Amazon has 10,000 employees dedicated to Alexa — here are some of the areas they’re working on — from businessinsider.com by Avery Hartmans

Summary (emphasis DSC):

  • Amazon’s vice president of Alexa, Steve Rabuchin, has confirmed that yes, there really are 10,000 Amazon employees working on Alexa and the Echo.
  • Those employees are focused on things like machine learning and making Alexa more knowledgeable.
  • Some employees are working on giving Alexa a personality, too.

 

 

From DSC:
How might this trend impact learning spaces? For example, I am interested in using voice to intuitively “drive” smart classroom control systems:

  • “Alexa, turn on the projector”
  • “Alexa, dim the lights by 50%”
  • “Alexa, open Canvas and launch my Constitutional Law I class”

 

 

 

The Lesson You Never Got Taught in School: How to Learn! — from bigthink.com by Simon Oxenham (from 2/15/13)
Psychological Science in the Public Interest evaluated ten techniques for improving learning, ranging from mnemonics to highlighting and came to some surprising conclusions.

 

Excerpts:

Practice Testing (Rating = High)
This is where things get interesting; testing is often seen as a necessary evil of education. Traditionally, testing consists of rare but massively important ‘high stakes’ assessments. There is however, an extensive literature demonstrating the benefits of testing for learning – but importantly, it does not seem necessary that testing is in the format of ‘high stakes’ assessments. All testing including ‘low stakes’ practice testing seems to result in benefits. Unlike many of the other techniques mentioned, the benefits of practice testing are not modest – studies have found that a practice test can double free recall!

Distributed Practice (Rating = High)
Have you ever wondered whether it is best to do your studying in large chunks or divide your studying over a period of time? Research has found that the optimal level of distribution of sessions for learning is 10-20% of the length of time that something needs to be remembered. So if you want to remember something for a year you should study at least every month, if you want to remember something for five years you should space your learning every six to twelve months. If you want to remember something for a week you should space your learning 12-24 hours apart. It does seem however that the distributed-practice effect may work best when processing information deeply – so for best results you might want to try a distributed practice and self-testing combo.

 

Also see:

 

 

 

 

Per Willingham (emphasis DSC):

  • Rereading is a terribly ineffective strategy. The best strategy–by far — is to self-test — which is the 9th most popular strategy out of 11 in this study.  Self-testing leads to better memory even compared to concept mapping (Karpicke & Blunt, 2011).

 

Three Takeaways from Becoming An Effective Learner:

  • Boser says that the idea that people have different learning styles, such as visual learning or verbal learning, has little scientific evidence to support it.
  • According to Boser, teachers and parents should praise their kids’ ability and effort, instead of telling them they’re smart. “When we tell people they are smart, we give them… a ‘fixed mindset,’” says Boser.
  • If you are learning piano – or anything, really – the best way to learn is to practice different composers’ work. “Mixing up your practices is far more effective,” says Boser.

 

Cumulative exams aren’t the same as spacing and interleaving. Here’s why. — from  retrievalpractice.org

Excerpts (emphasis DSC):

Our recommendations to make cumulative exams more powerful with small tweaks for you and your students:

  • Cumulative exams are good, but encourage even more spacing and discourage cramming with cumulative mini-quizzes throughout the semester, not just as an end-of-semester exam.
  • Be sure that cumulative mini-quizzes, activities, and exams include similar concepts that require careful discrimination from students, not simply related topics.
  • Make sure you are using spacing and interleaving as learning strategies and instructional strategies throughout the semester, not simply as part of assessments and cumulative exams.

Bottom line: Just because an exam is cumulative does not mean it automatically involves spacing or interleaving. Be mindful of relationships across exam content, as well as whether students are spacing their study throughout the semester or simply cramming before an exam – cumulative or otherwise.

 


From DSC:
We, like The Learning Scientists encourages us to do and even provides their own posters, should have posters with these tips on them throughout every single school and library in the country. The posters each have a different practice such as:

  • Spaced practice
  • Retrieval practice
  • Elaboration
  • Interleaving
  • Concrete examples
  • Dual coding

That said, I could see how all of that information could/would be overwhelming to some students and/or the more technical terms could bore them or fly over their heads. So perhaps we could boil down the information to feature excerpts from the top sections only that put the concepts into easier to digest words such as:

  • Practice bringing information to mind
  • Switch between ideas while you study
  • Combine words and visuals
  • Etc. 

 

Learn how to study using these practices

 

 

 

Presentation Translator for PowerPoint — from Microsoft (emphasis below from DSC:)

Presentation Translator breaks down the language barrier by allowing users to offer live, subtitled presentations straight from PowerPoint. As you speak, the add-in powered by the Microsoft Translator live feature, allows you to display subtitles directly on your PowerPoint presentation in any one of more than 60 supported text languages. This feature can also be used for audiences who are deaf or hard of hearing.

 

Additionally, up to 100 audience members in the room can follow along with the presentation in their own language, including the speaker’s language, on their phone, tablet or computer.

 

From DSC:
Up to 100 audience members in the room can follow along with the presentation in their own language! Wow!

Are you thinking what I’m thinking?! If this could also address learners and/or employees outside the room as well, this could be an incredibly powerful piece of a next generation, global learning platform! 

Automatic translation with subtitles — per the learner’s or employee’s primary language setting as established in their cloud-based learner profile. Though this posting is not about blockchain, the idea of a cloud-based learner profile reminds me of the following graphic I created in January 2017.

A couple of relevant quotes here:

A number of players and factors are changing the field. Georgia Institute of Technology calls it “at-scale” learning; others call it the “mega-university” — whatever you call it, this is the advent of the very large, 100,000-plus-student-scale online provider. Coursera, edX, Udacity and FutureLearn (U.K.) are among the largest providers. But individual universities such as Southern New Hampshire, Arizona State and Georgia Tech are approaching the “at-scale” mark as well. One could say that’s evidence of success in online learning. And without question it is.

But, with highly reputable programs at this scale and tuition rates at half or below the going rate for regional and state universities, the impact is rippling through higher ed. Georgia Tech’s top 10-ranked computer science master’s with a total expense of less than $10,000 has drawn more than 10,000 qualified majors. That has an impact on the enrollment at scores of online computer science master’s programs offered elsewhere. The overall online enrollment is up, but it is disproportionately centered in affordable scaled programs, draining students from the more expensive, smaller programs at individual universities. The dominoes fall as more and more high-quality at-scale programs proliferate.

— Ray Schroeder

 

 

Education goes omnichannel. In today’s connected world, consumers expect to have anything they want available at their fingertips, and education is no different. Workers expect to be able to learn on-demand, getting the skills and knowledge they need in that moment, to be able to apply it as soon as possible. Moving fluidly between working and learning, without having to take time off to go to – or back to – school will become non-negotiable.

Anant Agarwal

 

From DSC:
Is there major change/disruption ahead? Could be…for many, it can’t come soon enough.

 

 

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!

 

 

The information below is from Heather Campbell at Chegg
(emphasis DSC)


 

Chegg Math Solver is an AI-driven tool to help the student understand math. It is more than just a calculator – it explains the approach to solving the problem. So, students won’t just copy the answer but understand and can solve similar problems at the same time. Most importantly,students can dig deeper into a problem and see why it’s solved that way. Chegg Math Solver.

In every subject, there are many key concepts and terms that are crucial for students to know and understand. Often it can be hard to determine what the most important concepts and terms are for a given subject, and even once you’ve identified them you still need to understand what they mean. To help you learn and understand these terms and concepts, we’ve provided thousands of definitions, written and compiled by Chegg experts. Chegg Definition.

 

 

 

 

 


From DSC:
I see this type of functionality as a piece of a next generation learning platform — a piece of the Living from the Living [Class] Room type of vision. Great work here by Chegg!

Likely, students will also be able to take pictures of their homework, submit it online, and have that image/problem analyzed for correctness and/or where things went wrong with it.

 

 


 

 

Awesome study hacks: 5 ways to remember more of what you read — from academiccoachingwithpat.com by Pat LaDouceur; with thanks to Julia Reed for her Tweet on this

Excerpts:

  1. Annotate as you read
  2. Skim
  3. Rewrite key ideas in your own words
  4. Write a critique
  5. List your questions

 

Reorganizing information helps you learn it more effectively, which is why Rewriting makes the list as one of the top 5 reading study hacks. It forces you to stay active and involved with the text (from DSC: the word “engaged” comes to mind here), to consider arguments and synthesize information, and thus remember more of what you read.

 

 

From DSC:
The picture below was posted in the item below from edutopia. What a powerful picture! And not just for art or drama teachers!

Does it not once again illustrate that we are different? The lenses that we view the world through are different. Our learners are different. Each of us comes to a learning experience with different backgrounds, emotions, knowledge…and different real-life experiences.

As the article mentions, we need to create safe and supportive learning environments, where the love of (or at least the enjoyment of) learning can thrive.

 

Getting creative with social and emotional learning (SEL) — from by Maurice Elias, Sara LaHayne
How to incorporate creative expression and movement in the classroom while building social and emotional learning skills.

Excerpt:

Being creative is an inherently vulnerable process. In order to authentically build SEL competencies through creative expression, teachers need to strive to create a safe space, provide time, and open doors for validation.

  • Creating a safe and supportive classroom environment
  • Providing time
  • Opening the doors for validation

 

 

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.

 

 

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.

 

 

 

Multitasking is actually kind of a problem — for kids and adults — from washingtonpost.com by Hayley Tsukayama

Excerpt:

Multitasking is a problem in a couple of ways, Robb said, citing recent neuroscience research on the practice. “Many people think multitasking does not hamper your ability to get things done,” he said. “But multitasking can decrease your ability to get things done well, because you have to reorient. That causes a certain level of cognitive fatigue, which can slow the rate of work.”

 

But Michael Robb, the group’s director of research, said multitasking should no longer be seen as “some desirable trait that makes you the best 21st-century worker.”

 

 

 

 

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…?

 

 

 
 

Where Do I Even Start? — from byrdseed.com by Ian Byrd
Three places to begin differentiating for gifted kids

Excerpts:

I get lots of questions from overwhelmed folks who have suddenly landed in a new job in gifted ed and have had little training (heck, sounds a lot like me on my first day!).

“Where do I even start!?” is a very common cry. Here are three places to begin differentiating for gifted kids.

1. Pre-Assess
Pre-assessment is key! Without it, you’re setting out on a journey with no map and no compass. You have to know where your students are at before you differentiate.

2. Accelerate
Once you see where your students are at, the simplest way to differentiate is just to go faster! Acceleration can happen at many levels…

3. Give Complex Work, Not Merely Difficult Work
Many of you have attended my full-day workshop on the difference between difficulty and complexity. I think this difference is key for planning quality differentiated tasks that aren’t just more work.

 
© 2024 | Daniel Christian