this why metadata was entered in the post-processed MP4 file using the VLC player
export
H.264 . / iPAD 480p 29.9 fps
Shortcuts:
If you are using Premiere CC: 1. File/New/Sequence. 2. Ctrl M is the shortcut to export (M is for media)
Issues
the two Apple/Macs will deliver error messages with both the export to the MP4 format and for burning the CDs and DVDs.
e.g.
other issues
regular restart required for new capture
error messages e.g.
other issues:
audio. Audio synchronization during the digitization is off. Solution: possible solution is the last of this thread : https://forums.adobe.com/thread/2217377
open in in QT Pro copy an segment then past it into a new QT file and save. It then plays normally in Adobe products.
old Apple desktops. needed to be rebuild and reformatted.
Apple burner issues. issues with Premiere license (bigger organization, bigger bureaucracy – keep the licenses within the library, not with IT or the business department)
old VCRs – one of the VCRs was recording bad audio signal
old VHS tapes: the signal jump makes the digital recording stop, thus requiring a constant attendance of the digitization, instead of letting it be digitized and working on something else
the person who is uploading the digitized VHS movies can “Add Collaborator”
The collaborator can be “co-editor” and / or “co-publisher”
Thus, at the moment, Tom Hegert has been designated to a digitized VHS video as Co-:Publisher and Rhonda Huisman as “Co-Editor.”
Please DO log in into MediaSpace with your STAR ID and confirm that you can locate the video and you can, respectively edit its metadata.
If you can edit the video, this means that the proposed system will work, since the Library can follow the same pattern to “distribute” the videos to the instructors, who these videos are used by; and, respectively these instructors can further control the distribution of the videos in their classes.
issues:
sharing the videos from the generic Library account for MediaSpace to the MediaSPace account of the faculty who had requested the digitization either through sending the link to the video or publish in channel (we called our channel “digitized VHS”)
issue: ripping off content from DVD.
Faculty (mostly teaching online / hybrid courses) want to place teaching material from DVD to MediaSpace. Most DVDs are DRM protected.
Handbreak (https://handbrake.fr/) does not allow ripping DRM-ed DVDs. to bypass this Handbreak issue, we use DVD Decrypter before we run the file through Handbreak
Solutions:
From: “Lanska, Jeremiah K” <Jeremiah.Lanska@ridgewater.edu> Date: Tuesday, September 11, 2018 at 10:03 AM
I use a software on a MAC called MacX DVD Video Converter Pro. https://www.macxdvd.com/
I convert videos to MP4 with this and it just works for just about any DVD. Then upload them to MediaSpace.
From: “Docken, Marti L” <Marti.Docken@saintpaul.edu> Date: Tuesday, September 11, 2018 at 8:17 AM
Good morning Plamen. Here at Saint Paul College, we are asked to get permission from owner when we are looking at making any alterations to a video, tape, etc. This is true of adding closed captioning as well. The attached are forms given by Minnesota State which they may have an updated form.
Thank you and have a wonderful day.
Marti Docken Instructional Technology Specialist 651.846.1339 marti.docken@saintpaul.edu
From: Geri Wilson Sent: Friday, September 14, 2018 3:23 PM
What I do with DVDs is give a warning to the faculty that the MediaSpace link with the captions I’ve created should not be widely shared and should be treated as if it were still a DVD that can be shown in the classroom, but not posted on D2L. Because even if we use those forms, I don’t believe it gives us the right to use the video in a broader way. However, a safer approach might be to burn a new DVD with captions, so that it’s still in the same format that can’t be misused as easily.
Just my 2 cents. Geri
From: “Hunter, Gary B” <Gary.Hunter@minnstate.edu> Date: Friday, September 14, 2018 at 2:55 PM To: Plamen Miltenoff_old <pmiltenoff@stcloudstate.edu> Subject: RE: Process of ripping DVD video to mount it on MediaSpace
I’ll assume the contents of the DVDs are movies/films unless I hear otherwise from you. There’s a lot we need to consider from a copyright perspective. Let me know a day and time that we can touch base via a phone call. Next week my schedule is flexible, so let me know what day and time work for you. Until we speak, here’s some of the information related to making copies of copyrighted works for nonprofit teaching purposes.
There are two sections of the Copyright Act that authorize “copying” of copyrighted works for nonprofit educational purposes. It doesn’t matter if the copyrighted works are being copied from DVDs, CDs, flash drives, a computer’s hard drive, etc., the same sections of the Copyright Act apply.
Section 110(2), also known as the TEACH Act, allows nonprofit educational institutions to make a digital copy of a nondramatic copyrighted work and save it to a server for online and hybrid teaching. I have a TEACH Act checklist on the IP Tools & Forms webpage at http://www.minnstate.edu/system/asa/academicaffairs/policy/copyright/forms.html. The checklist identifies the few things that may not be copied under this section of the Copyright Act. If an instructor meets the various requirements on the checklist, than you can make a digital copy of the entire nondramatic copyrighted work and save it to MediaSpace. For nondramatic works, all MinnState instructors should be able to complete the TEACH Act checklist successfully, so I wouldn’t request a completed checklist from them.
Under the TEACH Act, nonprofit educational institutions are only permitted to make a digital copy of reasonable and limited portions of dramatic copyrighted works. Movies and films are usually dramatic works. Most people in higher education interpret “reasonable and limited portions” to mean something less than the whole and not the entire movie/film. There are several guidance documents on the TEACH Act on the IP Tools & Forms webpage that go into greater detail as to what is reasonable and limited portions. Unfortunately, this section only authorizes the copying of part of the movie/film and not the entire thing.
Section 107 Fair Use of the Copyright Act is the second section that permits copying of copyrighted works for nonprofit educational purposes. Fair Use is used more than any other section to make copies of copyrighted works for nonprofit educational purposes. An instructor needs to complete a fair Use Checklist showing the proposed copying is authorized by fair use. An instructor who completes a Fair Use Checklist that ends up being 50/50 or more in support of fair use for their proposed copying of a copyrighted work, should be able to make the digital copy. Fair Use has some nuances in it for unique situations. Let’s set up a phone call to further discuss them. There is also a flow chart that may helpful at http://www.minnstate.edu/system/asa/academicaffairs/policy/copyright/docs/Flow%20Chart-Using%20video%20in%20Online%20-%20D2L%20Courses.pdf.
We also have to consider whether or not the movies/films were purchased with “personal use” rights or “public performance” rights. Or if an educational license or some similar type of license gives us permission to make copies or publicly perform the movie/film. More layers of the onion that need peeled back to address the copyright concerns.
++++++++++++++
Issue: confidentiality
All digitized material is backedup on DVDs, whether faculty wants a DVD or not.
Some video content is confidential (e.g. interviews with patients) and faculty does not want any extra copies, but the DVD submitted to them. How do we archive / do we archive the content then?
Burning (Archiving)
where to store the burned DVDs? their shelf life is 12 years.
DVD’s must be labeled with soft tip perm marker, not labels. labels glue ages quickly.
all our desktops are outdated (5+ years and older). We used two Apple/Macs. OS El Captain, Version 10.11.6, 2.5 Gxz Intel Core i5. 8GB memory, 1333 MHz DDR3, Graphic Card AMD Radeon HD 6750 MD 512 MB
Question about the process of archiving the CDs and DVDs after burning. What is the best way to archive the digitized material? Store the CD and DVDs? Keep them in the “cloud?”
Question about the management of working files: 1. Premiere digitizes the original hi-quality file in .mov format and it is in GB. The export is in .mp4 format and it is in MB. Is it worth to store the GB-size .mov format and for how long, considering that the working station has a limited HDD of 200GB
we decided to export two types of files using Adobe Premiere: a) a low end .MP4 file about several hundred megabites, which respectively is uploaded in SCSU Media Space (AKA Kaltura) and b) one high-end (better quality) one the realm of several GBs, which was the archived copy
We placed a request for two 2TB HDD with the library dean and 10TB file space with the SCSU IT department. Idea being to have the files for MediaSpace readily available on the hardrives, if we have to make them available to faculty and the high-end files being stored on the SCSU file server.
++++++++++++++++++
Nov. 2019: transfer of accounts. The generic SCSULibraryVideo account is discontinued because of the August 2019 transition to the minnstate.edu. Agreed to host the accumulated digitized videos under the private account of one of the team members, who will be assigning the other members and the requesting faculty as co-editors.
++++++++++++++++++
2. correspondence among Greg J, Tom H and Plamen
email correspondence Greg, Tom, Plamen regarding Kaltura account:
From: Greg <gsjorgensen@stcloudstate.edu> Date: Friday, November 17, 2017 at 11:32 AM To: Plamen Miltenoff <pmiltenoff@stcloudstate.edu> Subject: RE: Question Kaltura
Plamen,
Channels are not required using this workflow. Just the collaboration change.
–g–
From: Miltenoff, Plamen Sent: Friday, November 17, 2017 11:31 AM To: Jorgensen, Greg S. <gsjorgensen@stcloudstate.edu>; Hergert, Thomas R. <trhergert@stcloudstate.edu> Subject: Question Kaltura
Greg,
About the channel:
Do I create one channel (videos)?
It seems to be a better idea to create separate channels for each of faculty, who’s videotapes are digitized.
******* any user you wish to collaborate with, will need to first sign in to mediaspace in order to provision their account.**** After they have signed in, you will be able to add them as collaborator.
Once they’ve been added, they will have access to the video in their MedisSpace account.
Like so:
From the My Media area:
Click ‘Filters’:
Then choose either media I can publish, or media I can edit:
If you want to simply change ownership to the requestor (for video available only to a single person), just choose change media owner on the collaboration tab.
The process above will allow for any number of collaborators, in a fashion similar to ‘on reserve’.
–g–
From: Miltenoff, Plamen Sent: Friday, November 17, 2017 11:19 AM To: Jorgensen, Greg S. <gsjorgensen@stcloudstate.edu>; Hergert, Thomas R. <trhergert@stcloudstate.edu> Subject: FW: Supplemental Account Request Status
Tom,
I submitted the request to Greg with the “SCSULibraryVideo” name
Greg, I submitted, Tom, Rachel W and Rhonda H (and you) as “owners.”
Pls, if possible, do not assigned to Tom ownership rights yet and add him later on.
I also received your approval, so I am starting to work on it
This message confirms your request for a new Supplemental Account with the requested username of SCSULibraryVideo. Please allow 2-3 business days for processing. You will be notified by email when your request is approved or denied. You may also check the status of your request by returning to the Supplemental Accounts Maintenance site.
Thank you for your request and please contact us with questions or concerns.
Once you’ve done that, just let me know the name of the account. (LibraryVideoDrop, SCSULibraryVideo, etc….)
I’ll then add it to the Mediaspace access list.
If there’s already an account to which you have access, we can use that, too. Remember, though, credentials will be shared at least between the two of you.
Well, that is a good question. Do we need a “STAR ID” type of account for the library?
If so, who will be the person to talk to. After Diane Schmitt, I do not know who to ask
Tom, can you ask the library dean’s office for any “generic” account?
Greg, for the time being, is it possible to have me as the “owner” of that account? Would that conflict with my current Kaltura account/content?
Can I participate for this project with my student account (as you helpled me several weeks ago restore it for D2L usage)?
Yes, except that there may be needs for multiple faculty to access the files. Think of it as analogous to DVDs on reserve or even in the general collection.
I think we’re hoping for an account from which we can share Library resources such as the digitized versions of VHS tapes that Plamen and I are creating. As I understand it, a closed channel is probably not the best answer. We need a common repository that can have open access to SCSU Kaltura users.
A single account can’t really be shared in the way you’re asking, but we can easily add a dept. supplemental account to Mediaspace. I just need the name of the account.
Depending on what you intend, maybe a closed channel? Create a closed channel and add individuals as needed?
Can you help me create a MediaSpace account for the library use.
How can it be tight up to the STAR ID login specifications?
Is it possible, let’s say Tom and I to use our STAR ID to login into such account?
Any info is welcome…
Plamen
++++++++++++
3. correspondence on the LITA listserv regarding “best practices for in house digital conversion”
From: <lita-l-request@lists.ala.org> on behalf of Sharona Ginsberg <lita-l@lists.ala.org> Reply-To: “lita-l@lists.ala.org” <lita-l@lists.ala.org> Date: Tuesday, November 21, 2017 at 10:07 AM To: “lita-l@lists.ala.org” <lita-l@lists.ala.org> Subject: Re: [lita-l] best practices for in house digital conversion
I’m at an academic rather than public library, but you can see what we offer for digital conversion here: https://www.oswego.edu/library/digital-conversion. We’ve been generally happy with our equipment, and I especially think the Elgato Video Capture device (VHS to digital) is a good tool.
– Sharona
From: <lita-l-request@lists.ala.org> on behalf of Molly Schwartz <mschwartz@metro.org> Reply-To: “lita-l@lists.ala.org” <lita-l@lists.ala.org> Date: Tuesday, November 21, 2017 at 10:03 AM To: “lita-l@lists.ala.org” <lita-l@lists.ala.org> Subject: Re: [lita-l] best practices for in house digital conversion
I would also definitely recommend DCPL’s Memory Lab and the project to build a Memory Lab Network, which is more applicable to public libraries.
best,
Molly
On Tue, Nov 21, 2017 at 10:49 AM, Stewart Wilson <SWilson@onlib.org> wrote:
Hi all,
I know there is a lot of information already out here, but is anyone up for a conversation about media conversion technologies for public library patrons?
I’m interested in best practices and recommended technologies or guides that you use in your system.
Anything that converts projector slides, 35mm, VHS, photographs, cassette, etc.
We are building a new PC for this and 3D rendering, so any recommendations for things like soundcards or video capture cards are also useful.
Thanks for your help; this group is the best.
Stew Wilson
Paralibrarian for Network Administration and Technology
company or group who is doing online program evaluation?
this information is extracted from the Blend-Online discussion list
Colleagues,
Do you know any company or group who is doing online program evaluation? Our school is seeking a consulting group to come to review our online programs and identify areas relate to online learning that we need to improve.
Thanks,
Carrie Halpin, Ph.D. Professor/Instructional Designer & Technologist eLearning & Instructional Technology (eLIT) Virginia Western Community College 3095 Colonial Ave. SW, Roanoke, VA 24015 Office: Brown Library 102 Phone: 540-857-6636 Fax: 540-857-6138 Email: chalpin@virginiawestern.edu
iDesign will do both of those things using a fee-for-service model versus a revenue-sharing model like Academic Partnerships or 2U. I have no personal experience with any OPM, but iDesign is the only one I know of that offers that ala carte type service.
Libraries supporting social inclusion for refugees and immigrants
UNESCO emphasizes the importance of social inclusion for international
migrants and encourages cities and local governments to “ensure social rights
for migrants to adequate housing, education, health and social care, welfare
and decent standard of living according to basic needs such as food, energy
and water.” Libraries can play an important role in helping new arrivals
acclimate and thrive in a new community.
Do you have a story to share about how your library, on its own or in
collaboration with community organizations, is providing social services and
support for refugees and immigrants? Do you have advice on creating successful
programming to support refugees and immigrants?
Proposal to the SCSU library administration:
Good afternoon,
I will be submitting a proposal about my individual work in that area:
In the fall of 2015, I organized a campus-wide meeting, including St. Cloud community members, on refugees and migrants, by inviting one Syrian and one Somali refugees:
I also reached out across campus (e.g. Dan Wildeson with the Holocaust Center, Geoffrey Tabakin, Stephen Philion).
I organized also the online presence by delivering the personal stories of three refugees:
I also maintain a FB group for the class and in conjunction with the blog (you need to request permission to enter the FB group): https://www.facebook.com/groups/hons221
I am formally proposing / requesting to transition my individual efforts and offering the library to support me in expanding my acitivies on this topic
Here is my rational:
If not on campus, at least in the library, I am the only refugee and for that matter an immigrant. I have the understanding and the compassion of someone, who personally have experienced the hardship of being and immigrant and refugee.
I have amounted information and experience presenting the information and engaging the audience in a discussion regarding a rather controversial (for St. Cloud) issue
I have the experience and skills to conduct such discussions both F2F and online
Based on my rational, here are activities I am proposing:
The library supports a monthly F2F meetings, where I am taking the responsibility to host students with refugee and/or migrant status and facilitate a conversation among those students and other students, faculty, staff, who would like to learn more about the topic and discuss related issues.
Library support constitutes of: e.g. necessary information willingly and actively shared at Reference and Circulation desk. Library faculty and staff willingly and actively promoting the information regarding this opportunity when occasions arise.
The library supports my campus-wide efforts to engage faculty, staff and students. Engagement includes: e.g., proposals to faculty to present in their classes on including refugees and immigrants but related to their classes; assisting students with research and bibliography on their papers related to refugees and immigrants; assisting faculty and students with presentations including refugees and immigrants etc.
Library support constitutes of: e.g. necessary information willingly and actively shared at Reference and Circulation desk. Library faculty and staff willingly and actively promoting the information regarding this opportunity when occasions arise.
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
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.
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.
that kind of tech — expensive, bleeding-edge tools — makes headlines but doesn’t make it into many classrooms, especially the most needy ones. What does, however, is video.
68 percent of teachers are using video in their classrooms, and 74 percent of middle schoolers are watching videos for learning.
Video is a key aspect of our always-online attention economy that’s impacting votingbehavior, and fueling hate speech and trolling. Put simply: Video is a contested civic space.
We need to move from a conflation of digital citizenship with internet safety and protectionism to a view of digital citizenship that’s pro-active and prioritizes media literacy and savvy.
Active viewing — engaging more thoughtfully and deeply with what you watch — is a tried-and-true teaching strategy for making sure you don’t just watch media but retain information.
1. Information security: Developing a risk-based security strategy that keeps pace with security threats and challenges.
2. Student success: Managing the system implementations and integrations that support multiple student success initiatives.
3. Institution-wide IT strategy: Repositioning or reinforcing the role of IT leadership as an integral strategic partner of institutional leadership in achieving institutions missions.
4. Data-enabled institutional culture: Using BI and analytics to inform the broad conversation and answer big questions.
5. Student-centered institution: Understanding and advancing technology’s role in defining the student experience on campus (from applicants to alumni).
6. Higher education affordability: Balancing and rightsizing IT priorities and budget to support IT-enabled institutional efficiencies and innovations in the context if institutional funding realities.
7. IT staffing and organizational models: Ensuring adequate staffing capacity and staff retention in the face of retirements, new sourcing models, growing external competition, rising salaries, and the demands of technology initiatives on both IT and non-IT staff.
8. (tie) Data management and governance: Implementing effective institutional data governance practices.
9. (tie) Digital integrations: Ensuring system interoperability, scalability, and extensibility, as well as data integrity, standards, and governance, across multiple applications and platforms.
10. Change leadership: Helping institutional constituents (including the IT staff) adapt to the increasing pace of technology change.
Applications for the 2018 Institute will be accepted between December 1, 2017 and January 27, 2018. Scholars accepted to the program will be notified in early March 2018.
Title:
Learning to Harness Big Data in an Academic Library
Abstract (200)
Research on Big Data per se, as well as on the importance and organization of the process of Big Data collection and analysis, is well underway. The complexity of the process comprising “Big Data,” however, deprives organizations of ubiquitous “blue print.” The planning, structuring, administration and execution of the process of adopting Big Data in an organization, being that a corporate one or an educational one, remains an elusive one. No less elusive is the adoption of the Big Data practices among libraries themselves. Seeking the commonalities and differences in the adoption of Big Data practices among libraries may be a suitable start to help libraries transition to the adoption of Big Data and restructuring organizational and daily activities based on Big Data decisions. Introduction to the problem. Limitations
The redefinition of humanities scholarship has received major attention in higher education. The advent of digital humanities challenges aspects of academic librarianship. Data literacy is a critical need for digital humanities in academia. The March 2016 Library Juice Academy Webinar led by John Russel exemplifies the efforts to help librarians become versed in obtaining programming skills, and respectively, handling data. Those are first steps on a rather long path of building a robust infrastructure to collect, analyze, and interpret data intelligently, so it can be utilized to restructure daily and strategic activities. Since the phenomenon of Big Data is young, there is a lack of blueprints on the organization of such infrastructure. A collection and sharing of best practices is an efficient approach to establishing a feasible plan for setting a library infrastructure for collection, analysis, and implementation of Big Data.
Limitations. This research can only organize the results from the responses of librarians and research into how libraries present themselves to the world in this arena. It may be able to make some rudimentary recommendations. However, based on each library’s specific goals and tasks, further research and work will be needed.
Big Data is becoming an omnipresent term. It is widespread among different disciplines in academia (De Mauro, Greco, & Grimaldi, 2016). This leads to “inconsistency in meanings and necessity for formal definitions” (De Mauro et al, 2016, p. 122). Similarly, to De Mauro et al (2016), Hashem, Yaqoob, Anuar, Mokhtar, Gani and Ullah Khan (2015) seek standardization of definitions. The main connected “themes” of this phenomenon must be identified and the connections to Library Science must be sought. A prerequisite for a comprehensive definition is the identification of Big Data methods. Bughin, Chui, Manyika (2011), Chen et al. (2012) and De Mauro et al (2015) single out the methods to complete the process of building a comprehensive definition.
In conjunction with identifying the methods, volume, velocity, and variety, as defined by Laney (2001), are the three properties of Big Data accepted across the literature. Daniel (2015) defines three stages in big data: collection, analysis, and visualization. According to Daniel, (2015), Big Data in higher education “connotes the interpretation of a wide range of administrative and operational data” (p. 910) and according to Hilbert (2013), as cited in Daniel (2015), Big Data “delivers a cost-effective prospect to improve decision making” (p. 911).
The importance of understanding the process of Big Data analytics is well understood in academic libraries. An example of such “administrative and operational” use for cost-effective improvement of decision making are the Finch & Flenner (2016) and Eaton (2017) case studies of the use of data visualization to assess an academic library collection and restructure the acquisition process. Sugimoto, Ding & Thelwall (2012) call for the discussion of Big Data for libraries. According to the 2017 NMC Horizon Report “Big Data has become a major focus of academic and research libraries due to the rapid evolution of data mining technologies and the proliferation of data sources like mobile devices and social media” (Adams, Becker, et al., 2017, p. 38).
Power (2014) elaborates on the complexity of Big Data in regard to decision-making and offers ideas for organizations on building a system to deal with Big Data. As explained by Boyd and Crawford (2012) and cited in De Mauro et al (2016), there is a danger of a new digital divide among organizations with different access and ability to process data. Moreover, Big Data impacts current organizational entities in their ability to reconsider their structure and organization. The complexity of institutions’ performance under the impact of Big Data is further complicated by the change of human behavior, because, arguably, Big Data affects human behavior itself (Schroeder, 2014).
De Mauro et al (2015) touch on the impact of Dig Data on libraries. The reorganization of academic libraries considering Big Data and the handling of Big Data by libraries is in a close conjunction with the reorganization of the entire campus and the handling of Big Data by the educational institution. In additional to the disruption posed by the Big Data phenomenon, higher education is facing global changes of economic, technological, social, and educational character. Daniel (2015) uses a chart to illustrate the complexity of these global trends. Parallel to the Big Data developments in America and Asia, the European Union is offering access to an EU open data portal (https://data.europa.eu/euodp/home ). Moreover, the Association of European Research Libraries expects under the H2020 program to increase “the digitization of cultural heritage, digital preservation, research data sharing, open access policies and the interoperability of research infrastructures” (Reilly, 2013).
The challenges posed by Big Data to human and social behavior (Schroeder, 2014) are no less significant to the impact of Big Data on learning. Cohen, Dolan, Dunlap, Hellerstein, & Welton (2009) propose a road map for “more conservative organizations” (p. 1492) to overcome their reservations and/or inability to handle Big Data and adopt a practical approach to the complexity of Big Data. Two Chinese researchers assert deep learning as the “set of machine learning techniques that learn multiple levels of representation in deep architectures (Chen & Lin, 2014, p. 515). Deep learning requires “new ways of thinking and transformative solutions (Chen & Lin, 2014, p. 523). Another pair of researchers from China present a broad overview of the various societal, business and administrative applications of Big Data, including a detailed account and definitions of the processes and tools accompanying Big Data analytics. The American counterparts of these Chinese researchers are of the same opinion when it comes to “think about the core principles and concepts that underline the techniques, and also the systematic thinking” (Provost and Fawcett, 2013, p. 58). De Mauro, Greco, and Grimaldi (2016), similarly to Provost and Fawcett (2013) draw attention to the urgent necessity to train new types of specialists to work with such data. As early as 2012, Davenport and Patil (2012), as cited in Mauro et al (2016), envisioned hybrid specialists able to manage both technological knowledge and academic research. Similarly, Provost and Fawcett (2013) mention the efforts of “academic institutions scrambling to put together programs to train data scientists” (p. 51). Further, Asomoah, Sharda, Zadeh & Kalgotra (2017) share a specific plan on the design and delivery of a big data analytics course. At the same time, librarians working with data acknowledge the shortcomings in the profession, since librarians “are practitioners first and generally do not view usability as a primary job responsibility, usually lack the depth of research skills needed to carry out a fully valid” data-based research (Emanuel, 2013, p. 207).
Borgman (2015) devotes an entire book to data and scholarly research and goes beyond the already well-established facts regarding the importance of Big Data, the implications of Big Data and the technical, societal, and educational impact and complications posed by Big Data. Borgman elucidates the importance of knowledge infrastructure and the necessity to understand the importance and complexity of building such infrastructure, in order to be able to take advantage of Big Data. In a similar fashion, a team of Chinese scholars draws attention to the complexity of data mining and Big Data and the necessity to approach the issue in an organized fashion (Wu, Xhu, Wu, Ding, 2014).
Bruns (2013) shifts the conversation from the “macro” architecture of Big Data, as focused by Borgman (2015) and Wu et al (2014) and ponders over the influx and unprecedented opportunities for humanities in academia with the advent of Big Data. Does the seemingly ubiquitous omnipresence of Big Data mean for humanities a “railroading” into “scientificity”? How will research and publishing change with the advent of Big Data across academic disciplines?
Reyes (2015) shares her “skinny” approach to Big Data in education. She presents a comprehensive structure for educational institutions to shift “traditional” analytics to “learner-centered” analytics (p. 75) and identifies the participants in the Big Data process in the organization. The model is applicable for library use.
Being a new and unchartered territory, Big Data and Big Data analytics can pose ethical issues. Willis (2013) focusses on Big Data application in education, namely the ethical questions for higher education administrators and the expectations of Big Data analytics to predict students’ success. Daries, Reich, Waldo, Young, and Whittinghill (2014) discuss rather similar issues regarding the balance between data and student privacy regulations. The privacy issues accompanying data are also discussed by Tene and Polonetsky, (2013).
Privacy issues are habitually connected to security and surveillance issues. Andrejevic and Gates (2014) point out in a decision making “generated by data mining, the focus is not on particular individuals but on aggregate outcomes” (p. 195). Van Dijck (2014) goes into further details regarding the perils posed by metadata and data to the society, in particular to the privacy of citizens. Bail (2014) addresses the same issue regarding the impact of Big Data on societal issues, but underlines the leading roles of cultural sociologists and their theories for the correct application of Big Data.
Library organizations have been traditional proponents of core democratic values such as protection of privacy and elucidation of related ethical questions (Miltenoff & Hauptman, 2005). In recent books about Big Data and libraries, ethical issues are important part of the discussion (Weiss, 2018). Library blogs also discuss these issues (Harper & Oltmann, 2017). An academic library’s role is to educate its patrons about those values. Sugimoto et al (2012) reflect on the need for discussion about Big Data in Library and Information Science. They clearly draw attention to the library “tradition of organizing, managing, retrieving, collecting, describing, and preserving information” (p.1) as well as library and information science being “a historically interdisciplinary and collaborative field, absorbing the knowledge of multiple domains and bringing the tools, techniques, and theories” (p. 1). Sugimoto et al (2012) sought a wide discussion among the library profession regarding the implications of Big Data on the profession, no differently from the activities in other fields (e.g., Wixom, Ariyachandra, Douglas, Goul, Gupta, Iyer, Kulkami, Mooney, Phillips-Wren, Turetken, 2014). A current Andrew Mellon Foundation grant for Visualizing Digital Scholarship in Libraries seeks an opportunity to view “both macro and micro perspectives, multi-user collaboration and real-time data interaction, and a limitless number of visualization possibilities – critical capabilities for rapidly understanding today’s large data sets (Hwangbo, 2014).
The importance of the library with its traditional roles, as described by Sugimoto et al (2012) may continue, considering the Big Data platform proposed by Wu, Wu, Khabsa, Williams, Chen, Huang, Tuarob, Choudhury, Ororbia, Mitra, & Giles (2014). Such platforms will continue to emerge and be improved, with librarians as the ultimate drivers of such platforms and as the mediators between the patrons and the data generated by such platforms.
Every library needs to find its place in the large organization and in society in regard to this very new and very powerful phenomenon called Big Data. Libraries might not have the trained staff to become a leader in the process of organizing and building the complex mechanism of this new knowledge architecture, but librarians must educate and train themselves to be worthy participants in this new establishment.
Method
The study will be cleared by the SCSU IRB.
The survey will collect responses from library population and it readiness to use and use of Big Data. Send survey URL to (academic?) libraries around the world.
Data will be processed through SPSS. Open ended results will be processed manually. The preliminary research design presupposes a mixed method approach.
The study will include the use of closed-ended survey response questions and open-ended questions. The first part of the study (close ended, quantitative questions) will be completed online through online survey. Participants will be asked to complete the survey using a link they receive through e-mail.
Mixed methods research was defined by Johnson and Onwuegbuzie (2004) as “the class of research where the researcher mixes or combines quantitative and qualitative research techniques, methods, approaches, concepts, or language into a single study” (Johnson & Onwuegbuzie, 2004 , p. 17). Quantitative and qualitative methods can be combined, if used to complement each other because the methods can measure different aspects of the research questions (Sale, Lohfeld, & Brazil, 2002).
Sampling design
Online survey of 10-15 question, with 3-5 demographic and the rest regarding the use of tools.
1-2 open-ended questions at the end of the survey to probe for follow-up mixed method approach (an opportunity for qualitative study)
data analysis techniques: survey results will be exported to SPSS and analyzed accordingly. The final survey design will determine the appropriate statistical approach.
Project Schedule
Complete literature review and identify areas of interest – two months
Prepare and test instrument (survey) – month
IRB and other details – month
Generate a list of potential libraries to distribute survey – month
Contact libraries. Follow up and contact again, if necessary (low turnaround) – month
Collect, analyze data – two months
Write out data findings – month
Complete manuscript – month
Proofreading and other details – month
Significance of the work
While it has been widely acknowledged that Big Data (and its handling) is changing higher education (https://blog.stcloudstate.edu/ims?s=big+data) as well as academic libraries (https://blog.stcloudstate.edu/ims/2016/03/29/analytics-in-education/), it remains nebulous how Big Data is handled in the academic library and, respectively, how it is related to the handling of Big Data on campus. Moreover, the visualization of Big Data between units on campus remains in progress, along with any policymaking based on the analysis of such data (hence the need for comprehensive visualization).
This research will aim to gain an understanding on: a. how librarians are handling Big Data; b. how are they relating their Big Data output to the campus output of Big Data and c. how librarians in particular and campus administration in general are tuning their practices based on the analysis.
Based on the survey returns (if there is a statistically significant return), this research might consider juxtaposing the practices from academic libraries, to practices from special libraries (especially corporate libraries), public and school libraries.
References:
Adams Becker, S., Cummins M, Davis, A., Freeman, A., Giesinger Hall, C., Ananthanarayanan, V., … Wolfson, N. (2017). NMC Horizon Report: 2017 Library Edition.
Andrejevic, M., & Gates, K. (2014). Big Data Surveillance: Introduction. Surveillance & Society, 12(2), 185–196.
Asamoah, D. A., Sharda, R., Hassan Zadeh, A., & Kalgotra, P. (2017). Preparing a Data Scientist: A Pedagogic Experience in Designing a Big Data Analytics Course. Decision Sciences Journal of Innovative Education, 15(2), 161–190. https://doi.org/10.1111/dsji.12125
Bughin, J., Chui, M., & Manyika, J. (2010). Clouds, big data, and smart assets: Ten tech-enabled business trends to watch. McKinsey Quarterly, 56(1), 75–86.
Cohen, J., Dolan, B., Dunlap, M., Hellerstein, J. M., & Welton, C. (2009). MAD Skills: New Analysis Practices for Big Data. Proc. VLDB Endow., 2(2), 1481–1492. https://doi.org/10.14778/1687553.1687576
Daniel, B. (2015). Big Data and analytics in higher education: Opportunities and challenges. British Journal of Educational Technology, 46(5), 904–920. https://doi.org/10.1111/bjet.12230
Daries, J. P., Reich, J., Waldo, J., Young, E. M., Whittinghill, J., Ho, A. D., … Chuang, I. (2014). Privacy, Anonymity, and Big Data in the Social Sciences. Commun. ACM, 57(9), 56–63. https://doi.org/10.1145/2643132
De Mauro, A. D., Greco, M., & Grimaldi, M. (2016). A formal definition of Big Data based on its essential features. Library Review, 65(3), 122–135. https://doi.org/10.1108/LR-06-2015-0061
De Mauro, A., Greco, M., & Grimaldi, M. (2015). What is big data? A consensual definition and a review of key research topics. AIP Conference Proceedings, 1644(1), 97–104. https://doi.org/10.1063/1.4907823
Eaton, M. (2017). Seeing Library Data: A Prototype Data Visualization Application for Librarians. Publications and Research. Retrieved from http://academicworks.cuny.edu/kb_pubs/115
Emanuel, J. (2013). Usability testing in libraries: methods, limitations, and implications. OCLC Systems & Services: International Digital Library Perspectives, 29(4), 204–217. https://doi.org/10.1108/OCLC-02-2013-0009
Graham, M., & Shelton, T. (2013). Geography and the future of big data, big data and the future of geography. Dialogues in Human Geography, 3(3), 255–261. https://doi.org/10.1177/2043820613513121
Hashem, I. A. T., Yaqoob, I., Anuar, N. B., Mokhtar, S., Gani, A., & Ullah Khan, S. (2015). The rise of “big data” on cloud computing: Review and open research issues. Information Systems, 47(Supplement C), 98–115. https://doi.org/10.1016/j.is.2014.07.006
Laney, D. (2001, February 6). 3D Data Management: Controlling Data Volume, Velocity, and Variety.
Miltenoff, P., & Hauptman, R. (2005). Ethical dilemmas in libraries: an international perspective. The Electronic Library, 23(6), 664–670. https://doi.org/10.1108/02640470510635746
Philip Chen, C. L., & Zhang, C.-Y. (2014). Data-intensive applications, challenges, techniques and technologies: A survey on Big Data. Information Sciences, 275(Supplement C), 314–347. https://doi.org/10.1016/j.ins.2014.01.015
Provost, F., & Fawcett, T. (2013). Data Science and its Relationship to Big Data and Data-Driven Decision Making. Big Data, 1(1), 51–59. https://doi.org/10.1089/big.2013.1508
Reyes, J. (2015). The skinny on big data in education: Learning analytics simplified. TechTrends: Linking Research & Practice to Improve Learning, 59(2), 75–80. https://doi.org/10.1007/s11528-015-0842-1
Schroeder, R. (2014). Big Data and the brave new world of social media research. Big Data & Society, 1(2), 2053951714563194. https://doi.org/10.1177/2053951714563194
Sugimoto, C. R., Ding, Y., & Thelwall, M. (2012). Library and information science in the big data era: Funding, projects, and future [a panel proposal]. Proceedings of the American Society for Information Science and Technology, 49(1), 1–3. https://doi.org/10.1002/meet.14504901187
Tene, O., & Polonetsky, J. (2012). Big Data for All: Privacy and User Control in the Age of Analytics. Northwestern Journal of Technology and Intellectual Property, 11, [xxvii]-274.
van Dijck, J. (2014). Datafication, dataism and dataveillance: Big Data between scientific paradigm and ideology. Surveillance & Society; Newcastle upon Tyne, 12(2), 197–208.
Waller, M. A., & Fawcett, S. E. (2013). Data Science, Predictive Analytics, and Big Data: A Revolution That Will Transform Supply Chain Design and Management. Journal of Business Logistics, 34(2), 77–84. https://doi.org/10.1111/jbl.12010
West, D. M. (2012). Big data for education: Data mining, data analytics, and web dashboards. Governance Studies at Brookings, 4, 1–0.
Willis, J. (2013). Ethics, Big Data, and Analytics: A Model for Application. Educause Review Online. Retrieved from https://docs.lib.purdue.edu/idcpubs/1
Wixom, B., Ariyachandra, T., Douglas, D. E., Goul, M., Gupta, B., Iyer, L. S., … Turetken, O. (2014). The current state of business intelligence in academia: The arrival of big data. CAIS, 34, 1.
Wu, X., Zhu, X., Wu, G. Q., & Ding, W. (2014). Data mining with big data. IEEE Transactions on Knowledge and Data Engineering, 26(1), 97–107. https://doi.org/10.1109/TKDE.2013.109
Wu, Z., Wu, J., Khabsa, M., Williams, K., Chen, H. H., Huang, W., … Giles, C. L. (2014). Towards building a scholarly big data platform: Challenges, lessons and opportunities. In IEEE/ACM Joint Conference on Digital Libraries (pp. 117–126). https://doi.org/10.1109/JCDL.2014.6970157
The EDUCAUSE Learning Initiative has just launched its 2018 Key Issues in Teaching and Learning Survey, so vote today: http://www.tinyurl.com/ki2018.
Each year, the ELI surveys the teaching and learning community in order to discover the key issues and themes in teaching and learning. These top issues provide the thematic foundation or basis for all of our conversations, courses, and publications for the coming year. Longitudinally they also provide the way to track the evolving discourse in the teaching and learning space. More information about this annual survey can be found at https://www.educause.edu/eli/initiatives/key-issues-in-teaching-and-learning.
ACADEMIC TRANSFORMATION (Holistic models supporting student success, leadership competencies for academic transformation, partnerships and collaborations across campus, IT transformation, academic transformation that is broad, strategic, and institutional in scope)
ACCESSIBILITY AND UNIVERSAL DESIGN FOR LEARNING (Supporting and educating the academic community in effective practice; intersections with instructional delivery modes; compliance issues)
ADAPTIVE TEACHING AND LEARNING (Digital courseware; adaptive technology; implications for course design and the instructor’s role; adaptive approaches that are not technology-based; integration with LMS; use of data to improve learner outcomes)
COMPETENCY-BASED EDUCATION AND NEW METHODS FOR THE ASSESSMENT OF STUDENT LEARNING (Developing collaborative cultures of assessment that bring together faculty, instructional designers, accreditation coordinators, and technical support personnel, real world experience credit)
DIGITAL AND INFORMATION LITERACIES (Student and faculty literacies; research skills; data discovery, management, and analysis skills; information visualization skills; partnerships for literacy programs; evaluation of student digital competencies; information evaluation)
EVALUATING TECHNOLOGY-BASED INSTRUCTIONAL INNOVATIONS (Tools and methods to gather data;data analysis techniques; qualitative vs. quantitative data; evaluation project design; using findings to change curricular practice; scholarship of teaching and learning; articulating results to stakeholders; just-in-time evaluation of innovations). here is my bibliographical overview on Big Data (scroll down to “Research literature”: https://blog.stcloudstate.edu/ims/2017/11/07/irdl-proposal/ )
EVOLUTION OF THE TEACHING AND LEARNING SUPPORT PROFESSION (Professional skills for T&L support; increasing emphasis on instructional design; delineating the skills, knowledge, business acumen, and political savvy for success; role of inter-institutional communities of practices and consortia; career-oriented professional development planning)
FACULTY DEVELOPMENT (Incentivizing faculty innovation; new roles for faculty and those who support them; evidence of impact on student learning/engagement of faculty development programs; faculty development intersections with learning analytics; engagement with student success)
GAMIFICATION OF LEARNING (Gamification designs for course activities; adaptive approaches to gamification; alternate reality games; simulations; technological implementation options for faculty)
INSTRUCTIONAL DESIGN (Skills and competencies for designers; integration of technology into the profession; role of data in design; evolution of the design profession (here previous blog postings on this issue: https://blog.stcloudstate.edu/ims/2017/10/04/instructional-design-3/); effective leadership and collaboration with faculty)
INTEGRATED PLANNING AND ADVISING FOR STUDENT SUCCESS (Change management and campus leadership; collaboration across units; integration of technology systems and data; dashboard design; data visualization (here previous blog postings on this issue: https://blog.stcloudstate.edu/ims?s=data+visualization); counseling and coaching advising transformation; student success analytics)
LEARNING ANALYTICS (Leveraging open data standards; privacy and ethics; both faculty and student facing reports; implementing; learning analytics to transform other services; course design implications)
LEARNING SPACE DESIGNS (Makerspaces; funding; faculty development; learning designs across disciplines; supporting integrated campus planning; ROI; accessibility/UDL; rating of classroom designs)
MICRO-CREDENTIALING AND DIGITAL BADGING (Design of badging hierarchies; stackable credentials; certificates; role of open standards; ways to publish digital badges; approaches to meta-data; implications for the transcript; Personalized learning transcripts and blockchain technology (here previous blog postings on this issue: https://blog.stcloudstate.edu/ims?s=blockchain)
MOBILE LEARNING (Curricular use of mobile devices (here previous blog postings on this issue:
MULTI-DIMENSIONAL TECHNOLOGIES (Virtual, augmented, mixed, and immersive reality; video walls; integration with learning spaces; scalability, affordability, and accessibility; use of mobile devices; multi-dimensional printing and artifact creation)
NEXT-GENERATION DIGITAL LEARNING ENVIRONMENTS AND LMS SERVICES (Open standards; learning environments architectures (here previous blog postings on this issue: https://blog.stcloudstate.edu/ims/2017/03/28/digital-learning/; social learning environments; customization and personalization; OER integration; intersections with learning modalities such as adaptive, online, etc.; LMS evaluation, integration and support)
ONLINE AND BLENDED TEACHING AND LEARNING (Flipped course models; leveraging MOOCs in online learning; course development models; intersections with analytics; humanization of online courses; student engagement)
OPEN EDUCATION (Resources, textbooks, content; quality and editorial issues; faculty development; intersections with student success/access; analytics; licensing; affordability; business models; accessibility and sustainability)
PRIVACY AND SECURITY (Formulation of policies on privacy and data protection; increased sharing of data via open standards for internal and external purposes; increased use of cloud-based and third party options; education of faculty, students, and administrators)
WORKING WITH EMERGING LEARNING TECHNOLOGY (Scalability and diffusion; effective piloting practices; investments; faculty development; funding; evaluation methods and rubrics; interoperability; data-driven decision-making)
Chun, L. (2017). Discipline and power: knowledge of China in political science. Critical Asian Studies, 49(4), 501-522. doi:10.1080/14672715.2017.1362321
p. 501 – is political science “softer” than the other soft social sciences?
thus… political science “may never live up to its lofty ambition of scientific explanation and prediction. Indeed, like other social sciences, it can be no more than a ‘ science in formation’ permanently seeking to surmount obstacles to objectivity.”
p. 502 disciplinary parochialism
the fetishes of pure observation, raw experience, unambiguous rationality, and one-way causality were formative influences in the genesis of the social sciences. the ‘unfortunate positivism” of such impulses, along with the illusion of a value-free science, converged to produce a behavioral revolution in the interwar period Behaviorism was then followed through an epistemological twist, by boldly optimistic leaps to an “end of ideology” and ultimately to a claimed “end of history” itself.
p. 503
early positivism was openly underpinned by an European condescension toward Asians’ “ignorance and prejudice.” Behind similar depictions lay a comprehensive Eurocentric social and political philosophy.
this is illustrated its view of China through the grand narrative of modernization.
p. 504
Robert McNamara famously reiterated that if World War I was a chemist’s war and Word War II a physicist’s, Vietnam “might well have to be considered the social scientists’ war.”
Although China nominally remains a communist state, it has doubtlessly changed color without a color revolution.
p. 505
In the fixed disciplinary eye, “China” is to specific to produce anything generalizable beyond descriptive and self-containing narratives. The area studies approach, in contrast to disciplinary approaches, is all about cultural, historical, and ethnographic specificities.
If first-hand information contradicts theoretical conclusions, redress is sought only at the former end (my note – ha ha ha, such an elegant but scathing criticism of [Western] academia).
The catch [is] that Chinese otherness is in essence not a matter of cultural difference (hence limitations of criticizing Eurocentrism and Orientalism) and does not merely reproduce itself by inertia.
Given a long omitted self-critical rethinking of the discipline’s parochial base, calling for cross-fertilizing alone would be fruitless or even lead only to a one-way colonization of seemingly particularistic histories by an illusive universal science.
p. 506
political culture, once a key concept of political science’s hope for unified theorization, has turned out to be no answer
Long after its heyday, modernization theory – now with its new face of globalization – remains a primary signifier and legitimating benchmark. To those, who use it to gauge developments since 1945, private property and liberal democracy are permanent, unquestioned norms that are to be globally homogenized.
Moreover, since modernity is assumed to be a liberal capitalists condition, the revolutionary nationalism of an oppressed people remaking itself into a new historical subject noncompliant with capitalism cannot be modernizational.
p. 507
Political scientists and historical sociologists… saw the communist in power as formidable modernizers, but distinguished the Maoist model from the Stalinist in economic management and campaign politics.
Their analyses showed how organic connections between top-down mobilization and bottom-up participation cultivated in an active citizenry and high intensity politics. My note: I disagree here with the author, since such statement can be arbitrary from a historical point of view; indeed, for a short period of time, such “organic connection” can produce positive results, but once calcitrated (as it is in China for the past 6-7 decades), it turns stagnant.
p. 510
the state’s altered support base is essentially a matter of class power, involving both adaptive cultivation of new economic elites and iron-fist approaches to protest and dissent. By the same weight of historical logic, the party’s internal decay, loss of its founding ideological vision and commitment, and collusion with capital will do more than any outside force ever could do to destroy the regime.
That the Party stays in power is not primarily because the country’s economy continues to grow, but is more attributable to a residual social reliance on its credentials and organizational capacities accumulated in earlier revolutionary and socialist struggles. This historical promise has so far worked to the extent that cracks within the leadership are more or less held in check, resentment against local wrongs are insulated from central intentions, and social policies in one way or another respond to common outcries, consultative deliberations, and pressure groups.
p. 511
The word “madness” has indeed been freely employed to describe nations and societies judged inept at modern reason, as found in contemporary academic publications on epi- sodes of the PRC history. My note: I agree with this – the deconstructionalists: (Jaques Derrida, Tzvetan Todorov) linguistically prove the inability of Western cultures to understand and explain other cultures. In this case, Lin Chun is right; just because western political scientist cannot comprehend foreign complex societal problems and/or juxtaposing them to their own “schemes,” prompts the same western researchers to announce them as “mad.”
p. 513aa
This is the best and worst of times for the globalization of knowledge. In one scenario, an eventual completion of the political science parameters can now seal both knowledge, sophisticatedly canalized, and ideology, universally uncontested – even if the two are never separable in the foundation of political science. In another scenario, causes and effects no longer rule out atypical polities, but the differences are presented as culturally incompatible. In either case, the trick remains to let anormalies make the norms validate preexist- ing disciplinary sanctions.
p. 514
Overcoming outmoded rigidities will nurture a robust scholarship committed to universally resonant theories.
Minecraft for Higher Ed? Try it. Pros, Cons, Recommendations?
Description: Why Minecraft, the online video game? How can Minecraft improve learning for higher education? We’ll begin with a live demo in which all can participate (see “Minecraft for Free”). We’ll review “Examples, Not Rumors” of successful adaptations and USES of Minecraft for teaching/learning in higher education. Especially those submitted in advance And we’ll try to extract from these activities a few recommendations/questions/requests re Minecraft in higher education.
Callaghan, N. (2016). Investigating the role of Minecraft in educational learning environments. Educational Media International, 53(4), 244-260. doi:10.1080/09523987.2016.1254877
Noelene Callaghan dissects the evolution in Australian education from a global perspective. She rightfully draws attention (p. 245) to inevitable changes in the educational world, which still remain ignored: e.g., the demise of “traditional” LMS (Educase is calling for their replacement with digital learning environments https://blog.stcloudstate.edu/ims/2017/07/06/next-gen-digital-learning-environment/ and so does the corporate world of learning: https://blog.stcloudstate.edu/ims/2017/03/28/digital-learning/ ), the inevitability of BYOD (mainly by the “budget restrictions and sustainability challenges” (p. 245); by the assertion of cloud computing, and, last but not least, by the gamification of education.
p. 245 literature review. In my paper, I am offering more comprehensive literature review. While Callaghan focuses on the positive, my attempt is to list both pros and cons: http://scsu.mn/1F008Re
246 General use of massive multiplayer online role playing games (MMORPGs)
levels of interaction have grown dramatically and have led to the creation of general use of massive multiplayer online role playing games (MMORPGs)
247 In teaching and learning environments, affordances associated with edugames within a project-based learning (PBL) environment permit:
These affordances develop both social and cognitive abilities of students
Nebel, S., Schneider, S., Beege, M., Kolda, F., Mackiewicz, V., & Rey, G. (2017). You cannot do this alone! Increasing task interdependence in cooperative educational videogames to encourage collaboration. Educational Technology Research & Development, 65(4), 993-1014. doi:10.1007/s11423-017-9511-8
Abrams, S. S., & Rowsell, J. (2017). Emotionally Crafted Experiences: Layering Literacies in Minecraft. Reading Teacher, 70(4), 501-506.
Nebel, S., Schneider, S., & Daniel Rey, G. (2016). Mining Learning and Crafting Scientific Experiments: A Literature Review on the Use of Minecraft in Education and Research. Source: Journal of Educational Technology & Society, 19(192), 355–366. Retrieved from http://www.jstor.org/stable/jeductechsoci.19.2.355
Cipollone, M., Schifter, C. C., & Moffat, R. A. (2014). Minecraft as a Creative Tool: A Case Study. International Journal Of Game-Based Learning, 4(2), 1-14.
Niemeyer, D. J., & Gerber, H. R. (2015). Maker culture and Minecraft : implications for the future of learning. Educational Media International, 52(3), 216-226. doi:10.1080/09523987.2015.1075103
Nebel, S., Schneider, S., & Daniel Rey, G. (2016). Mining Learning and Crafting Scientific Experiments: A Literature Review on the Use of Minecraft in Education and Research. Journal of Educational Technology & Society, 19(192), 355–366. Retrieved from http://www.jstor.org/stable/jeductechsoci.19.2.355
Wilkinson, B., Williams, N., & Armstrong, P. (2013). Improving Student Understanding, Application and Synthesis of Computer Programming Concepts with Minecraft. In The European Conference on Technology in the Classroom 2013. Retrieved from http://iafor.info/archives/offprints/ectc2013-offprints/ECTC2013_0477.pdf
Uusi-Mäkelä, M., & Uusi-Mäkelä, M. (2014). Immersive Language Learning with Games: Finding Flow in MinecraftEdu. EdMedia: World Conference on Educational Media and Technology (Vol. 2014). Association for the Advancement of Computing in Education (AACE). Retrieved from https://www.learntechlib.org/noaccess/148409/
Birt, J., & Hovorka, D. (2014). Effect of mixed media visualization on learner perceptions and outcomes. In 25th Australasian Conference on Information Systems (pp. 1–10). Retrieved from http://epublications.bond.edu.au/fsd_papers/74
Al Washmi, R., Bana, J., Knight, I., Benson, E., Afolabi, O., Kerr, A., Hopkins, G. (2014). Design of a Math Learning Game Using a Minecraft Mod. https://doi.org/10.13140/2.1.4660.4809
to bypass this Handbreak issue, we use DVD Decrypter before we run the file through Handbreak
Burning (Archiving)