Cut the curriculum — from willrichardson.com by Will Richardson

Excerpt:

Here’s an idea: A Minimal Viable Curriculum (MVC). That’s what Christian Talbot over at Basecamp is proposing, and I have to say, I love the idea.

He writes: “What if we were to design MVCs: Minimum Viable Curricula centered on just enough content to empower learners to examine questions or pursue challenges with rigor? Then, as learners go deeper into a question or challenge, they update their MVC…which is pretty much how learning happens in the real world.”

The key there to me is that THEY update their MVC. That resonates so deeply; it feels like that’s what I’m doing with my learning each day as I read about and work with school leaders who are thinking deeply about change.

 

When we pursue questions that matter to us, rigor is baked in.

 

From DSC:
I love the idea of giving students — as they can handle it — more choice, more control. So anytime around 8th-12th grade, I say we turn much more control over to the students, and let them make more choices on what they want to learn about. We should at least try some experiments along these lines.

 

 

As everyone in the workforce is now required to be a lifelong learner, our quality of life goes much higher if we actually enjoy learning. As I think about it, I have often heard an adult (especially middle age and older) say something like, “I hated school, but now, I love to learn.”

Plus, I can easily imagine greater engagement with the materials that students choose for themselves, as well as increased attention spans and higher motivation levels.

Also, here’s a major shout out to Will Richardson, Bruce Dixon, Missy Emler and Lyn Hilt for the work they are doing at ModernLearners.com.

 

Check out the work over at Modern Learners dot com

 

 

Top six AI and automation trends for 2019 — from forbes.com by Daniel Newman

Excerpt:

If your company hasn’t yet created a plan for AI and automation throughout your enterprise, you have some work to do. Experts believe AI will add nearly $16 trillion to the global economy by 2030, and 20 % of companies surveyed are already planning to incorporate AI throughout their companies next year. As 2018 winds down, now is the time to take a look at some trends and predictions for AI and automation that I believe will dominate the headlines in 2019—and to think about how you may incorporate them into your own company.

 

Also see — and an insert here from DSC:

Kai-Fu has a rosier picture than I do in regards to how humanity will be impacted by AI. One simply needs to check out today’s news to see that humans have a very hard time creating unity, thinking about why businesses exist in the first place, and being kind to one another…

 

 

 

How AI can save our humanity 

 

 

 

The world is changing. Here’s how companies must adapt. — from weforum.org by Joe Kaeser, President and Chief Executive Officer, Siemens AG

Excerpts (emphasis DSC):

Although we have only seen the beginning, one thing is already clear: the Fourth Industrial Revolution is the greatest transformation human civilization has ever known. As far-reaching as the previous industrial revolutions were, they never set free such enormous transformative power.

The Fourth Industrial Revolution is transforming practically every human activity...its scope, speed and reach are unprecedented.

Enormous power (Insert from DSC: What I was trying to get at here) entails enormous risk. Yes, the stakes are high. 

 

“And make no mistake about it: we are now writing the code that will shape our collective future.” CEO of Siemens AG

 

 

Contrary to Milton Friedman’s maxim, the business of business should not just be business. Shareholder value alone should not be the yardstick. Instead, we should make stakeholder value, or better yet, social value, the benchmark for a company’s performance.

Today, stakeholders…rightfully expect companies to assume greater social responsibility, for example, by protecting the climate, fighting for social justice, aiding refugees, and training and educating workers. The business of business should be to create value for society.

This seamless integration of the virtual and the physical worlds in so-called cyber-physical systems – that is the giant leap we see today. It eclipses everything that has happened in industry so far. As in previous industrial revolutions but on a much larger scale, the Fourth Industrial Revolution will eliminate millions of jobs and create millions of new jobs.

 

“…because the Fourth Industrial Revolution runs on knowledge, we need a concurrent revolution in training and education.

If the workforce doesn’t keep up with advances in knowledge throughout their lives, how will the millions of new jobs be filled?” 

Joe Kaeser, President and Chief Executive Officer, Siemens AG

 

 


From DSC:
At least three critically important things jump out at me here:

  1. We are quickly approaching a time when people will need to be able to reinvent themselves quickly and cost-effectively, especially those with families and who are working in their (still existing) jobs. (Or have we already entered this period of time…?)
  2. There is a need to help people identify which jobs are safe to reinvent themselves to — at least for the next 5-10 years.
  3. Citizens across the globe — and their relevant legislatures, governments, and law schools — need to help close the gap between emerging technologies and whether those technologies should even be rolled out, and if so, how and with which features.

 


 

What freedoms and rights should individuals have in the digital age?

Joe Kaeser, President and Chief Executive Officer, Siemens AG

 

 

5 influencers predict AI’s impact on business in 2019 — from martechadvisor.com by Christine Crandell

Excerpt:

With Artificial Intelligence (AI) already proving its worth to adopters, it’s not surprising that an increasing number of companies will implement and leverage AI in 2019. Now, it’s no longer a question of whether AI will take off. Instead, it’s a question of which companies will keep up. Here are five predictions from five influencers on the impact AI will have on businesses in 2019, writes Christine Crandell, President, New Business Strategies.

 

 

Should we be worried about computerized facial recognition? — from newyorker.com by David Owen
The technology could revolutionize policing, medicine, even agriculture—but its applications can easily be weaponized.

 

Facial-recognition technology is advancing faster than the people who worry about it have been able to think of ways to manage it. Indeed, in any number of fields the gap between what scientists are up to and what nonscientists understand about it is almost certainly greater now than it has been at any time since the Manhattan Project. 

 

From DSC:
This is why law schools, legislatures, and the federal government need to become much more responsive to emerging technologies. The pace of technological change has changed. But have other important institutions of our society adapted to this new pace of change?

 

 

Andrew Ng sees an eternal springtime for AI — from zdnet.com by Tiernan Ray
Former Google Brain leader and Baidu chief scientist Andrew Ng lays out the steps companies should take to succeed with artificial intelligence, and explains why there’s unlikely to be another “AI winter” like in times past.

 

 

Google Lens now recognizes over 1 billion products — from venturebeat.com by Kyle Wiggers with thanks to Marie Conway for her tweet on this

Excerpt:

Google Lens, Google’s AI-powered analysis tool, can now recognize over 1 billion products from Google’s retail and price comparison portal, Google Shopping. That’s four times the number of objects Lens covered in October 2017, when it made its debut.

Aparna Chennapragada, vice president of Google Lens and augmented reality at Google, revealed the tidbit in a retrospective blog post about Google Lens’ milestones.

 

Amazon Customer Receives 1,700 Audio Files Of A Stranger Who Used Alexa — from npr.org by Sasha Ingber

Excerpt:

When an Amazon customer in Germany contacted the company to review his archived data, he wasn’t expecting to receive recordings of a stranger speaking in the privacy of a home.

The man requested to review his data in August under a European Union data protection law, according to a German trade magazine called c’t. Amazon sent him a download link to tracked searches on the website — and 1,700 audio recordings by Alexa that were generated by another person.

“I was very surprised about that because I don’t use Amazon Alexa, let alone have an Alexa-enabled device,” the customer, who was not named, told the magazine. “So I randomly listened to some of these audio files and could not recognize any of the voices.”

 

 

5 questions we should be asking about automation and jobs — from hbr.org by Jed Kolko

Excerpts:

  1. Will workers whose jobs are automated be able to transition to new jobs?*
  2. Who will bear the burden of automation?
  3. How will automation affect the supply of labor?
  4. How will automation affect wages, and how will wages affect automation?
  5. How will automation change job searching?

 

From DSC:
For those Economics profs and students out there, I’m posted this with you in mind; also highly applicable and relevant to MBA programs.

* I would add a few follow-up questions to question #1 above:

  • To which jobs should they transition to?
  • Who can help identify the jobs that might be safe for 5-10 years?
  • If you have a family to feed, how are you going to be able to reinvent yourself quickly and as efficiently/flexibly as possible? (Yes…constant, online-based learning comes to my mind as well, as campus-based education is great, but very time-consuming.)

 

Also see:

We Still Don’t Know Much About the Jobs the AI Economy Will Make — or Take — from medium.com by Rachel Metz with MIT Technology Review
Experts think companies need to invest in workers the way they do for other core aspects of their business they’re looking to future-proof

One big problem that could have lasting effects, she thinks, is a mismatch between the skills companies need in new employees and those that employees have or know that they can readily acquire. To fix this, she said, companies need to start investing in their workers the way they do their supply chains.

 

Per LinkedIn:

Putting robots to work is becoming more and more popularparticularly in Europe. According to the European Bank for Reconstruction and Development, Slovakian workers face a 62% median probability that their job will be automated “in the near future.” Workers in Eastern Europe face the biggest likelihood of having their jobs overtaken by machines, with the textile, agriculture and manufacturing industries seen as the most vulnerable. • Here’s what people are saying.

 

Robot Ready: Human+ Skills for the Future of Work — from economicmodeling.com

Key Findings

In Robot-Ready, we examine several striking insights:

1. Human skills—like leadership, communication, and problem solving—are among the most in-demand skills in the labor market.

2. Human skills are applied differently across career fields. To be effective, liberal arts grads must adapt their skills to the job at hand.

3. Liberal art grads should add technical skills. There is considerable demand for workers who complement their human skills with basic technical skills like data analysis and digital fluency.

4. Human+ skills are at work in a variety of fields. Human skills help liberal arts grads thrive in many career areas, including marketing, public relations, technology, and sales.

 

 

 

From DSC:
Not too long ago, I really enjoyed watching a program on PBS regarding America’s 100 most-loved books, entitled, “The Great American Read.”

 

Watch “The Grand Finale”

 

While that’s not the show I’m talking about, it got me to thinking of one similar to it — something educational, yet entertaining. But also, something more.

The program that came to my mind would be a program that’s focused on significant topics and issues within American society — offered up in a debate/presentation style format. 

For example, you could have different individuals, groups, or organizations discuss the pros and cons of an issue or topic. The show would provide contact information for helpful resources, groups, organizations, legislators, etc.  These contacts would be for learning more about a subject or getting involved with finding a solution for that problem.

For example, how about this for a potential topic: Grades or no grades?
  • What are the pros and cons of using an A-F grading system?
  • What are the benefits and issues/drawbacks with using grades? 
  • How are we truly using grades Do we use them to rank and compare individuals, schools, school systems, communities? Do we use them to “weed people out” of a program?
  • With our current systems, what “product” do we get? Do we produce game-players or people who enjoy learning? (Apologies for some of my bias showing up here! But my son has become a major game-player and, likely, so did I at his age.)
  • How do grades jibe with Individualized Education Programs (IEPs)? On one hand…how do you keep someone moving forward, staying positive, and trying to keep learning/school enjoyable yet on the other hand, how do you have those grades mean something to those who obtain data to rank school systems, communities, colleges, programs, etc.?
  • How do grades impact one’s desire to learn throughout one’s lifetime?

Such debates could be watched by students and then they could have their own debates on subjects that they propose.

Or the show could have journalists debate college or high school teams. The format could sometimes involve professors and deans debating against researchers. Or practitioners/teachers debating against researchers/cognitive psychologists. 

Such a show could be entertaining, yet highly applicable and educational. We would probably all learn something. And perhaps have our eyes opened up to a new perspective on an issue.

Or better yet, we might actually resolve some more issues and then move on to address other ones!

 

 

 

From DSC:
When a professor walks into the room, the mobile device that the professor is carrying notifies the system to automatically establish his or her preferred settings for the room — and/or voice recognition allows a voice-based interface to adjust the room’s settings:

  • The lights dim to 50%
  • The projector comes on
  • The screen comes down
  • The audio is turned up to his/her liking
  • The LMS is logged into with his/her login info and launches the class that he/she is teaching at that time of day
  • The temperature is checked and adjusted if too high or low
  • Etc.
 

Forecast 5.0 – The Future of Learning: Navigating the Future of Learning  — from knowledgeworks.org by Katherine Prince, Jason Swanson, and Katie King
Discover how current trends could impact learning ten years from now and consider ways to shape a future where all students can thrive.

 

 

 

AI Now Report 2018 | December 2018  — from ainowinstitute.org

Meredith Whittaker , AI Now Institute, New York University, Google Open Research
Kate Crawford , AI Now Institute, New York University, Microsoft Research
Roel Dobbe , AI Now Institute, New York University
Genevieve Fried , AI Now Institute, New York University
Elizabeth Kaziunas , AI Now Institute, New York University
Varoon Mathur , AI Now Institute, New York University
Sarah Myers West , AI Now Institute, New York University
Rashida Richardson , AI Now Institute, New York University
Jason Schultz , AI Now Institute, New York University School of Law
Oscar Schwartz , AI Now Institute, New York University

With research assistance from Alex Campolo and Gretchen Krueger (AI Now Institute, New York University)

Excerpt (emphasis DSC):

Building on our 2016 and 2017 reports, the AI Now 2018 Report contends with this central problem, and provides 10 practical recommendations that can help create accountability frameworks capable of governing these powerful technologies.

  1. Governments need to regulate AI by expanding the powers of sector-specific agencies to oversee, audit, and monitor these technologies by domain.
  2. Facial recognition and affect recognition need stringent regulation to protect the public interest.
  3. The AI industry urgently needs new approaches to governance. As this report demonstrates, internal governance structures at most technology companies are failing to ensure accountability for AI systems.
  4. AI companies should waive trade secrecy and other legal claims that stand in the way of accountability in the public sector.
  5. Technology companies should provide protections for conscientious objectors, employee organizing, and ethical whistleblowers.
  6.  Consumer protection agencies should apply “truth-in-advertising” laws to AI products and services.
  7. Technology companies must go beyond the “pipeline model” and commit to addressing the practices of exclusion and discrimination in their workplaces.
  8. Fairness, accountability, and transparency in AI require a detailed account of the “full stack supply chain.”
  9. More funding and support are needed for litigation, labor organizing, and community participation on AI accountability issues.
  10. University AI programs should expand beyond computer science and engineering disciplines. AI began as an interdisciplinary field, but over the decades has narrowed to become a technical discipline. With the increasing application of AI systems to social domains, it needs to expand its disciplinary orientation. That means centering forms of expertise from the social and humanistic disciplines. AI efforts that genuinely wish to address social implications cannot stay solely within computer science and engineering departments, where faculty and students are not trained to research the social world. Expanding the disciplinary orientation of AI research will ensure deeper attention to social contexts, and more focus on potential hazards when these systems are applied to human populations.

 

Also see:

After a Year of Tech Scandals, Our 10 Recommendations for AI — from medium.com by the AI Now Institute
Let’s begin with better regulation, protecting workers, and applying “truth in advertising” rules to AI

 

Also see:

Excerpt:

As we discussed, this technology brings important and even exciting societal benefits but also the potential for abuse. We noted the need for broader study and discussion of these issues. In the ensuing months, we’ve been pursuing these issues further, talking with technologists, companies, civil society groups, academics and public officials around the world. We’ve learned more and tested new ideas. Based on this work, we believe it’s important to move beyond study and discussion. The time for action has arrived.

We believe it’s important for governments in 2019 to start adopting laws to regulate this technology. The facial recognition genie, so to speak, is just emerging from the bottle. Unless we act, we risk waking up five years from now to find that facial recognition services have spread in ways that exacerbate societal issues. By that time, these challenges will be much more difficult to bottle back up.

In particular, we don’t believe that the world will be best served by a commercial race to the bottom, with tech companies forced to choose between social responsibility and market success. We believe that the only way to protect against this race to the bottom is to build a floor of responsibility that supports healthy market competition. And a solid floor requires that we ensure that this technology, and the organizations that develop and use it, are governed by the rule of law.

 

From DSC:
This is a major heads up to the American Bar Association (ABA), law schools, governments, legislatures around the country, the courts, the corporate world, as well as for colleges, universities, and community colleges. The pace of emerging technologies is much faster than society’s ability to deal with them! 

The ABA and law schools need to majorly pick up their pace — for the benefit of all within our society.

 

 

 

Alexa, get me the articles (voice interfaces in academia) — from blog.libux.co by Kelly Dagan

Excerpt:

Credit to Jill O’Neill, who has written an engaging consideration of applications, discussions, and potentials for voice-user interfaces in the scholarly realm. She details a few use case scenarios: finding recent, authoritative biographies of Jane Austen; finding if your closest library has an item on the shelf now (and whether it’s worth the drive based on traffic).

Coming from an undergraduate-focused (and library) perspective, I can think of a few more:

  • asking if there are any group study rooms available at 7 pm and making a booking
  • finding out if [X] is open now (Archives, the Cafe, the Library, etc.)
  • finding three books on the Red Brigades, seeing if they are available, and saving the locations
  • grabbing five research articles on stereotype threat, to read later

 

Also see:

 

 

 

LinkedIn Learning Opens Its Platform (Slightly) [Young]

LinkedIn Learning Opens Its Platform (Slightly) — from edsurge by Jeff Young

Excerpt (emphasis DSC):

A few years ago, in a move toward professional learning, LinkedIn bought Lynda.com for $1.5 billion, adding the well-known library of video-based courses to its professional social network. Today LinkedIn officials announced that they plan to open up their platform to let in educational videos from other providers as well—but with a catch or two.

The plan, announced Friday, is to let companies or colleges who already subscribe to LinkedIn Learning add content from a select group of other providers. The company or college will still have to subscribe to those other services separately, so it’s essentially an integration—but it does mark a change in approach.

For LinkedIn, the goal is to become the front door for employees as they look for micro-courses for professional development.

 

LinkedIn also announced another service for its LinkedIn Learning platform called Q&A, which will give subscribers the ability to pose a question they have about the video lessons they’re taking. The question will first be sent to bots, but if that doesn’t yield an answer the query will be sent on to other learners, and in some cases the instructor who created the videos.

 

 

Also see:

LinkedIn becomes a serious open learning experience platform — from clomedia.com by Josh Bersin
LinkedIn is becoming a dominant learning solution with some pretty interesting competitive advantages, according to one learning analyst.

Excerpt:

LinkedIn has become quite a juggernaut in the corporate learning market. Last time I checked the company had more than 17 million users, 14,000 corporate customers, more than 3,000 courses and was growing at high double-digit rates. And all this in only about two years.

And the company just threw down the gauntlet; it’s now announcing it has completely opened up its learning platform to external content partners. This is the company’s formal announcement that LinkedIn Learning is not just an amazing array of content, it is a corporate learning platform. The company wants to become a single place for all organizational learning content.

 

LinkedIn now offers skills-based learning recommendations to any user through its machine learning algorithms. 

 

 



Is there demand for staying relevant? For learning new skills? For reinventing oneself?

Well…let’s see.

 

 

 

 

 

 



From DSC:
So…look out higher ed and traditional forms of accreditation — your window of opportunity may be starting to close. Alternatives to traditional higher ed continue to appear on the scene and gain momentum. LinkedIn — and/or similar organizations in the future — along with blockchain and big data backed efforts may gain traction in the future and start taking away some major market share. If employers get solid performance from their employees who have gone this route…higher ed better look out. 

Microsoft/LinkedIn/Lynda.com are nicely positioned to be a major player who can offer society a next generation learning platform at an incredible price — offering up-to-date, microlearning along with new forms of credentialing. It’s what I’ve been calling the Amazon.com of higher ed (previously the Walmart of Education) for ~10 years. It will take place in a strategy/platform similar to this one.

 



Also, this is what a guerilla on the back looks like:

 

This is what a guerilla on the back looks like!

 



Also see:

  • Meet the 83-Year-Old App Developer Who Says Edtech Should Better Support Seniors — from edsurge.com by Sydney Johnson
    Excerpt (emphasis DSC):
    Now at age 83, Wakamiya beams with excitement when she recounts her journey, which has been featured in news outlets and even at Apple’s developer conference last year. But through learning how to code, she believes that experience offers an even more important lesson to today’s education and technology companies: don’t forget about senior citizens.Today’s education technology products overwhelmingly target young people. And while there’s a growing industry around serving adult learners in higher education, companies largely neglect to consider the needs of the elderly.

 

 

From DSC:
I have often reflected on differentiation or what some call personalized learning and/or customized learning. How does a busy teacher, instructor, professor, or trainer achieve this, realistically?

It’s very difficult and time-consuming to do for sure. But it also requires a team of specialists to achieve such a holy grail of learning — as one person can’t know it all. That is, one educator doesn’t have the necessary time, skills, or knowledge to address so many different learning needs and levels!

  • Think of different cognitive capabilities — from students that have special learning needs and challenges to gifted students
  • Or learners that have different physical capabilities or restrictions
  • Or learners that have different backgrounds and/or levels of prior knowledge
  • Etc., etc., etc.

Educators  and trainers have so many things on their plates that it’s very difficult to come up with _X_ lesson plans/agendas/personalized approaches, etc.  On the other side of the table, how do students from a vast array of backgrounds and cognitive skill levels get the main points of a chapter or piece of text? How can they self-select the level of difficulty and/or start at a “basics” level and work one’s way up to harder/more detailed levels if they can cognitively handle that level of detail/complexity? Conversely, how do I as a learner get the boiled down version of a piece of text?

Well… just as with the flipped classroom approach, I’d like to suggest that we flip things a bit and enlist teams of specialists at the publishers to fulfill this need. Move things to the content creation end — not so much at the delivery end of things. Publishers’ teams could play a significant, hugely helpful role in providing customized learning to learners.

Some of the ways that this could happen:

Use an HTML like language when writing a textbook, such as:

<MainPoint> The text for the main point here. </MainPoint>

<SubPoint1>The text for the subpoint 1 here.</SubPoint1>

<DetailsSubPoint1>More detailed information for subpoint 1 here.</DetailsSubPoint1>

<SubPoint2>The text for the subpoint 2 here.</SubPoint2>

<DetailsSubPoint2>More detailed information for subpoint 2 here.</DetailsSubPoint2>

<SubPoint3>The text for the subpoint 3 here.</SubPoint3>

<DetailsSubPoint3>More detailed information for subpoint 3 here.</DetailsSubPoint1>

<SummaryOfMainPoints>A list of the main points that a learner should walk away with.</SummaryOfMainPoints>

<BasicsOfMainPoints>Here is a listing of the main points, but put in alternative words and more basic ways of expressing those main points. </BasicsOfMainPoints>

<Conclusion> The text for the concluding comments here.</Conclusion>

 

<BasicsOfMainPoints> could be called <AlternativeExplanations>
Bottom line: This tag would be to put things forth using very straightforward terms.

Another tag would be to address how this topic/chapter is relevant:
<RealWorldApplication>This short paragraph should illustrate real world examples

of this particular topic. Why does this topic matter? How is it relevant?</RealWorldApplication>

 

On the students’ end, they could use an app that works with such tags to allow a learner to quickly see/review the different layers. That is:

  • Show me just the main points
  • Then add on the sub points
  • Then fill in the details
    OR
  • Just give me the basics via an alternative ways of expressing these things. I won’t remember all the details. Put things using easy-to-understand wording/ideas.

 

It’s like the layers of a Microsoft HoloLens app of the human anatomy:

 

Or it’s like different layers of a chapter of a “textbook” — so a learner could quickly collapse/expand the text as needed:

 

This approach could be helpful at all kinds of learning levels. For example, it could be very helpful for law school students to obtain outlines for cases or for chapters of information. Similarly, it could be helpful for dental or medical school students to get the main points as well as detailed information.

Also, as Artificial Intelligence (AI) grows, the system could check a learner’s cloud-based learner profile to see their reading level or prior knowledge, any IEP’s on file, their learning preferences (audio, video, animations, etc.), etc. to further provide a personalized/customized learning experience. 

To recap:

  • “Textbooks” continue to be created by teams of specialists, but add specialists with knowledge of students with special needs as well as for gifted students. For example, a team could have experts within the field of Special Education to help create one of the overlays/or filters/lenses — i.e., to reword things. If the text was talking about how to hit a backhand or a forehand, the alternative text layer could be summed up to say that tennis is a sport…and that a sport is something people play. On the other end of the spectrum, the text could dive deeply into the various grips a person could use to hit a forehand or backhand.
  • This puts the power of offering differentiation at the point of content creation/development (differentiation could also be provided for at the delivery end, but again, time and expertise are likely not going to be there)
  • Publishers create “overlays” or various layers that can be turned on or off by the learners
  • Can see whole chapters or can see main ideas, topic sentences, and/or details. Like HTML tags for web pages.
  • Can instantly collapse chapters to main ideas/outlines.

 

 

The global companies that failed to adapt to change. — from trainingmag.com by Professor M.S. Rao, Ph.D.

Excerpt:

Eastman Kodak, a leader for many years, filed for bankruptcy in 2012. Blockbuster Video became defunct in 2013. Similarly, Borders — one of the largest book retailers in the U.S. — went out of business in 2011. Why did these companies, which once had great brands, ultimately fail? It is because they failed to adapt to change. Additionally, they failed to unlearn and relearn.

Former GE CEO Jack Welch once remarked, “If the rate of change on the outside exceeds the rate of change on the inside, the end is near.” Thus, accept change before the change is thrust on you.

Leaders must adopt tools and techniques to adapt to change. Here is a blueprint to embrace change effectively:

  • Keep the vision right and straight, and articulate it effectively.
  • Create organizational culture conducive to bring about change.
  • Communicate clearly about the need to change.
  • Enlighten people about the implications of the status quo.
  • Show them benefits once the change is implemented.
  • Coordinate all stakeholders effectively.
  • Remove the roadblocks by allaying their apprehensions.
  • Show them small gains to ensure that entire change takes place smoothly without any resistance.

 

From DSC:
Though I’m not on board with all of the perspectives in that article, institutions of traditional higher education likely have something to learn from the failures of these companies….while there’s still time to change and to innovate. 

 

 

Affordable and at-scale — from insidehighered.com by Ray Schroeder
Affordable degrees at scale have arrived. The momentum behind this movement is undeniable, and its impact will be significant, Ray Schroeder writes.

Excerpt (emphasis DSC):

How many times have we been told that major change in our field is on the near horizon? Too many times, indeed.

The promises of technologies and practices have fallen short more often than not. Just seven years ago, I was part of the early MOOC movement and felt the pulsating potential of teaching thousands of students around the world in a single class. The “year of the MOOC” was declared in 2012. Three years later, skeptics declared that the MOOC had died an ignominious death with high “failure” rates and relatively little recognition by employers.

However, the skeptics were too impatient, misunderstood the nature of MOOCs and lacked the vision of those at Georgia Tech, the University of Illinois, Arizona State University, Coursera, edX and scores of other institutions that have persevered in building upon MOOCs’ premises to develop high-quality, affordable courses, certificates and now, degrees at scale.

No, these degrees are not free, but they are less than half the cost of on-campus versions. No, they are not massive in the hundreds of thousands, but they are certainly at large scale with many thousands enrolled. In computer science, the success is felt across the country.

 

Georgia Tech alone has enrolled 10,000 students over all in its online master’s program and is adding thousands of new students each semester in a top 10-ranked degree program costing less than $7,000. Georgia Tech broke the new ground through building collaborations among several partners. Yet, that was just the beginning, and many leading universities have followed.

 

 

Also see:

Trends for the future of education with Jeff Selingo — from steelcase.com
How the future of work and new technology will make place more important than ever.

Excerpt:

Selingo sees artificial intelligence and big data as game changers for higher education. He says AI can free up professors and advisors to spend more time with students by answering some more frequently-asked questions and handling some of the grading. He also says data can help us track and predict student performance to help them create better outcomes. “When they come in as a first-year student, we can say ‘People who came in like you that had similar high school grades and took similar classes ended up here. So, if you want to get out of here in four years and have a successful career, here are the different pathways you should follow.’”

 

 

 

Academics Propose a ‘Blockchain University,’ Where Faculty (and Algorithms) Rule — from edsurge.com by Jeff Young

Excerpt:

A group of academics affiliated with Oxford University have proposed a new model of higher education that replaces traditional administrators with “smart contracts” on the blockchain, the same technology that drives Bitcoin and other cryptocurrencies.

“Our aim is to create a university in which the bulk of administrative tasks are either eliminated or progressively automated,” said the effort’s founders in a white paper released earlier this year. Those proposing the idea added the university would be “a decentralised, non-profit, democratic community in which the use of blockchain technology will provide the contractual stability needed to pursue a full course of study.”

Experiments with blockchain in higher education are underway at multiple campuses around the country, and many of researchers are looking into how to use the technology to verify and deliver credentials. Massachusetts Institute for Technology, for example, began issuing diplomas via blockchain last year.

The plan by Oxford researchers goes beyond digital diplomas—and beyond many typical proposals to disrupt education in general. It argues for a completely new framework for how college is organized, how professors are paid, and how students connect with learning. In other words, it’s a long shot.

But even if the proposed platform never emerges, it is likely to spur debates about whether blockchain technology could one day allow professors to reclaim greater control of how higher education operates through digital contracts.

 

The platform would essentially allow professors to organize their own colleges, and teach and take payments from students directly. “

 

 

 

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