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.

 

 

Introducing several new ideas to provide personalized, customized learning experiences for all kinds of learners! [Christian]

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.

 

 

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.

 

 

Reflections on “Inside Amazon’s artificial intelligence flywheel” [Levy]

Inside Amazon’s artificial intelligence flywheel — from wired.com by Steven Levy
How deep learning came to power Alexa, Amazon Web Services, and nearly every other division of the company.

Excerpt (emphasis DSC):

Amazon loves to use the word flywheel to describe how various parts of its massive business work as a single perpetual motion machine. It now has a powerful AI flywheel, where machine-learning innovations in one part of the company fuel the efforts of other teams, who in turn can build products or offer services to affect other groups, or even the company at large. Offering its machine-learning platforms to outsiders as a paid service makes the effort itself profitable—and in certain cases scoops up yet more data to level up the technology even more.

It took a lot of six-pagers to transform Amazon from a deep-learning wannabe into a formidable power. The results of this transformation can be seen throughout the company—including in a recommendations system that now runs on a totally new machine-learning infrastructure. Amazon is smarter in suggesting what you should read next, what items you should add to your shopping list, and what movie you might want to watch tonight. And this year Thirumalai started a new job, heading Amazon search, where he intends to use deep learning in every aspect of the service.

“If you asked me seven or eight years ago how big a force Amazon was in AI, I would have said, ‘They aren’t,’” says Pedro Domingos, a top computer science professor at the University of Washington. “But they have really come on aggressively. Now they are becoming a force.”

Maybe the force.

 

 

From DSC:
When will we begin to see more mainstream recommendation engines for learning-based materials? With the demand for people to reinvent themselves, such a next generation learning platform can’t come soon enough!

  • Turning over control to learners to create/enhance their own web-based learner profiles; and allowing people to say who can access their learning profiles.
  • AI-based recommendation engines to help people identify curated, effective digital playlists for what they want to learn about.
  • Voice-driven interfaces.
  • Matching employees to employers.
  • Matching one’s learning preferences (not styles) with the content being presented as one piece of a personalized learning experience.
  • From cradle to grave. Lifelong learning.
  • Multimedia-based, interactive content.
  • Asynchronously and synchronously connecting with others learning about the same content.
  • Online-based tutoring/assistance; remote assistance.
  • Reinvent. Staying relevant. Surviving.
  • Competency-based learning.

 

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

 

 

 

 

 

 

 

We’re about to embark on a period in American history where career reinvention will be critical, perhaps more so than it’s ever been before. In the next decade, as many as 50 million American workers—a third of the total—will need to change careers, according to McKinsey Global Institute. Automation, in the form of AI (artificial intelligence) and RPA (robotic process automation), is the primary driver. McKinsey observes: “There are few precedents in which societies have successfully retrained such large numbers of people.”

Bill Triant and Ryan Craig

 

 

 

Also relevant/see:

Online education’s expansion continues in higher ed with a focus on tech skills — from educationdive.com by James Paterson

Dive Brief:

  • Online learning continues to expand in higher ed with the addition of several online master’s degrees and a new for-profit college that offers a hybrid of vocational training and liberal arts curriculum online.
  • Inside Higher Ed reported the nonprofit learning provider edX is offering nine master’s degrees through five U.S. universities — the Georgia Institute of Technology, the University of Texas at Austin, Indiana University, Arizona State University and the University of California, San Diego. The programs include cybersecurity, data science, analytics, computer science and marketing, and they cost from around $10,000 to $22,000. Most offer stackable certificates, helping students who change their educational trajectory.
  • Former Harvard University Dean of Social Science Stephen Kosslyn, meanwhile, will open Foundry College in January. The for-profit, two-year program targets adult learners who want to upskill, and it includes training in soft skills such as critical thinking and problem solving. Students will pay about $1,000 per course, though the college is waiving tuition for its first cohort.

 

 

 

 

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.

 

 

 

NEW: The Top Tools for Learning 2018 [Jane Hart]

The Top Tools for Learning 2018 from the 12th Annual Digital Learning Tools Survey -- by Jane Hart

 

The above was from Jane’s posting 10 Trends for Digital Learning in 2018 — from modernworkplacelearning.com by Jane Hart

Excerpt:

[On 9/24/18],  I released the Top Tools for Learning 2018 , which I compiled from the results of the 12th Annual Digital Learning Tools Survey.

I have also categorised the tools into 30 different areas, and produced 3 sub-lists that provide some context to how the tools are being used:

  • Top 100 Tools for Personal & Professional Learning 2018 (PPL100): the digital tools used by individuals for their own self-improvement, learning and development – both inside and outside the workplace.
  • Top 100 Tools for Workplace Learning (WPL100): the digital tools used to design, deliver, enable and/or support learning in the workplace.
  • Top 100 Tools for Education (EDU100): the digital tools used by educators and students in schools, colleges, universities, adult education etc.

 

3 – Web courses are increasing in popularity.
Although Coursera is still the most popular web course platform, there are, in fact, now 12 web course platforms on the list. New additions this year include Udacity and Highbrow (the latter provides daily micro-lessons). It is clear that people like these platforms because they can chose what they want to study as well as how they want to study, ie. they can dip in and out if they want to and no-one is going to tell them off – which is unlike most corporate online courses which have a prescribed path through them and their use is heavily monitored.

 

 

5 – Learning at work is becoming personal and continuous.
The most significant feature of the list this year is the huge leap up the list that Degreed has made – up 86 places to 47th place – the biggest increase by any tool this year. Degreed is a lifelong learning platform and provides the opportunity for individuals to own their expertise and development through a continuous learning approach. And, interestingly, Degreed appears both on the PPL100 (at  30) and WPL100 (at 52). This suggests that some organisations are beginning to see the importance of personal, continuous learning at work. Indeed, another platform that underpins this, has also moved up the list significantly this year, too. Anders Pink is a smart curation platform available for both individuals and teams which delivers daily curated resources on specified topics. Non-traditional learning platforms are therefore coming to the forefront, as the next point further shows.

 

 

From DSC:
Perhaps some foreshadowing of the presence of a powerful, online-based, next generation learning platform…?

 

 

 

Coursera’s CEO on the Evolving Meaning of ‘MOOC’ — from by Dian Schaffhauser
When you can bring huge numbers of students together with lots of well-branded universities and global enterprises seeking a highly skilled workforce, could those linkages be strong enough to forge a new future for massive open online courses?

Excerpts:

Campus Technology: Coursera used to be a MOOC operator, but now it’s a tech company, an LMS company, a virtual bootcamp and more. So how are you describing Coursera these days?

Maggioncalda: As a learning platform. We like to say to our universities, “Coursera is a platform for your global campus.”

You have [traditional universities] teaching with some of the world’s best professors, with some of the most cutting-edge research, to a population of people who have sat right here in front of you, on a small parcel of land, and who pay a lot of money to do that. It’s been very high quality that’s been available to the very few.

What we’re interested in doing is taking that quality of education and making it available to a vast group of people. When you think about our business model, I like to think about it as an ecosystem of learners, educators and employers. What we do is we link them together. We have 34 million learners from around the world. Our biggest country represented is the United States, followed by India, followed by China, followed by Mexico, followed by Brazil. A lot of the emerging markets and the learners there are coming to Coursera to learn and prosper.

[Editor’s note: Coursera currently hosts 10 online degree programs. And most recently, in July 2018, the University of Pennsylvania announced that it was launching its first fully online master’s degree, delivered through Coursera and priced at about a third of the cost of its on-campus equivalent.]

CT: Let’s talk about the University of Pennsylvania deal. Do you think that’s going to put some competitive pressure on the other Tier 1 schools to jump into the fray?

Maggioncalda: This is a very well-regarded program. The University of Pennsylvania is a very well-regarded university. I think it’s causing a lot of people to re-evaluate what they were imagining their future might look like: Maybe learners really do want to have access that’s more convenient and lower cost and they don’t have to quit their jobs to take. And maybe there is literally a world of learners who can’t come to campus, in India and Europe and Latin America and Russia and Asia Pacific and China.

 

 

As a learning platform. We like to say to our universities, “Coursera is a platform for your global campus.”

Jeff Maggioncalda, Coursera CEO

 

 

In two years we’ve had over 1,400 companies hire Coursera to deliver university courses at work to their employees.

Now we’re starting to link the 34 million learners out there to the employers who are looking for people who have certain skills, saying, “Look, if you’re on Coursera learning about this thing, there might be companies who want to hire people that know the thing that you just learned.”

Jeff Maggioncalda, Coursera CEO

 

 


 

The Living [Class] Room -- by Daniel Christian -- July 2012

Learning from the Living [Class] Room:
A global, powerful, next generation learning platform — meant to help people
reinvent themselves quickly, cost-effectively, conveniently, & consistently

  • A new, global, collaborative learning platform that offers more choice, more control to learners of all ages – 24×7 – and could become the organization that futurist Thomas Frey discusses here with Business Insider:
    • “I’ve been predicting that by 2030 the largest company on the internet is going to be an education-based company that we haven’t heard of yet,” Frey, the senior futurist at the DaVinci Institute think tank, tells Business Insider.
  • A learner-centered platform that is enabled by – and reliant upon – human beings but is backed up by a powerful suite of technologies that work together in order to help people reinvent themselves quickly, conveniently, and extremely cost-effectively
  • A customizable learning environment that will offer up-to-date streams of regularly curated content (i.e., microlearning) as well as engaging learning experiences
  • Along these lines, a lifelong learner can opt to receive an RSS feed on a particular topic until they master that concept; periodic quizzes (i.e., spaced repetition) determine that mastery. Once mastered, the system will ask the learner as to whether they still want to receive that particular stream of content or not.
  • A Netflix-like interface to peruse and select plugins to extend the functionality of the core product
  • An AI-backed system of analyzing employment trends and opportunities will highlight those courses and “streams of content” that will help someone obtain the most in-demand skills
  • A system that tracks learning and, via Blockchain-based technologies, feeds all completed learning modules/courses into learners’ web-based learner profiles
  • A learning platform that provides customized, personalized recommendation lists – based upon the learner’s goals
  • A platform that delivers customized, personalized learning within a self-directed course (meant for those content creators who want to deliver more sophisticated courses/modules while moving people through the relevant Zones of Proximal Development)
  • Notifications and/or inspirational quotes will be available upon request to help provide motivation, encouragement, and accountability – helping learners establish habits of continual, lifelong-based learning
  • (Potentially) An online-based marketplace, matching learners with teachers, professors, and other such Subject Matter Experts (SMEs)
  • (Potentially) Direct access to popular job search sites
  • (Potentially) Direct access to resources that describe what other companies do/provide and descriptions of any particular company’s culture (as described by current and former employees and freelancers)
  • (Potentially) Integration with one-on-one tutoring services

 


 

 

Smart Machines & Human Expertise: Challenges for Higher Education — from er.educause.edu by Diana Oblinger

Excerpts:

What does this mean for higher education? One answer is that AI, robotics, and analytics become disciplines in themselves. They are emerging as majors, minors, areas of emphasis, certificate programs, and courses in many colleges and universities. But smart machines will catalyze even bigger changes in higher education. Consider the implications in three areas: data; the new division of labor; and ethics.

 

Colleges and universities are challenged to move beyond the use of technology to deliver education. Higher education leaders must consider how AI, big data, analytics, robotics, and wide-scale collaboration might change the substance of education.

 

Higher education leaders should ask questions such as the following:

  • What place does data have in our courses?
  • Do students have the appropriate mix of mathematics, statistics, and coding to understand how data is manipulated and how algorithms work?
  • Should students be required to become “data literate” (i.e., able to effectively use and critically evaluate data and its sources)?

Higher education leaders should ask questions such as the following:

  • How might problem-solving and discovery change with AI?
  • How do we optimize the division of labor and best allocate tasks between humans and machines?
  • What role do collaborative platforms and collective intelligence have in how we develop and deploy expertise?


Higher education leaders should ask questions such as the following:

  • Even though something is possible, does that mean it is morally responsible?
  • How do we achieve a balance between technological possibilities and policies that enable—or stifle—their use?
  • An algorithm may represent a “trade secret,” but it might also reinforce dangerous assumptions or result in unconscious bias. What kind of transparency should we strive for in the use of algorithms?

 

 

 

Experiences in self-determined learning — a free download/PDF file from uni-oldenburg.de by Lisa Blaschke, Chris Kenyon, & Stewart Hase (Eds.)

Excerpts (emphasis DSC):

An Introduction to Self-Determined Learning (Heutagogy)

Summary
There is a good deal that is provocative in the theory and principles surrounding self-determined learning or heutagogy. So, it seems appropriate to start off with a, hopefully, eyebrow-raising observation. One of the key ideas underpinning self-determined learning is that learning, and educational and training are quite different things. Humans are born to learn and are very good at it. Learning is a natural capability and it occurs across the human lifespan, from birth to last breath. In contrast, educational and training systems are concerned with the production of useful citizens, who can contribute to the collective economic good. Education and training is largely a conservative enterprise that is highly controlled, is product focused, where change is slow, and the status quo is revered. Learning, however, is a dynamic process intrinsic to the learner, uncontrolled except by the learner’s mental processes. Self-determined learning is concerned with understanding how people learn best and how the methods derived from this understanding can be applied to educational systems. This chapter provides a relatively brief introduction of the origins, the key principles, and the practice of self-determined learning. It also provides a number of resources to enable the interested reader to take learning about the approach further.

Contributors to this book come from around the world: they are everyday practitioners of self-determined learning who have embraced the approach. In doing so, they have chosen the path less taken and set off on a journey of exploration and discovery – a new frontier – as they implement heutagogy in their homes, schools, and workplaces. Each chapter was written with the intent of sharing the experiences of practical applications of heutagogy, while also encouraging those just starting out on the journey in using self-determined learning. The authors in this book are your guides as you move forward and share with you the lessons they have learned along the way. These shared experiences are meant to be read – or dabbled in – in any way that you want to read them. There is no fixed recipe or procedure for tackling the book contents.

At the heart of self-determined learning is that the learner is at the centre of the learning process. Learning is intrinsic to the learner, and the educator is but an agent, as are many of the resources so freely available these days. It is now so easy to access knowledge and skills (competencies), and in informal settings we do this all the time, and we do it well. Learning is complex and non-linear, despite what the curricula might try to dictate. In addition, every brain is different as a result of its experience (as brain research tells us). Each brain will also change as learning takes place with new hypotheses, new needs, and new questions forming, as new neuronal connections are created.

Heutagogy also doesn’t have anything directly to do with self-determination theory (SDT). SDT is a theory of motivation related to acting in healthy and effective ways (Ryan & Deci, 2000). However, heutagogy is related to the philosophical notion of self-determinism and shares a common belief in the role of human agency in behavior.

The idea of human agency is critical to self-determined learning, where learning is learner-directed. Human agency is the notion that humans have the capacity to make choices and decisions, and then act on them in the real world. However, how experiences and learning bring people to make the choices and decisions that they do make, and what actions they may then take is a very complex matter. What we are concerned with in self-determined learning is that people have agency with respect to how, what, and when they learn. It is something that is intrinsic to each individual person. Learning occurs in the learner’s brain, as the result of his or her past and present experiences.

 

The notion of placing the learner at the centre of the learning experience is a key principle of self-determined learning. This principle is the opposite of teacher-centric or, perhaps more accurately curriculum-centric, approaches to learning. This is not to say that the curriculum is not important, just that it needs to be geared to the learner – flexible, adaptable, and be a living document that is open to change.

Teacher-centric learning is an artifact of the industrial revolution when an education system was designed to meet the needs of the factories (Ackoff & Greenberg, 2008) and to “make the industrial wheel go around” (Hase & Kenyon, 2013b). It is time for a change to learner-centred learning and the time is right with easy access to knowledge and skills through the Internet, high-speed communication and ‘devices’. Education can now focus on more complex cognitive activities geared to the needs of the 21st century learner, rather than have its main focus on competence (Blaschke & Hase, 2014; Hase & Kenyon, 2013a).

 

 

 

What is a learning ecosystem? And how does it support corporate strategy? [Eudy]

What is a learning ecosystem? And how does it support corporate strategy? — from ej4.com by Ryan Eudy

Excerpt:

learning ecosystem is a system of people, content, technology, culture, and strategy, existing both within and outside of an organization, all of which has an impact on both the formal and informal learning that goes on in that organization.

The word “ecosystem” is worth paying attention to here. It’s not just there to make the term sound fancy or scientific. A learning ecosystem is the L&D equivalent of an ecosystem out in the wild. Just as a living ecosystem has many interacting species, environments, and the complex relationships among them, a learning ecosystem has many people and pieces of content, in different roles and learning contexts, and complex relationships.

Just like a living ecosystem, a learning ecosystem can be healthy or sick, nurtured or threatened, self-sustaining or endangered. Achieving your development goals, then, requires an organization to be aware of its own ecosystem, including its parts and the internal and external forces that shape them.

 

From DSC:
Yes, to me, the concept/idea of a learning ecosystem IS important. Very important. So much so, I named this blog after it.

Each of us as individuals have a learning ecosystem, whether we officially recognize it or not. So do the organizations that we work for. And, like an ecosystem out in nature, a learning ecosystem is constantly morphing, constantly changing.

We each have people in our lives that help us learn and grow, and the people that were in our learning ecosystems 10 years ago may or may not still be in our current learning ecosystems. Many of us use technologies and tools to help us learn and grow. Then there are the spaces where we learn — both physical and virtual spaces. Then there are the processes and procedures we follow, formally and/or informally. Any content that helps us learn and grow is a part of that ecosystem. Where we get that content can change, but obtaining up-to-date content is a part of our learning ecosystems. I really appreciate streams of content in this regard — and tapping into blogs/websites, especially via RSS feeds and Feedly (an RSS aggregator that took off when Google Reader left the scene).

The article brings up a good point when it states that a learning ecosystem can be “healthy or sick, nurtured or threatened, self-sustaining or endangered.” That’s why I urge folks to be intentional about maintaining and, better yet, consistently enhancing their learning ecosystems. In this day and age where lifelong learning is now a requirement to remain in the workforce, each of us needs to be intentional in this regard.

 

 

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