Reimagining the Higher Education Ecosystem — from edu2030.agorize.com
How might we empower people to design their own learning journeys so they can lead purposeful and economically stable lives?

Excerpts:

The problem
Technology is rapidly transforming the way we live, learn, and work. Entirely new jobs are emerging as others are lost to automation. People are living longer, yet switching jobs more often. These dramatic shifts call for a reimagining of the way we prepare for work and life—specifically, how we learn new skills and adapt to a changing economic landscape.

The changes ahead are likely to hurt most those who can least afford to manage them: low-income and first generation learners already ill-served by our existing postsecondary education system. Our current system stifles economic mobility and widens income and achievement gaps; we must act now to ensure that we have an educational ecosystem flexible and fair enough to help all people live purposeful and economically stable lives. And if we are to design solutions proportionate to this problem, new technologies must be called on to scale approaches that reach the millions of vulnerable people across the country.

 

The challenge
How might we empower people to design their own learning journeys so they can lead purposeful and economically stable lives?

The Challenge—Reimagining the Higher Education Ecosystem—seeks bold ideas for how our postsecondary education system could be reimagined to foster equity and encourage learner agency and resilience. We seek specific pilots to move us toward a future in which all learners can achieve economic stability and lead purposeful lives. This Challenge invites participants to articulate a vision and then design pilot projects for a future ecosystem that has the following characteristics:

Expands access: The educational system must ensure that all people—including low-income learners who are disproportionately underserved by the current higher education system—can leverage education to live meaningful and economically stable lives.

Draws on a broad postsecondary ecosystem: While college and universities play a vital role in educating students, there is a much larger ecosystem in which students learn. This ecosystem includes non-traditional “classes” or alternative learning providers, such as MOOCs, bootcamps, and online courses as well as on-the-job training and informal learning. Our future learning system must value the learning that happens in many different environments and enable seamless transitions between learning, work, and life.

 

From DSC:
This is where I could see a vision similar to Learning from the Living [Class] Room come into play. It would provide a highly affordable, accessible platform, that would offer more choice, and more control to learners of all ages. It would be available 24×7 and would be a platform that supports lifelong learning. It would combine a variety of AI-enabled functionalities with human expertise, teaching, training, motivation, and creativity.

It could be that what comes out of this challenge will lay the groundwork for a future, massive new learning platform.

 

The Living [Class] Room -- by Daniel Christian -- July 2012 -- a second device used in conjunction with a Smart/Connected TV

 

Also see:

 

 

 

Below are some excerpted slides from her presentation…

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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  • 20 important takeaways for learning world from Mary Meeker’s brilliant tech trends – from donaldclarkplanb.blogspot.com by Donald Clark
    Excerpt:
    Mary Meeker’s slide deck has a reputation of being the Delphic Oracle of tech. But, at 294 slides it’s a lot to take in. Don’t worry, I’ve been through them all. It has tons on economic stuff that is of marginal interest to education and training but there’s plenty to to get our teeth into. We’re not immune to tech trends, indeed we tend to follow in lock-step, just a bit later than everyone else. Among the data are lots of fascinating insights that point the way forward in terms of what we’re likely to be doing over the next decade. So here’s a really quick, top-end summary for folk in the learning game.

 

“Educational content usage online is ramping fast” with over 1 billion daily educational videos watched. There is evidence that use of the Internet for informal and formal learning is taking off.

 

 

 

 

 

 

10 Big Takeaways From Mary Meeker’s Widely-Read Internet Report — from fortune.com by  Leena Rao

 

 

 

 

Skill shift: Automation and the future of the workforce — from mckinsey.com by Jacques Bughin, Eric Hazan, Susan Lund, Peter Dahlström, Anna Wiesinger, and Amresh Subramaniam
Demand for technological, social and emotional, and higher cognitive skills will rise by 2030. How will workers and organizations adapt?

Excerpt:

Skill shifts have accompanied the introduction of new technologies in the workplace since at least the Industrial Revolution, but adoption of automation and artificial intelligence (AI) will mark an acceleration over the shifts of even the recent past. The need for some skills, such as technological as well as social and emotional skills, will rise, even as the demand for others, including physical and manual skills, will fall. These changes will require workers everywhere to deepen their existing skill sets or acquire new ones. Companies, too, will need to rethink how work is organized within their organizations.

This briefing, part of our ongoing research on the impact of technology on the economy, business, and society, quantifies time spent on 25 core workplace skills today and in the future for five European countries—France, Germany, Italy, Spain, and the United Kingdom—and the United States and examines the implications of those shifts.

Topics include:
How will demand for workforce skills change with automation?
Shifting skill requirements in five sectors
How will organizations adapt?
Building the workforce of the future

 

 

Incumbents Strike Back: Insights from the Global C-suite Study — by the IBM Institute for Business Value

Excerpts:

Dancing with disruption
Incumbents hit their stride
We explore the forces at play in shaping the current competitive environment, the opportunities emerging, and how a balance between stability and dynamism favors the Reinventors.

Trust in the journey
The path to personalization
Here we show how the Reinventors as design thinkers are testing their assumptions and re-orienting their organizations to engage their customers and create bonds based on trust.

Orchestrating the future
The pull of platform business models
This section reveals the step change in capability that occurs as organizations scale their partner networks in new ways. We chart how organizations will need to reconsider their value propositions and allocation of resources to own or participate in platforms.

Innovation in motion
Agility for the enterprise
We delineate how leaders are liberating their employees to experiment and innovate, get up close to customers and thrive in an ever-evolving ecosystem of dynamic teams and partnerships.

 

 

 

From DSC:
How do we best help folks impacted by these changes reinvent themselves? And to what? What adjustments to our educational systems do we need to make in order to help people stay marketable and employed?

Given the pace of change and the need for lifelong learning, we need to practice some serious design thinking on our new reality.

 


 

The amount of retail space closing in 2018 is on pace to break a record — from cnbc.com by Lauren Thomas

  • Bon-Ton’s more than 200 stores encompass roughly 24 million square feet.
  • CoStar Group has calculated already more than 90 million square feet of retail space (including Bon-Ton) is set to close in 2018.
  • That’s easily on track to surpass a record 105 million square feet of space shuttered in 2017.

 


 

 

 

Transforming the Postsecondary Professional Education Experience — from by Mary Grush & Thomas Finholt

Excerpt:

So, among other factors currently influencing change, those are the predominate ones. I’ll sum it up this way: The tried-and-true residential model has worked so far, but a number of factors are forcing transformation: emerging technologies, new expectations about when learning will occur in a student’s lifespan, and the introduction of a whole new population of students that had never been imagined before.

Grush: What are your latest efforts or experiments in new professional education offerings that you see as part of this transformation? When did you make a start and what impacts do you see so far?
Finholt: The biggest transformation for us to date has been our entry into the MOOC space. That movement began with a few small trials, but it’s now rapidly expanding and may include, ultimately, full degree offerings. I would describe our period of experimentation with MOOCs to have started in 2013, gaining especially significant momentum in the past two years. Over the next couple of years, our efforts will expand even more dramatically, if we elect to offer fully online degrees. As a measure of the magnitude of impact of MOOCs so far, one of our MOOC specializations in the Python programming language is among the most popular offerings on Coursera — I believe that it has reached more than a million learners at this point. A significant fraction of those learners have opted to sit for an exam to get a certificate in Python programming.

 

 

One is, as announced at the March 6th Coursera meeting, that we have joined in a partnership with Coursera and the University of Michigan’s Office of Academic Innovation to design and get approved, a brand-new online master’s degree in Applied Data Science. 

 

 

 

From DSC:
Mary and Thomas’ solid article reminds me of a graphic I put together a while back:

 

 

 

 

“The process of obtaining postgraduate credentials is becoming something that one works on over the entire span of one’s career… Working professionals will have an array of punctuated intervals, if you will — periods of time when they work intensively to update their credentials.” (source)

 

 

 

 

Students are being prepared for jobs that no longer exist. Here’s how that could change. — from nbcnews.com by Sarah Gonser, The Hechinger Report
As automation disrupts the labor market and good middle-class jobs disappear, schools are struggling to equip students with future-proof skills.

Excerpts:

In many ways, the future of Lowell, once the largest textile manufacturing hub in the United States, is tied to the success of students like Ben Lara. Like many cities across America, Lowell is struggling to find its economic footing as millions of blue-collar jobs in manufacturing, construction and transportation disappear, subject to offshoring and automation.

The jobs that once kept the city prosperous are being replaced by skilled jobs in service sectors such as health care, finance and information technology — positions that require more education than just a high-school diploma, thus squeezing out many of those blue-collar, traditionally middle-class workers.

 

As emerging technologies rapidly and thoroughly transform the workplace, some experts predict that by 2030 400 million to 800 million people worldwide could be displaced and need to find new jobs. The ability to adapt and quickly acquire new skills will become a necessity for survival.

 

 

“We’re preparing kids for these jobs of tomorrow, but we really don’t even know what they are,” said Amy McLeod, the school’s director of curriculum, instruction and assessment. “It’s almost like we’re doing this with blinders on. … We’re doing all we can to give them the finite skills, the computer languages, the programming, but technology is expanding so rapidly, we almost can’t keep up.”

 

 

 

For students like Amber, who would rather do just about anything but go to school, the Pathways program serves another function: It makes learning engaging, maybe even fun, and possibly keeps her in school and on track to graduate.

“I think we’re turning kids off to learning in this country by putting them in rows and giving them multiple-choice tests — the compliance model,” McLeod said. “But my hope is that in the pathways courses, we’re teaching them to love learning. And they’re learning about options in the field — there’s plenty of options for kids to try here.”

 

 

 

From MIT Technology Review on 4-2-2018

*Only* 14 percent of the world has to worry about robots taking their jobs. Yay?
The Organization for Economic Cooperation and Development (OECD) has released a major report analyzing the impact of automation on jobs in 32 countries.

Clashing views: In 2016, the OECD said only 9 percent of US and worldwide jobs face a “high degree of automobility.” That was a contradiction of one of the most widely cited reports on jobs and automation, by Oxford researchers Carl Frey and Michael Osborne, who in 2013 said that 47 percent of US jobs were at high risk of being consumed by automation.

What’s new: The OECD’s latest report says that across the countries analyzed, 14 percent of jobs are highly automatable, meaning they have over a 70 percent likelihood of automation. In the US, the study concludes that 10 percent of jobs will likely be lost to automation. An additional 32 percent of global jobs will be transformed and require significant worker retraining.

The big “but”: As the gap between the OECD report and Frey and Osborne’s estimates illustrate, predictions like these aren’t known for their accuracy. In fact, when we compiled all of the studies we could on the subject, we found there are about as many predictions as there are experts.

 


Also see:



Automation, skills use and training
— from oecd-ilibrary.org by Ljubica Nedelkoska and Glenda Quintini

Excerpts:

Here are the study’s key findings.
Across the 32 countries, close to one in two jobs are likely to be significantly affected by automation, based on the tasks they involve. But the degree of risk varies.

The variance in automatability across countries is large: 33% of all jobs in Slovakia are highly automatable, while this is only the case with 6% of the jobs in Norway.

The cross-country variation in automatability, contrary to expectations, is better explained by the differences in the organisation of job tasks within economic sectors, than by the differences in the sectoral structure of economies.

There are upside and downside risks to the figures obtained in this paper. On the upside, it is important to keep in mind that these estimates refer to technological possibilities, abstracting from the speed of diffusion and likelihood of adoption of such technologies….But there are risks on the downside too. First, the estimates are based on the fact that, given the current state of knowledge, tasks related to social intelligence, cognitive intelligence and perception and manipulation cannot be automated. However, progress is being made very rapidly, particularly in the latter two categories.

Most importantly, the risk of automation is not distributed equally among workers. Automation is found to mainly affect jobs in the manufacturing industry and agriculture, although a number of service sectors, such as postal and courier services, land transport and food services are also found to be highly automatable.

Overall, despite recurrent arguments that automation may start to adversely affect selected highly skilled occupations, this prediction is not supported by the Frey and Osborne (2013) framework of engineering bottlenecks used in this study. If anything, Artificial Intelligence puts more low-skilled jobs at risk than previous waves of technological progress…

A striking novel finding is that the risk of automation is the highest among teenage jobs. The relationship between automation and age is U-shaped, but the peak in automatability among youth jobs is far more pronounced than the peak among senior workers.


This unequal distribution of the risk of automation raises the stakes involved in policies to prepare workers for the new job requirements. In this context, adult learning is a crucial policy instrument for the re-training and up-skilling of workers whose jobs are being affected by technology. Unfortunately, evidence from this study suggests that a lot needs to be done to facilitate participation by the groups most affected by automation.

An analysis of German data suggests that training is used to move to jobs at lower risk of automation.

 

 
 

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