social media and news

News Use Across Social Media Platforms 2017

http://www.journalism.org/2017/09/07/news-use-across-social-media-platforms-2017/

some_text

Furthermore, about three-quarters of nonwhites (74%) get news on social media sites, up from 64% in 2016.

Twitter, YouTube and Snapchat have grown in share of users who get news on each site.

Twitter, YouTube and Snapchat have grown in share of users who get news on each site

More Americans now get news on multiple social media sites

Snapchat has by far the youngest group of news users – 82% are ages 18-29. While Facebook and YouTube are still the most popular among this age group for news overall, the makeup of the app’s news audience means that about one-in-five (21%) 18- to 29-year-olds now get news on Snapchat.

Many social media news consumers still get news from more traditional platforms

traditional use of news
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more on social media in this IMS blog
http://blog.stcloudstate.edu/ims?s=social+media

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
http://blog.stcloudstate.edu/ims?s=badges

reimaging first year college experience

Welcome to the Re-Imagining the First Year of College Project George L. Mehaffy
Vice President for Academic Leadership and Change
http://www.aascu.org/RFY/MehaffySpeech.pdf
undertake innovations simultaneously in 4 “buckets”—1. Institutional Intentionality, 2. Curriculum, 3. Faculty and Staff, and 4. Students.

some examples of innovations in each area:

• Institutional Intentionality

* Administrative structures

* Budgeting

*Data and Data Analytics: Predictive analytics, use of data in scheduling and advising, etc.

* Collaborative, not individual. Creating opportunities for crowdsourcing, collective projects, etc.

* Creating a supporting environment for innovation * Building a culture of obligation

 

• Curriculum

* Personalization. Software that takes each student on a different journey

* Course Re-Design: Blended courses such as the ones we are working on. Interdisciplinary courses, gateway courses, etc.

* Pathways: Reduced choice, math alternatives, First Year Seminar, Orientation, Summer Bridge

* Degree maps

 

• Faculty/Staff:

* Incentives for teaching in the first year

* Research about first year outcomes

* Collaboration between academic affairs and student affairs

 

• Students

* Non-Cognitive Factors: belonging, mindset, etc.

* Advising: Professional, linked to data, intrusive, etc.

* Career Focus: purpose, ethnography of work, early field experiences

* Reduction in choices

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more on first year college experience in this IMS blog
http://blog.stcloudstate.edu/ims?s=first+year

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

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

online teaching evaluation

Tobin, T. J., Mandernach, B. J., & Taylor, A. H. (2015). Evaluating Online Teaching: Implementing Best Practices (1 edition). San Francisco, CA: Jossey-Bass.
  1. 5 measurable faculty competencies for on line teaching:
  • attend to unique challenges of distance learning
  • Be familiar with unique learning needs
  • Achieve mastery of course content, structure , and organization
  • Respond to student inquiries
  • Provide detailed feedback
  • Communicate effectively
  • Promote a safe learning environment
  • Monitor student progress
  • Communicate course goals
  • Provide evidence of teaching presence.

Best practices include:

  • Making interactions challenging yet supportive for students
  • Asking learners to be active participants in the learning process
  • Acknowledging variety on the ways that students learn best
  • Providing timely and constructive feedback

Evaluation principles

  • Instructor knowledge
  • Method of instruction
  • Instructor-student rapport
  • Teaching behaviors
  • Enthusiastic teaching
  • Concern for teaching
  • Overall

8. The American Association for higher Education 9 principle4s of Good practice for assessing student learning from 1996 hold equally in the F2F and online environments:

the assessment of student learning beings with educational values

assessment is most effective when it reflects an understanding of learning as multidimensional, integrated and revealed in performance over time

assessment works best when the programs it seeks to improve have clear, explicitly stated purposes.

Assessment requires attention to outcomes but also and equally to the experiences that lead to those outcomes.

Assessment works best when it is ongoing, not episodic

Assessment fosters wider improvement when representatives from across the educational community are involved

Assessment makes a difference when it begins with issues of use and illumines questions that people really care bout

Assessment is most likely to lead to improvements when it is part of the large set of conditions that promote change.

Through assessment, educators meet responsibilities to students and to the public.

9 most of the online teaching evaluation instruments in use today are created to evaluate content design rather than teaching practices.

29 stakeholders for the evaluation of online teaching

  • faculty members with online teaching experience
  • campus faculty members as a means of establishing equitable evaluation across modes of teaching
  • contingent faculty members teaching online
  • department or college administrators
  • members of faculty unions or representative governing organizations
  • administrative support specialists
  • distance learning administrators
  • technology specialists
  • LMS administrators
  • Faculty development and training specialists
  • Institutional assessment and effectiveness specialists
  • Students

Sample student rating q/s

University resources

Rate the effectiveness of the online library for locationg course materials

Based on your experience,

148. Checklist for Online Interactive Learning COIL

150. Quality Online Course Initiative QOCI

151 QM Rubric

154 The Online Insturctor Evaluation System OIES

 

163 Data Analytics: moving beyond student learning

  • # of announcments posted per module
  • # of contributions to the asynchronous discussion boards
  • Quality of the contributions
  • Timeliness of posting student grades
  • Timelines of student feedback
  • Quality of instructional supplements
  • Quality of feedback on student work
  • Frequency of logins
  1. 180 understanding big data
  • reliability
  • validity
  • factor structure

187 a holistics valuation plan should include both formative evaluation, in which observations and rating are undertaken with the purposes of improving teaching and learning, and summative evaluation, in which observation and ratings are used in order to make personnel decisions, such as granting promotion and tenure, remediation, and asking contingent faculty to teach again.

195 separating teaching behaviors from content design

 

 

 

 

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more on online teaching in this IMS blog
http://blog.stcloudstate.edu/ims?s=online+teaching

cognitive load theory

Cognitive load theory: Research that teachers really need to understand
AUGUST 2017 Centre for Education Statistics and Evaluation
https://www.cese.nsw.gov.au/images/stories/PDF/cognitive_load_theory_report_AA1.pdf
Cognitive load theory is built upon two commonly accepted ideas. The first is that there is a limit to how much new information the human brain can process at one time. The second is that there are no known limits to how much stored information can be processed at one time. The aim of cognitive load research is therefore to develop instructional techniques and recommendations that fit within the characteristics of working memory, in order to maximise learning.
Explicit instruction involves teachers clearly showing students what to do and how to do it, rather than having students discover or construct information for themselves
how working memory and long-term memory process and store information
Working memory is the memory system where small amounts of information are stored for a very short duration (RAM). Long-term memory is the memory system where large amounts of information are stored semi-permanently (hard drive)
Cognitive load theory assumes that knowledge is stored in long- term memory in the form of ‘schemas’ 2 . A schema organises elements of information according to how they will be used. According to schema theory, skilled performance is developed through building ever greater numbers of increasingly complex schemas by combining elements of lower level schemas into higher level schemas. There is no limit to how complex schemas can become. An important process in schema construction is automation, whereby information can be processed automatically with minimal conscious effort. Automaticity occurs after extensive practice
Schemas provide a number of important functions that are relevant to learning. First, they provide a system for organising and storing knowledge. Second, and crucially for cognitive load theory, they reduce working memory load. This is because, although there are a limited number of elements that can be held in working memory at one time, a schema constitutes only a single element in working memory. In this way, a high level schema – with potentially infinite informational complexity – can effectively bypass the limits of working memory

Types of cognitive load

Cognitive load theory identifies three different types of cognitive load: intrinsic, extraneous and germane load
Intrinsic cognitive load relates to the inherent difficulty of the subject matter being learnt.

subject matter that is difficult for a novice may be very easy for an expert.
Extraneous cognitive load relates to how the subject matter is taught.
extraneous load is the ‘bad’ type of cognitive load, because it does not directly contribute to learning. Cognitive load theorists consider that instructional design will be most effective when it minimises extraneous load in order to free up the capacity of working memory
Germane cognitive load refers to the load imposed on the working memory by the process of learning – that is, the process of transferring information into the long-term memory through schema construction
the approach of decreasing extraneous cognitive load while increasing germane cognitive load will only be effective if the total cognitive load remains within the limits of working memory
Explicit teaching

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more on educational theories in this IMS blog
http://blog.stcloudstate.edu/ims?s=educational+theories

university deans about future

College deans predict higher-ed is in for remarkable changes in 10 years

By Laura Ascione, Managing Editor, Content Services, @eSN_Laura
September 4th, 2017  New survey reveals more than two-thirds of college deans believe institutional change is on the horizon
The survey findings are from the responses of 109 deans of four-year colleges and universities in March and April 2017. Of the respondents, 61 percent were from public universities and 60 percent have been in their jobs at least five years.
Deans were divided on whether faculty members get enough support in teaching courses online–43 percent said faculty are getting shortchanged in how much help they get in rethinking their courses and teaching with technology, while 40 percent said they believe they are getting enough support and 14 percent are neutral.

One-third of deans agree online courses are comparable to face-to-face courses, and roughly the same proportion said they disagree.

Thirty-seven percent of college deans surveyed described the pace of change at their own institutions as “too slow.” Deans surveyed cite lack of money being the biggest hurdle to change, followed by resource constraints on faculty and staff and a resistance or aversion to change.

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university presidents about future in this IMS blog
http://blog.stcloudstate.edu/ims?s=university+presidents

Loom screencast

Loom – Screencast on Chromebooks, Macs, and PCs

https://www.useloom.com/

http://www.freetech4teachers.com/2017/09/loom-screencast-on-chromebooks-macs-and.html

Loom – Screencast on Chromebooks, Macs, and PCshttp://www.freetech4teachers.com/2017/09/loom-screencast-on-chromebooks-macs-and.html

Posted by Free Technology for Teachers on Friday, September 1, 2017

Please share your impressions and comparisons to the MnSCU available MediaSpace (AKA Kaltura):

https://idpstarid.mnscu.edu/idp/Authn/UserPassword

https://scsu.mediaspace.kaltura.com/

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more on lecture capture in this IMS blog
http://blog.stcloudstate.edu/ims?s=lecture+capture

post portion of video

How to Share a Portion of a YouTube Video

http://www.freetech4teachers.com/2017/09/how-to-share-portion-of-youtube-video.html

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more on video editing in this IMS blog
http://blog.stcloudstate.edu/ims?s=video+editing

more on EdPuzzle in this IMS blog
http://blog.stcloudstate.edu/ims?s=edpuzzle

more on YouTube in this IMS blog
http://blog.stcloudstate.edu/ims?s=youtube

youtube Captivate:

learning and work future

From the LinkedIn “Technology Using Professors”

“scalable learning”, the ability to rapidly adapt to new information and quickly deploy new skills to act upon it.

https://www.linkedin.com/groups/934617/934617-6308656108315648004

Future of Work: Learning To Manage Uncertainty

Published on

https://www.linkedin.com/pulse/learning-uncertainty-imperative-heather-mcgowan

longevity + change rates

4th industrial revolution

We need to recognize that as we leave the third and enter the fourth industrial revolution our systems of learning — that is, codifying knowledge into a curriculum, then transferring that pre-determined knowledge to accepting students so that they can become productive workers – can’t support a rapidly changing world where new knowledge is continuously created and new skills are required to capture opportunity. Deloitte’s John Hagel argues, and we agree, that workers and organizations must now strive for “scalable learning”, the ability to rapidly adapt to new information and quickly deploy new skills to act upon it.

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more on learning and instructions in this IMS blog

http://blog.stcloudstate.edu/ims/2017/03/28/digital-learning/
http://blog.stcloudstate.edu/ims/2014/01/05/what-is-the-difference-between-education-and-training/

http://blog.stcloudstate.edu/ims?s=instruction

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