones.
If you are interested in the research, there is a lot out there to read about how it happens and how bad it is.
a Scientific American article published about a recent study of nomophobia – on adults (yes, many of us are addicted too).
how data is produced, collected and analyzed. make accessible all kind of data and info
ask good q/s and find good answers, share finding in meaningful ways. this is where digital literacy overshadows information literacy and this the fact that SCSU library does not understand; besides teaching students how to find and evaluate data, I also teach them how to communicate effectively using electronic tools.
connecting people tools and resources and making it easier for everybody. building collaborative, open and interdisciplinary
robust data computational literates. developing workshops, project and events to practice new skills. to position the library as the interdisciplinary nexus
what are data: definition. items of information, facts, traces of content and form. higher level, conception discussion about data in terms of social effects: matadata capturing information about the world, social political and economic changes. move away the mystic conceptions about data. nothing objective about data.
the emergence of IoT – digital meets physical. cyber physical systems. smart objects driven by industry. . proliferation of sensor and device – smart devices.
what does privacy looks like ? what is netneutrality when IoT? library must restructure : collaborate across institutions about collections of data in opien and participatory ways. put IoT in the hands of make and break things (she is maker space aficionado)
make and break things hackathons – use cheap devices such as Arduino and Pi.
data literacy programs with higher level conception exploration; libraries empower the campus in data collection. data science norms, store and share data to existing repositories and even catalogs. commercial services to store and connect data, but very restrictive and this is why libraries must be involved.
linked data and dark data
linked data – draw connections around online data most of the data are locked. linked data uses metadata to link related information in ways computers can understand.
libraries take advantage of link data. link data opportunity for semantics, natural language processing etc. if hidden data is relative to our communities, it is a library responsibility to provide it. community data practitioners
dark data
massive data, which cannot be analyzed by relational processing. data not yield significant findings. might be valuable for researchers: one persons trash is another persons’ treasure. preserving data and providing access to info. collaborate with researchers across disciplines and assist decide what is worth keeping and what discarding and how to study.
rich learning experience working with lined and dark data enable fresh perspective and learning how to work with data architecture. data literacy programming.
in context of data is different from open source and open projects. the social side of data science . advising researchers on navigation data, ethical compilations.
open science movement .https://cos.io/ pushing beyond licences and reframe, position ourselves as collaborators
analysis and publishing ; use tools that can be shared and include data, code and executable files.
reproducibility and contestability https://www.lib.ncsu.edu/events/series/summer-of-open-science
In the age of Big Data, there is an abundance of free or cheap data sources available to libraries about their users’ behavior across the many components that make up their web presence. Data from vendors, data from Google Analytics or other third-party tracking software, and data from user testing are all things libraries have access to at little or no cost. However, just like many students can become overloaded when they do not know how to navigate the many information sources available to them, many libraries can become overloaded by the continuous stream of data pouring in from these sources. This session will aim to help librarians understand 1) what sorts of data their library already has (or easily could have) access to about how their users use their various web tools, 2) what that data can and cannot tell them, and 3) how to use the datasets they are collecting in a holistic manner to help them make design decisions. The presentation will feature examples from the presenters’ own experience of incorporating user data in decisions related to design the Bethel University Libraries’ web presence.
silos, IT barrier, focusing on student success, retention, server space is cheap, if
promotion and tenure for faculty can include incentive to work with the librarian
lack of fear, changing the mindset.
deep collaboration both within and cross-consortia
don’t rely on vendor solutions. changing mindset
development = oppty (versus development as “work”)
private higher education is PALNI
3d virtual picture of disastrous areas. unlock the digital information to be digitally accessible to all people who might be interested.
they opened the maps of Katmandu for the local community and they were coming up with the strategies to recover. democracy in action
i can’t stop thinking that the keynote speaker efforts are mere follow up of what Naomi Klein explains in her Shock Doctrine: http://www.naomiklein.org/shock-doctrine: a government country seeks reasons to destroy another country or area and then NGOs from the same country go to remedy the disasters
A question from a librarian from the U about the use of drones. My note: why did the SCSU library have to give up its drone?
Douglas County Library model. too resource intensive to continue
Marmot Library Network
ILS integrated library system – shared with other counties, same sever for the entire consortium. they have a programmer, viewfind, open source, discovery player, he customized viewfind community to viewfind plus. instead of using the ILS public access catalogue, they are using the Vufind interface
Caiifa Enki. public library – single access collection. they purchase ebooks from the publisher and they are using also the viewfind interface. but not integrated with the library catalogs. Kansas public library went from OverDrive to Viewfind. CA State library is funding for the time being this effort.
types of content – publisher will not understand issue, which clear for librarians
PDF and epub formats
purchase content –
title by title selection – academia is tired of selections. although it is intended to buy also collections
library – owned ( and shared collections)
host content from libraries – papers in academic lib, genealogy in pub lib.
options in license models .
e resource content. not only ebooks, after it is taken care of, add other types of digital objects.
instead of replicate, replacement of the commercial aggregators,
Amigos Shelf interface is the product of the presenter
instead of having a young reader collection as SCSU has on the third floor, an academic library is outsourcing through AMigos shelf ebooks for young readers
Harper Collins is too cumbersome and the reason to avoid working with them.
security issues. some of the material sent over ftp and immediately moved to sftp
decisions – use of internal resources only, if now – amazon
programmer used for the pilot. contracted programmers. lack of the ability to see the large picture. eventually hired a full time person, instead of outsourcing. RDA compliant MARC.
ONIX, spreadsheet MARC.
Decision about who to start with : public or academic.
attempt to keep pricing down –
own agreement with the customers, separate from the agreement with the Publisher
current development: web-based online reading, shared-consortial collections and SIP2 authentication
