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Embedded Librarian and Gamification in Libraries

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Open Discussion: Embedded Librarian and Gamification in Libraries

by invitation of New Bulgarian University, Sofia, Bulgaria: https://www.nbu.bg/en
May 14, 9-11AM, New Bulgarian University.

short link: http://bit.ly/embed18

Live stream: https://www.facebook.com/InforMediaServices/ and recording available (предаване на живо и запис)

 

 qr code NBU

 

 

 

Live stream:
https://www.facebook.com/InforMediaServices/
and recording available
(предаване на живо и запис)

backchanneling: @scsutechinstruct ##NBUembed

Archived Discussion
https://www.facebook.com/InforMediaServices/videos/1532459913531167/

Video 360 excerpt from the discussion:

Семинар „Embedded“ библиотекари и геймификация в библиотеките:
Съвременни американски практики“, 14 май 2018 г., 9.00 ч.-11.00 ч.,

Embedded Librarian and Gamification in Libraries from Plamen Miltenoff

Preliminary Information and Literature. Please do not hesitate to share in the comments section your ideas, suggestions and questions
предварителна информация и литература по дискусията. Не се колебайте да споделите мнения, препоръки и въпроси в “Comment” секцията:

https://blog.stcloudstate.edu/ims/2017/10/03/embedded-librarianship-in-online-courses/

https://blog.stcloudstate.edu/ims/2017/08/24/embedded-librarian-qualifications/

https://blog.stcloudstate.edu/ims/2015/05/04/lms-and-embedded-librarianship/

“Embedded librarianship” also mentioned in:

https://blog.stcloudstate.edu/ims/2015/05/27/handbook-of-mobile-learning/

https://blog.stcloudstate.edu/ims/2016/08/18/digital-humanities-and-libraries/

Gaming and Gamification and Education:

https://blog.stcloudstate.edu/ims/2018/04/18/engage-with-dungeons-and-dragons/

https://blog.stcloudstate.edu/ims?s=iste+standards

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For more information and for backchanneling please use the following social media
за повече въпроси и информация, както и за споделяне на вашите идеи и мисли използвайте следните канали / социални медии:

Facebook:

Twitter:

https://twitter.com/SCSUtechinstruc/status/984437858244145152

LinkedIn discussion on VR/AR
https://www.linkedin.com/groups/2811/2811-6391674579739303939

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even more info

The embedded librarian from doberhelman

The Embedded Librarian: Using Technology in Service Delivery from Pavlinka Kovatcheva

Embedded Librarian-ALA 2011 from Info_Witch

Toward a Sustainable Embedded Librarian Program from Robin M. Ashford, MSLIS

The Embedded Librarian: Integrating Library Resources into Course Management Systems from Emily Daly

Embedded Librarian in Higher Education from Shahril Effendi

Ilago 2016 presentation: Next Steps in Embedded Librarian Instructional Design from Dawn Lowe-Wincentsen





BUT WAIT

how does embedded librarian relates to the emerging technologies in the library?

Emerging Technology Trends in Libraries for 2018 from David King

publish metrics ranking and citation info

EdTech Research – Where to Publish, How to Share (Part 2): Journal Metrics, Rankings and Citation Information

EdTech Research – Where to Publish, How to Share (Part 1): Journal Overview

electronic journals

International Review of Research in Open and Distributed Learning (IRRODL)

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.

First Monday

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.

URL: http://firstmonday.org/

International Journal of Educational Technology in Higher Education(ETHE)

Publisher / Organization: Springer (from 2013)

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.

URL: https://educationaltechnologyjournal.springeropen.com/

Online Learning (formerly JOLT / JALN)

Publisher / Organization: Online Learning Consortium

Year founded: 1997

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).

URL: https://olj.onlinelearningconsortium.org/

Journal of Educational Technology & Society

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.

URL: http://www.ds.unipi.gr/et&s/index.php

Australasian Journal of Educational Technology

Publisher / Organization: Ascilite (Organization) & PKP Publishing Services Network

Year founded: 1985

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.

URL: https://ajet.org.au/index.php/AJET

Print Journals

The Internet and Higher Education

Publisher / Organization: Elsevier Ltd.

YEAR FOUNDED: 1998

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.

URL: https://www.journals.elsevier.com/the-internet-and-higher-education

British Journal of Educational Technology

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.

LINK: http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1467-8535

Computers & Education

Publisher / Organization: Elsevier Ltd.

Year founded: 1976

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.

URL: https://www.journals.elsevier.com/computers-and-education/

Tech Trends

Publisher / Organization: Springer US

Year founded: 1985

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.

URL: https://link.springer.com/journal/11528

International Journal on E-Learning (IJEL)

Year founded: 2002

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.

URL: http://www.aace.org/pubs/ijel/

Journal of Computers in Mathematics and Science Teaching (JCMST)

Year founded: 1981

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.

URL: https://www.aace.org/pubs/jcmst/

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..

Journal of Interactive Learning Research (JILR)

Year founded: 1997

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.

URL: http://learntechlib.org/j/JILR/

Journal of Educational Multimedia and Hypermedia (JEMH)

Year founded: 1996

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.

URL: https://www.aace.org/pubs/jemh/

Journal of Technology and Teacher Education (JTATE)

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.

URL: https://www.aace.org/pubs/jtate/

Journal on Online Learning Research (JOLR)

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.

URL: https://www.aace.org/pubs/jolr/

 

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part 2

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

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.).

Google Scholar Journal Rank

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.

Scopus Journal Metrics

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

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

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

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.

ORCID

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.

SCOPUS

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

https://blog.stcloudstate.edu/ims?s=metrics

Blockchain, Money and Empathy

On Blockchain, Money and Empathy: EdSurge Talks Trends and 2018 Predictions

By Jeffrey R. Young     Jan 30, 2018

EdSurge’s CEO, Betsy Corcoran, argued that 2017 was a year when educators and schools were trying to take control of their technology choices “We have said from the time we started writing the newsletters that not every piece of technology will work for every student, or for every school or every classroom,” she said. “It’s all about asking the right questions to figure out if there is a piece of technology that will support learning goals. What we’re starting to really see across schools, districts and teachers, people really owning those questions. They’re saying, ‘What do I want to do with my classroom? With my kids? And what are the technologies that will support me?’”

Another discussion participant asked whether colleges and universities are starting to accept cryptocurrencies like Bitcoin, or experimenting with the blockchain technology that drives those systems. Johnson said most of the hype around unversities’ blockchain experiments has centered on storing and managing credentials.

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more on blockchain and education in this IMS blog
https://blog.stcloudstate.edu/ims?s=blockchain+education

Principalship EDAD

Link to this blog entry: http://bit.ly/principaledad

Fri, Feb. 2, 2018, Principalship class, 22 people, Plymouth room 103

Instructor Jim Johnson  EDAD principalship class

The many different roles of the principals:

Communication

Effective communication is one critical characteristics of effective and successful school principal. Research on effective schools and instructional leadership emphasizes the impact of principal leadership on creating safe and secure learning environment and positive nurturing school climate (Halawah, 2005, p. 334)

Halawah, I. (2005). The Relationship between Effective Communication of High School Principal and School Climate. Education, 126(2), 334-345.

http://login.libproxy.stcloudstate.edu/login?qurl=http%3a%2f%2fsearch.ebscohost.com%2flogin.aspx%3fdirect%3dtrue%26db%3deric%26AN%3dEJ765683%26site%3dehost-live%26scope%3dsite

Selection of school principals in Hong Kong. The findings confirm a four-factor set of expectations sought from applicants; these are Generic Managerial Skills; Communication and Presentation Skills; Knowledge and Experience; and Religious Value Orientation.

Kwan, P. (2012). Assessing school principal candidates: perspectives of the hiring superintendents. International Journal Of Leadership In Education, 15(3), 331-349. doi:10.1080/13603124.2011.617838

http://login.libproxy.stcloudstate.edu/login?qurl=http%3a%2f%2fsearch.ebscohost.com%2flogin.aspx%3fdirect%3dtrue%26db%3dkeh%26AN%3d77658138%26site%3dehost-live%26scope%3dsite

Yee, D. L. (2000). Images of school principals’ information and communications technology leadership. Journal of Information Technology for Teacher Education, 9(3), 287–302. https://doi.org/10.1080/14759390000200097

Catano, N., & Stronge, J. H. (2007). What do we expect of school principals? Congruence between principal evaluation and performance standards. International Journal of Leadership in Education, 10(4), 379–399. https://doi.org/10.1080/13603120701381782

Communication can consist of two large areas:

  • broadcasting information: PR, promotions, notifications etc.
  • two-way communication: collecting feedback, “office hours” type of communication, backchanneling, etc.

Further communication initiated by/from principals can have different audiences

  • staff: teachers, maintenance etc.

Ärlestig, H. (2008). Communication between principals and teachers in successful schools. DIVA. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-1927

Reyes, P., & Hoyle, D. (1992). Teachers’ Satisfaction With Principals’ Communication. The Journal of Educational Research, 85(3), 163–168. https://doi.org/10.1080/00220671.1992.9944433

  • parents: involvement, feeling of empowerment, support, volunteering
  • students
  • board members
  • community

Epstein, J. L. (1995). School/family/community partnerships – ProQuest. Phi Delta Kappan, 76(9), 701.

  • Others

Communication and Visualization

The ever-growing necessity to be able to communicate data to different audiences in digestible format.

https://blog.stcloudstate.edu/ims/2017/07/15/large-scale-visualization/

So, how do we organize and exercise communication with these audiences and considering the different content to be communicated?

  • How do you use to do it at your school, when you were students 20-30 years ago?
  • How is it different now?
  • How do you think it must be changed?

Communication tools:

physical

  • paper-based memos, physical boards

Electronic

  • phone, Intercom, email, electronic boards (listservs)

21st century electronic tools

  • Electronic boards
    • Pinterest
  • Internet telephony and desktopsharing
    • Adobe Connect, Webex, Zoom, GoToMeeting, Teamviewer etc.
    • Skype, Google Hangouts, Facebook Messenger
  • Electronic calendars
    • Doodle, MS Offce365, Google Calendar
  • Social media / The Cloud
    • Visuals: Flickr, YouTube, TeacherTube, MediaSpace
    • Podasts
    • Direct two-way communication
      • Asynchronous
        • Snapchat
        • Facebook
        • Twitter
        • LinkedIn
        • Instagram
      • Synchronous
        • Chat
        • Audio/video/desktopsharing
      • Management tools

 

Tools:

https://blog.stcloudstate.edu/ims/2016/07/16/communication-tool-for-teachers-and-parents/

Top 10 Social Media Management Tools: beyond Hootsuite and TweetDeck

https://blog.stcloudstate.edu/ims/2013/11/17/top-10-social-media-management-tools-beyond-hootsuite-and-tweetdeck/

Manage control of your passwords and logons (Password Managers)

  • 1Password.
  • Okta.
  • Keeper.
  • KeePass.
  • Centrify Application Services.
  • RoboForm.
  • Zoho Vault.
  • Passpack.
  • LastPass

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class discussion Feb 2.

PeachJar : https://www.peachjar.com/

Seesaw: https://web.seesaw.me/

Schoology: https://www.schoology.com/

 

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Group Assignment

considering the information discussed in class, split in groups of 4 and develop your institution strategy for effective and modern communication across and out of your school.

>>>>>>>>>>> Word of the day: blockchain credentialing <<<<<<<<<<<<<<<<<<<<<

>>>>>>>>>>> K12 Trends 4 2018 <<<<<<<<<<<<<<<<<

 

 

topics for IM260

proposed topics for IM 260 class

  • Media literacy. Differentiated instruction. Media literacy guide.
    Fake news as part of media literacy. Visual literacy as part of media literacy. Media literacy as part of digital citizenship.
  • Web design / web development
    the roles of HTML5, CSS, Java Script, PHP, Bootstrap, JQuery, React and other scripting languages and libraries. Heat maps and other usability issues; website content strategy. THE MODEL-VIEW-CONTROLLER (MVC) design pattern
  • Social media for institutional use. Digital Curation. Social Media algorithms. Etiquette Ethics. Mastodon
    I hosted a LITA webinar in the fall of 2016 (four weeks); I can accommodate any information from that webinar for the use of the IM students
  • OER and instructional designer’s assistance to book creators.
    I can cover both the “library part” (“free” OER, copyright issues etc) and the support / creative part of an OER book / textbook
  • Big Data.” Data visualization. Large scale visualization. Text encoding. Analytics, Data mining. Unizin. Python, R in academia.
    I can introduce the students to the large idea of Big Data and its importance in lieu of the upcoming IoT, but also departmentalize its importance for academia, business, etc. From infographics to heavy duty visualization (Primo X-Services API. JSON, Flask).
  • NetNeutrality, Digital Darwinism, Internet economy and the role of your professional in such environment
    I can introduce students to the issues, if not familiar and / or lead a discussion on a rather controversial topic
  • Digital assessment. Digital Assessment literacy.
    I can introduce students to tools, how to evaluate and select tools and their pedagogical implications
  • Wikipedia
    a hands-on exercise on working with Wikipedia. After the session, students will be able to create Wikipedia entries thus knowing intimately the process of Wikipedia and its information.
  • Effective presentations. Tools, methods, concepts and theories (cognitive load). Presentations in the era of VR, AR and mixed reality. Unity.
    I can facilitate a discussion among experts (your students) on selection of tools and their didactically sound use to convey information. I can supplement the discussion with my own findings and conclusions.
  • eConferencing. Tools and methods
    I can facilitate a discussion among your students on selection of tools and comparison. Discussion about the their future and their place in an increasing online learning environment
  • Digital Storytelling. Immersive Storytelling. The Moth. Twine. Transmedia Storytelling
    I am teaching a LIB 490/590 Digital Storytelling class. I can adapt any information from that class to the use of IM students
  • VR, AR, Mixed Reality.
    besides Mark Gill, I can facilitate a discussion, which goes beyond hardware and brands, but expand on the implications for academia and corporate education / world
  • IoT , Arduino, Raspberry PI. Industry 4.0
  • Instructional design. ID2ID
    I can facilitate a discussion based on the Educause suggestions about the profession’s development
  • Microcredentialing in academia and corporate world. Blockchain
  • IT in K12. How to evaluate; prioritize; select. obsolete trends in 21 century schools. K12 mobile learning
  • Podcasting: past, present, future. Beautiful Audio Editor.
    a definition of podcasting and delineation of similar activities; advantages and disadvantages.
  • Digital, Blended (Hybrid), Online teaching and learning: facilitation. Methods and techniques. Proctoring. Online students’ expectations. Faculty support. Asynch. Blended Synchronous Learning Environment
  • Gender, race and age in education. Digital divide. Xennials, Millennials and Gen Z. generational approach to teaching and learning. Young vs old Millennials. Millennial employees.
  • Privacy, [cyber]security, surveillance. K12 cyberincidents. Hackers.
  • Gaming and gamification. Appsmashing. Gradecraft
  • Lecture capture, course capture.
  • Bibliometrics, altmetrics
  • Technology and cheating, academic dishonest, plagiarism, copyright.

IRDL proposal

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

Title:

Learning to Harness Big Data in an Academic Library

Abstract (200)

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

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

 

 

Research Literature

“Big data is like teenage sex: everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it…”
– Dan Ariely, 2013  https://www.asist.org/publications/bulletin/aprilmay-2017/big-datas-impact-on-privacy-for-librarians-and-information-professionals/

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

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

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

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

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

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

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

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

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

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

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

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

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

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

 

Method

 

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

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

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

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

 

Sampling design

 

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

 

Project Schedule

 

Complete literature review and identify areas of interest – two months

Prepare and test instrument (survey) – month

IRB and other details – month

Generate a list of potential libraries to distribute survey – month

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

Collect, analyze data – two months

Write out data findings – month

Complete manuscript – month

Proofreading and other details – month

 

Significance of the work 

While it has been widely acknowledged that Big Data (and its handling) is changing higher education (https://blog.stcloudstate.edu/ims?s=big+data) as well as academic libraries (https://blog.stcloudstate.edu/ims/2016/03/29/analytics-in-education/), it remains nebulous how Big Data is handled in the academic library and, respectively, how it is related to the handling of Big Data on campus. Moreover, the visualization of Big Data between units on campus remains in progress, along with any policymaking based on the analysis of such data (hence the need for comprehensive visualization).

 

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

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

 

 

References:

 

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

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

Asamoah, D. A., Sharda, R., Hassan Zadeh, A., & Kalgotra, P. (2017). Preparing a Data Scientist: A Pedagogic Experience in Designing a Big Data Analytics Course. Decision Sciences Journal of Innovative Education, 15(2), 161–190. https://doi.org/10.1111/dsji.12125

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

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

Bruns, A. (2013). Faster than the speed of print: Reconciling ‘big data’ social media analysis and academic scholarship. First Monday, 18(10). Retrieved from http://firstmonday.org/ojs/index.php/fm/article/view/4879

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

Chen, X. W., & Lin, X. (2014). Big Data Deep Learning: Challenges and Perspectives. IEEE Access, 2, 514–525. https://doi.org/10.1109/ACCESS.2014.2325029

Cohen, J., Dolan, B., Dunlap, M., Hellerstein, J. M., & Welton, C. (2009). MAD Skills: New Analysis Practices for Big Data. Proc. VLDB Endow., 2(2), 1481–1492. https://doi.org/10.14778/1687553.1687576

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

Daries, J. P., Reich, J., Waldo, J., Young, E. M., Whittinghill, J., Ho, A. D., … Chuang, I. (2014). Privacy, Anonymity, and Big Data in the Social Sciences. Commun. ACM, 57(9), 56–63. https://doi.org/10.1145/2643132

De Mauro, A. D., Greco, M., & Grimaldi, M. (2016). A formal definition of Big Data based on its essential features. Library Review, 65(3), 122–135. https://doi.org/10.1108/LR-06-2015-0061

De Mauro, A., Greco, M., & Grimaldi, M. (2015). What is big data? A consensual definition and a review of key research topics. AIP Conference Proceedings, 1644(1), 97–104. https://doi.org/10.1063/1.4907823

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

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

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

Graham, M., & Shelton, T. (2013). Geography and the future of big data, big data and the future of geography. Dialogues in Human Geography, 3(3), 255–261. https://doi.org/10.1177/2043820613513121

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

Hashem, I. A. T., Yaqoob, I., Anuar, N. B., Mokhtar, S., Gani, A., & Ullah Khan, S. (2015). The rise of “big data” on cloud computing: Review and open research issues. Information Systems, 47(Supplement C), 98–115. https://doi.org/10.1016/j.is.2014.07.006

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

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

Miltenoff, P., & Hauptman, R. (2005). Ethical dilemmas in libraries: an international perspective. The Electronic Library, 23(6), 664–670. https://doi.org/10.1108/02640470510635746

Philip Chen, C. L., & Zhang, C.-Y. (2014). Data-intensive applications, challenges, techniques and technologies: A survey on Big Data. Information Sciences, 275(Supplement C), 314–347. https://doi.org/10.1016/j.ins.2014.01.015

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

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

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

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

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

Sugimoto, C. R., Ding, Y., & Thelwall, M. (2012). Library and information science in the big data era: Funding, projects, and future [a panel proposal]. Proceedings of the American Society for Information Science and Technology, 49(1), 1–3. https://doi.org/10.1002/meet.14504901187

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

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

Waller, M. A., & Fawcett, S. E. (2013). Data Science, Predictive Analytics, and Big Data: A Revolution That Will Transform Supply Chain Design and Management. Journal of Business Logistics, 34(2), 77–84. https://doi.org/10.1111/jbl.12010

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

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

Willis, J. (2013). Ethics, Big Data, and Analytics: A Model for Application. Educause Review Online. Retrieved from https://docs.lib.purdue.edu/idcpubs/1

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

Wu, X., Zhu, X., Wu, G. Q., & Ding, W. (2014). Data mining with big data. IEEE Transactions on Knowledge and Data Engineering, 26(1), 97–107. https://doi.org/10.1109/TKDE.2013.109

Wu, Z., Wu, J., Khabsa, M., Williams, K., Chen, H. H., Huang, W., … Giles, C. L. (2014). Towards building a scholarly big data platform: Challenges, lessons and opportunities. In IEEE/ACM Joint Conference on Digital Libraries (pp. 117–126). https://doi.org/10.1109/JCDL.2014.6970157

 

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more on big data





Embedded Librarianship in Online Courses

Embedded Librarianship in Online Courses

Instructor: Mimi O’Malley Dates: October 2nd to 27th, 2017

http://libraryjuiceacademy.com/081-embedded-online.php

Learning outcomes:

  • Discuss ways to incorporate library services through the learning management system level.
  • Examine bibliographic instruction in the virtual classroom through team teaching, guest lecturing.
  • Identify librarian roles during the design and development of online courses.
  • Assessing embedded librarianship efforts.

Mimi O’Malley is the learning technology translation strategist at Spalding University. She helps faculty prepare course content for hybrid and fully online courses in addition to incorporating open education resources into courses. She previously wrote and facilitated professional development courses and workshops at the Learning House, Inc. Mimi has presented workshops on online learning topics including assessment, plagiarism, copyright, and curriculum trends at the Learning House, Inc. CONNECT Users Conference, SLOAN-C ALN, Pencils and Pixels and New Horizons Teaching & Learning Conference. Interview with Mimi O’Malley

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

digital microcredentials

Designing and Developing Digital Credentials

Part 1: September 13, 2017 | 1:00–2:30 p.m. ET
Part 2: September 19, 2017 | 1:00–2:30 p.m. ET
Part 3: September 28, 2017 | 1:00–2:30 p.m. ET

https://events.educause.edu/eli/courses/2017/digging-into-badges-designing-and-developing-digital-credentials

Digital badges are receiving a growing amount of attention and are beginning to disrupt the norms of what it means to earn credit or be credentialed. Badges allow the sharing of evidence of skills and knowledge acquired through a wide range of life activity, at a granular level, and at a pace that keeps up with individuals who are always learning—even outside the classroom. As such, those not traditionally in the degree-granting realm—such as associations, online communities, and even employers—are now issuing “credit” for achievement they can uniquely recognize. At the same time, higher education institutions are rethinking the type and size of activities worthy of official recognition. From massive open online courses (MOOCs), service learning, faculty development, and campus events to new ways of structuring academic programs and courses or acknowledging granular or discrete skills and competencies these programs explore, there’s much for colleges and universities to consider in the wide open frontier called badging.

Learning Objectives

During this ELI course, participants will:

  • Explore core concepts that define digital badges, as well as the benefits and use in learning-related contexts
  • Understand the underlying technical aspects of digital badges and how they relate to each other and the broader landscape for each learner and issuing organization
  • Critically review and analyze examples of the adoption of digital credentials both inside and outside higher education
  • Identify and isolate specific programs, courses, or other campus or online activities that would be meaningfully supported and acknowledged with digital badges or credentials
  • Consider the benefit of each minted badge or system to the earner, issuer, and observer
  • Develop a badge constellation or taxonomy for their own project
  • Consider forms of assessment suitable for evaluating badge earning
  • Learn about design considerations around the visual aspects of badges
  • Create a badge-issuing plan
  • Issue badges

NOTE: Participants will be asked to complete assignments in between the course segments that support the learning objectives stated above and will receive feedback and constructive critique from course facilitators on how to improve and shape their work.

Jonathan Finkelstein, CEO, Credly

Jonathan Finkelstein is founder and CEO of Credly, creator of the Open Credit framework, and founder of the open source BadgeOS project. Together these platforms have enabled thousands of organizations to recognize, reward, and market skills and achievement. Previously, he was founder of LearningTimes and co-founder of HorizonLive (acquired by Blackboard), helping mission-driven organizations serve millions of learners through online programs and platforms. Finkelstein is author of Learning in Real Time (Wiley), contributing author to The Digital Museum, co-author of a report for the U.S. Department of Education on the potential for digital badges, and a frequent speaker on digital credentials, open badges, and the future of learning and workforce development. Recent speaking engagements have included programs at The White House, U.S. Chamber of Commerce, Smithsonian, EDUCAUSE, IMS Global, Lumina Foundation, ASAE, and the Federal Reserve. Finkelstein is involved in several open standards initiatives, such as the IMS Global Learning Consortium, Badge Alliance, American Council on Education (ACE) Stackable Credentials Framework Advisory Group, and the Credential Registry. He graduated with honors from Harvard.

Susan Manning, University of Wisconsin-Stout

In addition to helping Credly clients design credential systems in formal and informal settings, Susan Manning comes from the teaching world. Presently she teaches for the University of Wisconsin at Stout, including courses in instructional design, universal design for learning, and the use of games for learning. Manning was recognized by the Sloan Consortium with the prestigious 2013 Excellence in Online Teaching Award. She has worked with a range of academic institutions to develop competency-based programs that integrate digital badges. Several of her publications specifically speak to digital badge systems; other work is centered on technology tools and online education.

EDUC-441 Mobile Learning Instructional Design


(3 cr.)
Repeatable for Credit: No
Mobile learning research, trends, instructional design strategies for curriculum integration and professional development.

EDUC-452 Universal Design for Learning


(2 cr.)
Repeatable for Credit: No
Instructional design strategies that support a wide range of learner differences; create barrier-free learning by applying universal design concepts.

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

back to school discussion

Bryan Alexander (BA) Future Trends of Sept. 7

Are you seeing enrollments change? Which technologies hold the most promise? Will your campus become politically active? What collaborations might power up teaching and learning?

  • the big technological issues for the next year?
    robotics? automation in education? big data / analytics?

organizational transformation. David Stone (Penn State) – centralization vs decentralization. technology is shifting everywhere, even the registrar. BA – where should be the IT department? CFO or Academic Department.

difference between undergrads and grad students and how to address. CETL join center for academic technologies.

faculty role, developing courses and materials. share these materials and make more usable. who should be maintaining these materials. life cycle, compensation for development materials. This is in essence the issues of the OER Open Education Resources initiative in MN

BA: OER and Open Access to Research has very similar models and issues. Open access scholarship both have a lot of impact on campus finances. Library and faculty budges.

Amanda Major is with Division of Digital Learning as part of Academic Affairs at UCF: Are there trends in competency-based learning, assessing quality course and programs, personalized adaptive learning, utilizing data analytics for retention and student success?  BA: CBL continue to grow at state U’s and community colleges.

BA for group discussions: what are the technological changes happening this coming year, not only internally on campus, but global changes and how thy might be affecting us. Amazon Dash button, electric cars for U fleet, newer devices on campus

David Stone: students are price-sensitive. college and U can charge whatever they want and text books can raise prices.

http://hechingerreport.org/ next week

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more on future trends in this IMS blog

https://blog.stcloudstate.edu/ims/2017/05/30/missionu-on-bryan-alexanders-future-trends/

blended learning implementation

Critical Factors for Implementing Blended Learning in Higher Education.

Available from: https://www.researchgate.net/publication/318191000_Critical_Factors_for_Implementing_Blended_Learning_in_Higher_Education [accessed Jul 6, 2017].

Definition of Blended learning

Blended learning is in one dimension broadly defined as “The convergence of online and face-to-face Education” as in the study by Watson (2008). At the same time it is important to also include the dimension of technology and media use as it has been depicted in the multimodal conceptual model in Figure 1 below. This conceptual model was proposed and presented in an article published by Picciano (2009). Critical Factors for Implementing Blended Learning in Higher Education.

 

online face to face hybrid

 

 

 

Several studies that argue for the need to focus on pedagogy and learning objectives and not solely on technology (Hoffinan, 2006; Garrison & Vaughan, 2008; Al amm ary et al., 2014; McGee & Reis, 2012; Shand, Glassett Farrelly & Costa, 2016). Other findings in this study are that technology still is a critical issue (So & Brush, 2008; Fleming, Becker & Newton, 2017), not least in developing regions (AI Busaidi & Al-Shihi, 2012; Raphae1 & Mtebe, 2016), and also the more positive idea of technology as a supporting factor for innovative didactics and instructional design to satisfy the needs in heterogeneous student groups (Picciano, 2009). Critical Factors for Implementing Blended Learning in Higher Education.

Critical factors:

  1. technology
  2. didactics –  pedagogy, instructional design and the teacher role
  3. Course outcomes – learning outcomes and learner satisfaction
  4. collaboration and social presence
  5. course design
  6. the heritage from technology enhanced distance courses
  7. multimodal overload
  8. trends and hypes
  9. economy

Blended learning perspectives

  1. the university perspective
  2. the Learner perspective
  3. the Teacher perspective
  4. the Global perspective

 

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

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