These news anchors are professional and efficient. They’re also not human. — from washingtonpost.com by Taylor Telford

Excerpt:

The new anchors at China’s state-run news agency have perfect hair and no pulse.

Xinhua News just unveiled what it is calling the world’s first news anchors powered by artificial intelligence, at the World Internet Conference on Wednesday in China’s Zhejiang province. From the outside, they are almost indistinguishable from their human counterparts, crisp-suited and even-keeled. Although Xinhua says the anchors have the “voice, facial expressions and actions of a real person,” the robotic anchors relay whatever text is fed to them in stilted speech that sounds less human than Siri or Alexa.

 

From DSC:
The question is…is this what we want our future to look like? Personally, I don’t care to watch a robotic newscaster giving me the latest “death and dying report.” It comes off bad enough — callous enough — from human beings backed up by TV networks/stations that have agendas of their own; let alone from a robot run by AI.

 

 

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.

 

 

Top Trends in Active and Collaborative Learning — from thesextantgroup.com by Joe Hammett

Excerpts:

My daughter is a maker. She spends hours tinkering with sewing machines and slime recipes, building salamander habitats and the like. She hangs out with her school friends inside apps that teach math and problem solving through multi-player games. All the while, they are learning to communicate and collaborate in ways that are completely foreign to their grandparent’s generation. She is 10 years old and represents a shift in human cognitive processing brought about by the mastery of technology from a very young age. Her generation and those that come after have never known a time without technology. Personal devices have changed the shared human experience and there is no turning back.

The spaces in which this new human chooses to occupy must cater to their style of existence. They see every display as interactive and are growing up knowing that the entirety of human knowledge is available to them by simply asking Alexa. The 3D printer is a familiar concept and space travel for pleasure will be the norm when they have children of their own.

Current trends in active and collaborative learning are evolving alongside these young minds and when appropriately implemented, enable experiential learning and creative encounters that are changing the very nature of the learning process. Attention to the spaces that will support the educators is also paramount to this success. Lesson plans and teaching style must flip with the classroom. The learning space is just a room without the educator and their content.

 


8. Flexible and Reconfigurable
With floor space at a premium, classrooms need to be able to adapt to a multitude of uses and pedagogies. Flexible furniture will allow the individual instructor freedom to set up the space as needed for their intended activities without impacting the next person to use the room. Construction material choices are key to achieving an easily reconfigurable space. Raised floors and individually controllable lighting fixtures allow a room to go from lecture to group work with ease. Whiteboard paints and rail mounting systems make walls reconfigurable too!.

Active Learning, Flipped Classroom, SCALE-UP, TEAL Classroom, whatever label you choose to place before it, the classroom, learning spaces of all sorts, are changing. The occupants of these spaces demand that they are able to effectively, and comfortably, share ideas and collaborate on projects with their counterparts both in person and in the ether. A global shift is happening in the way humans share ideas. Disruptive technology, on a level not seen since the assembly line, is driving a change in the way humans interact with other humans. The future is collaborative.

 

 

 

Robots won’t replace instructors, 2 Penn State educators argue. Instead, they’ll help them be ‘more human.’ — from edsurge.com by Tina Nazerian

Excerpt:

Specifically, it will help them prepare for and teach their courses through several phases—ideation, design, assessment, facilitation, reflection and research. The two described a few prototypes they’ve built to show what that might look like.

 

Also see:

The future of education: Online, free, and with AI teachers? — from fool.com by Simon Erickson
Duolingo is using artificial intelligence to teach 300 million people a foreign language for free. Will this be the future of education?

Excerpts:

While it might not get a lot of investor attention, education is actually one of America’s largest markets.

The U.S. has 20 million undergraduates enrolled in colleges and universities right now and another 3 million enrolled in graduate programs. Those undergrads paid an average of $17,237 for tuition, room, and board at public institutions in the 2016-17 school year and $44,551 for private institutions. Graduate education varies widely by area of focus, but the average amount paid for tuition alone was $24,812 last year.

Add all of those up, and America’s students are paying more than half a trillion dollars each year for their education! And that doesn’t even include the interest amassed for student loans, the college-branded merchandise, or all the money spent on beer and coffee.

Keeping the costs down
Several companies are trying to find ways to make college more affordable and accessible.

 

But after we launched, we have so many users that nowadays if the system wants to figure out whether it should teach plurals before adjectives or adjectives before plurals, it just runs a test with about 50,000 people. So for the next 50,000 people that sign up, which takes about six hours for 50,000 new users to come to Duolingo, to half of them it teaches plurals before adjectives. To the other half it teaches adjectives before plurals. And then it measures which ones learn better. And so once and for all it can figure out, ah it turns out for this particular language to teach plurals before adjectives for example.

So every week the system is improving. It’s making itself better at teaching by learning from our learners. So it’s doing that just based on huge amounts of data. And this is why it’s become so successful I think at teaching and why we have so many users.

 

 

From DSC:
I see AI helping learners, instructors, teachers, and trainers. I see AI being a tool to help do some of the heavy lifting, but people still like to learn with other people…with actual human beings. That said, a next generation learning platform could be far more responsive than what today’s traditional institutions of higher education are delivering.

 

 

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.’”

 

 

 

Can a culture of change improve innovation? — from washingtonpost.com by Jim Whitehurst, president and chief executive officer, Red Hat

Excerpts:

Plenty of executives lay awake at night wondering how they can keep up with the waves of digital disruption that continue to shake every industry out there. Everyone wants to know how they can get their organization to innovate better and faster.

But this is more than a technology problem. Businesses can’t simply buy a solution off the shelf. Instead, leaders need to encourage people to think and act differently. And to do that, they need to rethink the way they organize to get work done.

But the pace of digital transformation today has made Industrial Era thinking and planning obsolete when it comes to overcoming the challenges an organization faces.

 

Automation requires processes to change; digital transformation requires people to change.

We’re talking about building an organizational culture that embraces innovative thinking and behaviors. But you can’t change culture overnight, because it’s an output, not an input.

 

1. Planning must be replaced by configuring for constant change…

2. Prescription must be replaced by enablement…

3. Execution must be replaced by engagement…

 

Organizations today need to spend less time charting long-term courses and more time fostering teams configured to respond effectively to constant change.

 

From DSC:
That last quote reminds me of the need for more TrimTab Groups within higher education:

 

 

 

 

 

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. “

 

 

 

Gartner: Immersive experiences among top tech trends for 2019 — from campustechnology.com by Dian Schaffhauser

Excerpt:

IT analyst firm Gartner has named its top 10 trends for 2019, and the “immersive user experience” is on the list, alongside blockchain, quantum computing and seven other drivers influencing how we interact with the world. The annual trend list covers breakout tech with broad impact and tech that could reach a tipping point in the near future.

 

 

 

 

In the 2030 and beyond world, employers will no longer be a separate entity from the education establishment. Pressures from both the supply and demand side are so large that employers and learners will end up, by default, co-designing new learning experiences, where all learning counts.

 

OBJECTIVES FOR CONVENINGS

  • Identify the skills everyone will need to navigate the changing relationship between machine intelligence and people over the next 10-12 years.
  • Develop implications for work, workers, students, working learners, employers, and policymakers.
  • Identify a preliminary set of actions that need to be taken now to best prepare for the changing work + learn ecosystem.

Three key questions guided the discussions:

  1. What are the LEAST and MOST essential skills needed for the future?
  2. Where and how will tomorrow’s workers and learners acquire the skills they really need?
  3. Who is accountable for making sure individuals can thrive in this new economy?

This report summarizes the experts’ views on what skills will likely be needed to navigate the work + learn ecosystem over the next 10–15 years—and their suggested steps for better serving the nation’s future needs.

 

In a new world of work, driven especially by AI, institutionally-sanctioned curricula could give way to AI-personalized learning. This would drastically change the nature of existing social contracts between employers and employees, teachers and students, and governments and citizens. Traditional social contracts would need to be renegotiated or revamped entirely. In the process, institutional assessment and evaluation could well shift from top-down to new bottom-up tools and processes for developing capacities, valuing skills, and managing performance through new kinds of reputation or accomplishment scores.

 

In October 2017, Chris Wanstrath, CEO of Github, the foremost code-sharing and social networking resource for programmers today, made a bold statement: “The future of coding is no coding at all.” He believes that the writing of code will be automated in the near future, leaving humans to focus on “higher-level strategy and design of software.” Many of the experts at the convenings agreed. Even creating the AI systems of tomorrow, they asserted, will likely require less human coding than is needed today, with graphic interfaces turning AI programming into a drag-and-drop operation.

Digital fluency does not mean knowing coding languages. Experts at both convenings contended that effectively “befriending the machine” will be less about teaching people to code and more about being able to empathize with AIs and machines, understanding how they “see the world” and “think” and “make decisions.” Machines will create languages to talk to one another.

Here’s a list of many skills the experts do not expect to see much of—if at all—in the future:

  • Coding. Systems will be self-programming.
  • Building AI systems. Graphic interfaces will turn AI programming into drag-and-drop operations.
  • Calendaring, scheduling, and organizing. There won’t be need for email triage.
  • Planning and even decision-making. AI assistants will pick this up.
  • Creating more personalized curricula. Learners may design more of their own personalized learning adventure.
  • Writing and reviewing resumes. Digital portfolios, personal branding, and performance reputation will replace resumes.
  • Language translation and localization. This will happen in real time using translator apps.
  • Legal research and writing. Many of our legal systems will be automated.
  • Validation skills. Machines will check people’s work to validate their skills.
  • Driving. Driverless vehicles will replace the need to learn how to drive.

Here’s a list of the most essential skills needed for the future:

  • Quantitative and algorithmic thinking.  
  • Managing reputation.  
  • Storytelling and interpretive skills.  
  • First principles thinking.  
  • Communicating with machines as machines.  
  • Augmenting high-skilled physical tasks with AI.
  • Optimization and debugging frame of mind.
  • Creativity and growth mindset.
  • Adaptability.
  • Emotional intelligence.
  • Truth seeking.
  • Cybersecurity.

 

The rise of machine intelligence is just one of the many powerful social, technological, economic, environmental, and political forces that are rapidly and disruptively changing the way everyone will work and learn in the future. Because this largely tech-driven force is so interconnected with other drivers of change, it is nearly impossible to understand the impact of intelligent agents on how we will work and learn without also imagining the ways in which these new tools will reshape how we live.

 

 

 

What will be important in the learn and work ecosystem in 2030? How do we prepare? — from evolllution.com by Holly Zanville | Senior Advisor for Credentialing and Workforce Development, Lumina Foundation

Excerpt:

These seven suggested actions—common to all scenarios—especially resonated with Lumina:

  1. Focus on learning: All learners will need a range of competencies and skills, most critically: learning how to learn; having a foundation in math, science, IT and cross-disciplines; and developing the behaviors of grit, empathy and effective communication.
  2. Prepare all “systems”: Schools will continue to be important places to teach competencies and skills. Parents will be important teachers for children. Workplaces will also be important places for learning, and many learners will need instruction on how to work effectively as part of human/machine teams.
  3. Integrate education and work: Education systems will need to be integrated with work in an education/work ecosystem. To enable movement within the ecosystem, credentials will be useful, but only if they are transparent and portable. The competencies and skills that stand behind credentials will need to be identifiable, using a common language to enable (a) credential providers to educate/train for an integrated education/work system; (b) employers to hire people and upgrade their skills; and (c) governments (federal/state/local) to incentivize and regulate programs and policies that support the education/work system.
  4. Assess learning: Assessing competencies and skills acquired in multiple settings and modes (including artificial reality and virtual reality tools), will be essential. AI will enable powerful new assessment tools to collect and analyze data about what humans know and can do.
  5. Build fair, moral AI: There will be a high priority on ensuring that AI has built-in checks and balances that reflect moral values and honor different cultural perspectives.
  6. Prepare for human/machine futures: Machines will join humans in homes, schools and workplaces. Machines will likely be viewed as citizens with rights. Humans must prepare for side-by-side “relationships” with machines, especially in situations in which machines will be managing aspects of education, work and life formerly managed by humans. Major questions will also arise about the ownership of AI structures—what ownership looks like, and who profits from ubiquitous AI structures.
  7. Build networks for readiness/innovation: Open and innovative partnerships will be needed for whatever future scenarios emerge. In a data-rich world, we won’t solve problems alone; networks, partnerships and communities will be key.

 

 

Also see:

 

 

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