LMS and student learning

Techniques for Unleashing Student Work from Learning Management Systems


the fundamental problem is that learning management systems are ultimately about serving the needs of institutions, not individual students.

In his manifesto on Connectivism, George Siemens writes that in Connectivist learning environments, the “pipes” of a course are more important than what flows through those pipes. The networks that students build are durable structures of lifelong learning, and they are more important

by having students own their learning spaces and democratize the means of production. Rather than forcing students to log in to an institutional LMS, I asked them to create their own websites, blogs, Twitter accounts and spaces on the open Web. In these spaces, students could curate links and connections and share their evolving ideas. Whatever they create is owned and maintained by them, not by me or by Harvard. They can keep their content for three months, three years, or the rest of their lives, so long as they continue to curate and move their published content as platforms change.

so, it is back what i claimed at the turn of the century: LMS were claimed to be invented to make the instructor’s life “easier”: instead of learning HTML, use LMS. My argument was that by the time one learns the interface of WebCT, one can learn HTML and HTML will be remain for the rest of their professional life, whereas WebCT got replaced by D2L and D2L will be replaced by another interface. I was labeled as “D2L hater” for such an opinion.
Now to the argument that LMS was a waste of instructors’ time, is added the new argument that it is also a waste of students’ time.

The way that Connected Courses deal with this challenge is by aggregation, sometimes also called syndication. All of the content produced on student blogs, websites, Twitter accounts and other social media accounts is syndicated to a single website. On the Flow page, every piece of content created by students, myself and teaching staff was aggregated into one place. We also had Blog and Twitter Hubs that displayed only long-form writing from blogs or microposts from Twitter. A Spotlight page highlighted some of the best writings from students.

This online learning environment had three important advantages. First, students owned their means of production. They weren’t writing in discussion forums in order to get 2 points for posting to the weekly prompt. They wrote to communicate with audiences within the class and beyond. Second, everyone’s thinking could be found in the same place, by looking at hashtags and our syndication engines on t509massive.org. Finally, this design allows our learning to be permeable to the outside world. Students could write for audiences they cared about: fellow librarians or English teachers or education technologists working in developing countries. And as our networks grew, colleagues form outside our classroom could share with us, by posting links or thoughts to the #t509massive hashtag.




MediaSpace Lecture Capture

[technology] MnSCU Special Interest Group – New October Webinar – Leveraging MnSCU MediaSpace Through Integration With Cloud-based Lecture Capture

Join us next Tuesday, October 27th from 12:00 PM to 1:00 PM, for a special SIG Series webinar: Leveraging MnSCU MediaSpace Through Integration With Cloud-based Lecture Capture

Are you looking for a more affordable and sustainable way to capture classroom lectures?  Or perhaps that is not even an option due to the on-going costs. Riverland recently replaced its Echo360 system by paring AV-to-IP encoders/decoders with a centrally located array of capture devices, which are integrated with MnSCU MediaSpace. This eliminates the need for a dedicated capture device in each room, as well as the on-going licensing costs of proprietary lecture capture systems. Join us as J.C. Turner shows us how the system works and how you can add this to your campus.

J.C. Turner, Ph.D., is the Director of Instructional Technology and Intellectual Property at Riverland Community College. He has more than 25 years of experience in higher ed, including 15 years of university teaching experience at the graduate and undergraduate levels in electronic media, information and telecommunications, video production, and multimedia authoring. He oversees the library and Office of Instructional Technology, and serves as Riverland’s intellectual property officer and Quality Matters coordinator.

Register for the webinar at http://www.eventbrite.com/o/minnesota-online-quality-initiative-7290950883. Please forward this invitation to others on your campus who might be interested.

big data


Center for Digital Education (CDE)

real-time impact on curriculum structure, instruction delivery and student learning, permitting change and improvement. It can also provide insight into important trends that affect present and future resource needs.

Big Data: Traditionally described as high-volume, high-velocity and high-variety information.
Learning or Data Analytics: The measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs.
Educational Data Mining: The techniques, tools and research designed for automatically extracting meaning from large repositories of data generated by or related to people’s learning activities in educational settings.
Predictive Analytics: Algorithms that help analysts predict behavior or events based on data.
Predictive Modeling: The process of creating, testing and validating a model to best predict the probability of an outcome.

Data analytics, or the measurement, collection, analysis and reporting of data, is driving decisionmaking in many institutions. However, because of the unique nature of each district’s or college’s data needs, many are building their own solutions.

For example, in 2014 the nonprofit company inBloom, Inc., backed by $100 million from the Gates Foundation and the Carnegie Foundation for the Advancement of Teaching, closed its doors amid controversy regarding its plan to store, clean and aggregate a range of student information for states and districts and then make the data available to district-approved third parties to develop tools and dashboards so the data could be used by classroom educators.22

Tips for Student Data Privacy

Know the Laws and Regulations
There are many regulations on the books intended to protect student privacy and safety: the Family Educational Rights and Privacy Act (FERPA), the Protection of Pupil Rights Amendment (PPRA), the Children’s Internet Protection Act (CIPA), the Children’s Online Privacy Protection Act (COPPA) and the Health Insurance Portability and Accountability Act (HIPAA)
— as well as state, district and community laws. Because technology changes so rapidly, it is unlikely laws and regulations will keep pace with new data protection needs. Establish a committee to ascertain your institution’s level of understanding of and compliance with these laws, along with additional safeguard measures.
Make a Checklist Your institution’s privacy policies should cover security, user safety, communications, social media, access, identification rules, and intrusion detection and prevention.
Include Experts
To nail down compliance and stave off liability issues, consider tapping those who protect privacy for a living, such as your school attorney, IT professionals and security assessment vendors. Let them review your campus or district technologies as well as devices brought to campus by students, staff and instructors. Finally, a review of your privacy and security policies, terms of use and contract language is a good idea.
Communicate, Communicate, Communicate
Students, staff, faculty and parents all need to know their rights and responsibilities regarding data privacy. Convey your technology plans, policies and requirements and then assess and re-communicate those throughout each year.

“Anything-as-a-Service” or “X-as-a-Service” solutions can help K-12 and higher education institutions cope with big data by offering storage, analytics capabilities and more. These include:
• Infrastructure-as-a-Service (IaaS): Providers offer cloud-based storage, similar to a campus storage area network (SAN)

• Platform-as-a-Service (PaaS): Opens up application platforms — as opposed to the applications themselves — so others can build their own applications
using underlying operating systems, data models and databases; pre-built application components and interfaces

• Software-as-a-Service (SaaS): The hosting of applications in the cloud

• Big-Data-as-a-Service (BDaaS): Mix all the above together, upscale the amount of data involved by an enormous amount and you’ve got BDaaS


Use accurate data correctly
Define goals and develop metrics
Eliminate silos, integrate data
Remember, intelligence is the goal
Maintain a robust, supportive enterprise infrastructure.
Prioritize student privacy
Develop bullet-proof data governance guidelines
Create a culture of collaboration and sharing, not compliance.

more on big data in this IMS blog:


Technology Instruction available free

Student’s relationship with technology is complex. They recognize its value but still need guidance when it comes to better using it for academics.

Educause’s ECAR Study, 2013

InforMedia Services

IMS faculty would be happy to meet with you or your group at your convenience.
Please request using this Google Form:  http://scsu.mn/1OjBMf9 or
by email: pmiltenoff@stcloudstate.edu | informedia@stcloudstate.edu

How you can reach us:

Services we provide:

  • Instruct and collaborate with faculty, staff and students on specific computer, Cloud and mobile applications
  • Assist faculty in course design and instruction to incorporate SCSU’s resources
  • Join faculty in the classroom instructional designto assist students with learning technology application for the class
  • Consult with faculty on instructional design issues, particularly those that use the World Wide Web, multimedia techniques and interactivity
  • Collaborate with faculty, staff and students on technology-related projects
  • Work with campus units in technology planning and acquisition
  • Respond to faculty, staff and students requests and technology developments


facebook1google2 copyyoutube

adobe connect2


transcription tool

it is a hot topic [and contested] topic at MnSCU, considering ADA. In the MnSCU case, it is video and audio material, here, it is text based. The crowdsourcing idea applies, though…

From: lita-l-request@lists.ala.org <lita-l-request@lists.ala.org> on behalf of Ronald Houk <rhouk@ottumwapubliclibrary.org>
Sent: Thursday, September 10, 2015 10:01 AM
To: lita-l@lists.ala.org
Subject: Re: [lita-l] Crowdsourced transcription tool?


Hi Kathryn,

Scripto looks like an interesting project.  http://scripto.org/


On Thu, Sep 10, 2015 at 8:31 AM, Kathryn Frederick (Library) <kfrederi@skidmore.edu> wrote:


We recently had preservation work done on a number of 16th – 18th century land patents. We will be digitizing them, and would like to transcribe the documents which are hand-written in English and, in some cases, Latin.

Is anyone aware of a tool that would allow us to crowdsource the transcription?

Thanks for any suggestions,



Kathryn Frederick

Head of Digital and Collection Services

Lucy Scribner Library – Skidmore College

Saratoga Springs, NY 12866

(518) 580-5505
To maximize your use of LITA-L or to unsubscribe, see http://www.ala.org/lita/involve/email

Ronald Houk ☕
Assistant Director
Ottumwa Public Library
102 W. Fourth Street
Ottumwa, IA 52501


Subject: Re: [lita-l] Crowdsourced transcription tool?


If you’re interested in a fully hosted solution, you might also check out http://beta.fromthepage.com/. The underlying software is open source and you can install it locally as well.

Ben Brumfield, the guy who developed FromThePage also has a blog, http://manuscripttranscription.blogspot.com/, which has some useful information about different systems.

Danielle Cunniff Plumer

Texas State Library and Archives Commission