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.

 

 


 

 

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.

 

 

 

Why higher ed should do more with blockchain tech — from by Dian Schaffhauser
Oral Roberts University recently held a conference to persuade higher education institutions that it’s time to get on board the blockchain train. Its recommendations: Learn about the technology’s potential, test it out and collaborate.

Excerpt:

As CIO Michael Mathews, the event’s organizer, explained, blockchain will be as important to transforming education as the internet was. He said he believes those colleges and universities that jump on the secure public ledger concept early enough and begin testing it out will be the ones who could see the biggest benefits.

Mathews believes blockchain will have the “biggest payback” within an organization’s processes where trust is essential as part of a “value chain”: student application processing, transcript evaluations, articulation agreements. Blockchain “templates” that run in the cloud could replace “entire cumbersome processes”…

 

 

From DSC:
It could easily be that blockchain-based technologies and processes feed into cloud/web-based learner profiles in the future. That’s one aspect of the next generation learning platform that I’m pulse checking — I call it Learning from the Living [Class] Room.

 

Blockchain could be involved with cloud/web-based learner profiles in the future

Blockchain -- something to keep on our radars in higher education

 

Also, from a while back…

Oracle to Launch Blockchain Products This Month — from investopedia.com by Shobhit Seth

Excerpt:

Tech corporations are seeing big opportunities in the blockchain space, and are now in a closely contested race to seize them sooner rather than later.

Oracle Corp. has announced that it will unveil its blockchain software later this month, reports Bloomberg. Oracle will launch its platform-as-a-service blockchain product later this month, which will be followed by launch of the decentralized ledger-based applications next month.

The Redwood City, California-based software giant is already having clients on board for its blockchain offerings. Santiago-based Banco de Chile is one of the early clients that Oracle is working with to record inter-bank transactions on a hyperledger. The world’s second-largest software company is also working with the government of Nigeria, which is aiming to document customs and import duties on a blockchain. Oracle is also hopeful of offering solutions to a large number of pharmaceutical companies to efficiently track and locate batches of drugs to help them reduce the number of recalls. Thomas Kurian, president of product development, said that Oracle’s products will be compatible with other platforms.

 

 

 

 

 

Creating continuous, frictionless learning with new technologies — from clomedia.com by Karen Hebert-Maccaro
Point-of-need and on-the-job learning experiences are about to get a lot more creative.

Excerpt:

Technology has conditioned workers to expect quick and easy experiences — from Google searches to help from voice assistants — so they can get the answers they need and get back to work. While the concept of “on-demand” learning is not new, it’s been historically tough to deliver, and though most learning and development departments have linear e-learning modules or traditional classroom experiences, today’s learners are seeking more performance-adjacent, “point-of-need” models that fit into their busy, fast-paced work environments.

Enter emerging technologies. Artificial intelligence, voice interfaces and augmented reality, when applied correctly, have the potential to radically change the nature of how we learn at work. What’s more, these technologies are emerging at a consumer-level, meaning HR’s lift in implementing them into L&D may not be substantial. Consider the technologies we already use regularly — voice assistants like Alexa, Siri and Google Assistant may be available in 55 percent of homes by 2022, providing instant, seamless access to information we need on the spot. While asking a home assistant for the weather, the best time to leave the house to beat traffic or what movies are playing at a local theater might not seem to have much application in the workplace, this nonlinear, point-of-need interaction is already playing out across learning platforms.

 

Artificial intelligence, voice interfaces and augmented reality, when applied correctly, have the potential to radically change the nature of how we learn at work.

 

 

The rise of newsroom smart machines: Optimizing workflow with artificial intelligence — from mediablog.prnewswire.com by Julian Dossett

Excerpts:

As computer algorithms become more advanced, artificial intelligence (AI) increasingly has grown prominent in the workplace.  Top news organizations now use AI for a variety of newsroom tasks.

But current AI systems largely are still dependent on humans to function correctly, and the most pressing concern is understanding how to correctly operate these systems as they continue to thrive in a variety of media-related industries.

So, while [Machine Learning] systems soon will become ubiquitous in many professions, they won’t replace the professionals working in those fields for some time — rather, they will become an advanced tool that will aid in decision making. This is not to say that AI will never endanger human jobs. Automation always will find a way.

 

 

 
AI and Chatbots in Education: What Does The FutureHold? — from chatbotsmagazine.com by Robin Singh

From DSC:
While I don’t find this  article to be exemplary, I post this one mainly to encourage innovative thinking about how we might use some of these technologies in our future learning ecosystems. 

 

 

 

 

2018 Workplace Learning Report — from learning.linkedin.com

Excerpts:

The path to opportunity is changing
The short shelf life of skills and a tightening labor market are giving rise to a multitude of skill gaps. Businesses are fighting to stay ahead of the curve, trying to hold onto their best talent and struggling to fill key positions. Individuals are conscious of staying relevant in the age of automation.

Enter the talent development function.
These organizational leaders create learning opportunities to enable employee growth and achievement. They have the ability to guide their organizations to success in tomorrow’s labor market, but they can’t do it alone.

Our research answers the talent developer’s most pressing questions:
* How are savvy talent development leaders adapting to the pace of change in today’s dynamic world of work?
* Why do employees demand learning and development resources, but don’t make the time to learn?
* How do executives think about learning and development?
* Are managers the missing link to successful learning programs?

 

From DSC:
Even though this piece is a bit of a sales pitch for Lynda.com — a great service I might add — it’s still worth checking out. I say this because it brings up a very real trend that I’m trying to bring more awareness to — i.e., the pace of change has changed. Our society is not ready for this new, exponential pace of change. Technologies are impacting jobs and how we do our jobs, and will likely do so for the next several decades. Skills gaps are real and likely growing larger. Corporations need to do their part in helping higher education revise/develop curriculum and they need to offer funds to create new types of learning labs/environments. They need to offer more internships and opportunities to learn new skills.

 

 

 

From DSC:
After seeing the article entitled, “Scientists Are Turning Alexa into an Automated Lab Helper,” I began to wonder…might Alexa be a tool to periodically schedule & provide practice tests & distributed practice on content? In the future, will there be “learning bots” that a learner can employ to do such self-testing and/or distributed practice?

 

 

From page 45 of the PDF available here:

 

Might Alexa be a tool to periodically schedule/provide practice tests & distributed practice on content?

 

 

 

 

Michelle Weise: ‘We Need to Design the Learning Ecosystem of the Future’ — from edsurge.com  by Michelle Weise

Excerpts:

These days, education reformers, evangelists and foundations pay a lot of lip service to the notion of lifelong learning, but we do little to invest in the systems, architecture and infrastructure needed to facilitate seamless movements in and out of learning and work.

Talk of lifelong learning doesn’t translate into action. In fact, resources and funding are often geared toward the traditional 17- to 22-year-old college-going population and less often to working adults, our growing new-traditional student population.

We’ll need a different investment thesis: For most adults, taking time off work to attend classes at a local, brick-and-mortar community college or a four-year institution will not be the answer. The opportunity costs will be too high. Our current system of traditional higher education is ill-suited to facilitate flexible, seamless cost-effective learning pathways for these students to keep up with the emergent demands of the workforce.

Many adults may have no interest in coming back to college. Out of the 37 million Americans with some college and no degree, many have already failed one or twice before and will be wholly uninterested in experiencing more educational trauma.We can’t just say, “Here’s a MOOC, or here’s an online degree, or a 6- to 12-week immersive bootcamp.”

 

We have to do better. Let’s begin seeding the foundational elements of a learning ecosystem of the future—flexible enough for adults to move consistently in and out of learning and work. Enough talk about lifelong learning: Let’s build the foundations of that learning ecosystem of the future.

 

 

From DSC:
I couldn’t agree more with Michelle that we need a new learning ecosystem of the future. In fact, I have been calling such an effort “Learning from the Living [Class] Room — and it outlines a next generation learning platform that aims to deliver everything Michelle talks about in her solid article out at edsurge.com.

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

 

Along these lines…I just saw that Amazon is building out more cashierless stores (and Walmart is also at work on introducing more cashierless stores.) Now, let’s say that you are currently a cashier. 2-5 years from now (depending upon where you’re currently working and which stores are in your community), what are you going to do? The opportunities for such a position will be fewer and fewer. Who can help you do what Michelle mentioned here:

Working learners will also need help articulating their learning goals and envisioning a future for themselves. People don’t know how to translate their skills from one industry to another. How does a student begin to understand that 30% of what they already know could be channeled into a totally different and potentially promising pathway they never even knew was within reach?

And that cashier may have had a tough time with K-12 education and/or with higher education. As Michelle writes:

Many adults may have no interest in coming back to college. Out of the 37 million Americans with some college and no degree, many have already failed one or twice before and will be wholly uninterested in experiencing more educational trauma. We can’t just say, “Here’s a MOOC, or here’s an online degree, or a 6- to 12-week immersive bootcamp.”

And like the cashier in this example…we are quickly approaching an era where, I believe, many of us will need to reinvent ourselves in order to:

  • stay marketable
  • keep bread and butter on the table
  • continue to have a sense of purpose and meaning in our lives

Higher ed, if it wants to remain relevant, must pick up the pace of experimentation and increase the willingness to innovate, and to develop new business models — to develop new “learning channels” so to speak. Such channels need to be:

  • Up-to-date
  • Serving relevant data and information– especially regarding the job market and which jobs appear to be safe for the next 5-10 years
  • Inexpensive/affordable
  • Highly convenient

 

 

 

From DSC:
DC: Will Amazon get into delivering education/degrees? Is is working on a next generation learning platform that could highly disrupt the world of higher education? Hmmm…time will tell.

But Amazon has a way of getting into entirely new industries. From its roots as an online bookseller, it has branched off into numerous other arenas. It has the infrastructure, talent, and the deep pockets to bring about the next generation learning platform that I’ve been tracking for years. It is only one of a handful of companies that could pull this type of endeavor off.

And now, we see articles like these:


Amazon Snags a Higher Ed Superstar — from insidehighered.com by Doug Lederman
Candace Thille, a pioneer in the science of learning, takes a leave from Stanford to help the ambitious retailer better train its workers, with implications that could extend far beyond the company.

Excerpt:

A major force in the higher education technology and learning space has quietly begun working with a major corporate force in — well, in almost everything else.

Candace Thille, a pioneer in learning science and open educational delivery, has taken a leave of absence from Stanford University for a position at Amazon, the massive (and getting bigger by the day) retailer.

Thille’s title, as confirmed by an Amazon spokeswoman: director of learning science and engineering. In that capacity, the spokeswoman said, Thille will work “with our Global Learning Development Team to scale and innovate workplace learning at Amazon.”

No further details were forthcoming, and Thille herself said she was “taking time away” from Stanford to work on a project she was “not really at liberty to discuss.”

 

Amazon is quietly becoming its own university — from qz.com by Amy Wang

Excerpt:

Jeff Bezos’ Amazon empire—which recently dabbled in home security, opened artificial intelligence-powered grocery stores, and started planning a second headquarters (and manufactured a vicious national competition out of it)—has not been idle in 2018.

The e-commerce/retail/food/books/cloud-computing/etc company made another move this week that, while nowhere near as flashy as the above efforts, tells of curious things to come. Amazon has hired Candace Thille, a leader in learning science, cognitive science, and open education at Stanford University, to be “director of learning science and engineering.” A spokesperson told Inside Higher Ed that Thille will work “with our Global Learning Development Team to scale and innovate workplace learning at Amazon”; Thille herself said she is “not really at liberty to discuss” her new project.

What could Amazon want with a higher education expert? The company already has footholds in the learning market, running several educational resource platforms. But Thille is famous specifically for her data-driven work, conducted at Stanford and Carnegie Mellon University, on nontraditional ways of learning, teaching, and training—all of which are perfect, perhaps even necessary, for the education of employees.

 


From DSC:
It could just be that Amazon is simply building its own corporate university and will stay focused on developing its own employees and its own corporate learning platform/offerings — and/or perhaps license their new platform to other corporations.

But from my perspective, Amazon continues to work on pieces of a powerful puzzle, one that could eventually involve providing learning experiences to lifelong learners:

  • Personal assistants
  • Voice recognition / Natural Language Processing (NLP)
  • The development of “skills” at an incredible pace
  • Personalized recommendation engines
  • Cloud computing and more

If Alexa were to get integrated into a AI-based platform for personalized learning — one that features up-to-date recommendation engines that can identify and personalize/point out the relevant critical needs in the workplace for learners — better look out higher ed! Better look out if such a platform could interactively deliver (and assess) the bulk of the content that essentially does the heavy initial lifting of someone learning about a particular topic.

Amazon will be able to deliver a cloud-based platform, with cloud-based learner profiles and blockchain-based technologies, at a greatly reduced cost. Think about it. No physical footprints to build and maintain, no lawns to mow, no heating bills to pay, no coaches making $X million a year, etc.  AI-driven recommendations for digital playlists. Links to the most in demand jobs — accompanied by job descriptions, required skills & qualifications, and courses/modules to take in order to master those jobs.

Such a solution would still need professors, instructional designers, multimedia specialists, copyright experts, etc., but they’ll be able to deliver up-to-date content at greatly reduced costs. That’s my bet. And that’s why I now call this potential development The New Amazon.com of Higher Education.

[Microsoft — with their purchase of Linked In (who had previously
purchased Lynda.com) — is
another such potential contender.]

 

 

 


From DSC:
From an early age, we need to help our students learn how to learn. What tips, advice, and/or questions can we help our students get into the habit of asking themselves? Along these lines, the article below,”How Metacognition Boosts Learning,” provides some excellent questions. 

Speaking of questions…I’ll add some more, but of a different sort:

  • How can all educators do a better job of helping their students learn how to learn?
  • How can Instructional Designers and Instructional Technologists help out here? Librarians? Provosts? Deans? Department Chairs? Teachers? Trainers (in the corporate L&D space)?
  • How might technologies come into play here in terms of building more effective web-based learner profiles that can be fed into various platforms and/or into teachers’ game plans?

I appreciate Bill Knapp and his perspectives very much (see here and here; Bill is GRCC’s Executive Director of Distance Learning & Instructional Technologies). The last we got together, we wondered out loud:

  • Why don’t teachers, professors, school systems, administrations within in K-20 address this need/topic more directly…? (i.e., how can we best help our students learn how to learn?)
  • Should we provide a list of potentially helpful techniques, questions, tools, courses, modules, streams of content, or other resources on how to learn?
  • Should we be weaving these sorts of things into our pedagogies?
  • Are there tools — such as smartphone related apps — that can be of great service here? For example, are there apps for sending out reminders and/or motivational messages?

As Bill asserted, we need to help our students build self-efficacy and a mindset of how to learn. Then learners can pivot into new areas with much more confidence. I agree. In an era that continues to emphasize freelancing and entrepreneurship — plus dealing with a rapidly-changing workforce — people now need to be able to learn quickly and effectively. They need to have the self confidence to be able to pivot. So how can we best prepare our students for their futures?

Also, on a relevant but slightly different note (and I suppose is of the flavor of a Universal Design for Learning approach)…I think that “tests” given to special needs children — for example that might have to do with executive functioning, and/or identifying issues, and/or providing feedback as to how a particular learner might best absorb information — would be helpful for ALL students to take. If I realize that the way my brain learns best is to have aural and visual materials presented on any given topic, that is very useful information for me to realize — and the sooner the better!

 



How Metacognition Boosts Learning — from edutopia.org by Youki Terada
Students often lack the metacognitive skills they need to succeed, but they can develop these skills by addressing some simple questions.

Excerpt (emphasis DSC):

Strategies that target students’ metacognition—the ability to think about thinking—can close a gap that some students experience between how prepared they feel for a test and how prepared they actually are. In a new study, students in an introductory college statistics class who took a short online survey before each exam asking them to think about how they would prepare for it earned higher grades in the course than their peers—a third of a letter grade higher, on average. This low-cost intervention helped students gain insight into their study strategies, boosting their metacognitive skills and giving them tools to be more independent learners.

More recently, a team of psychologists and neuroscientists published a comprehensive analysis of 10 learning techniques commonly used by students. They discovered that one of the most popular techniques—rereading material and highlighting key points—is also one of the least effective because it leads students to develop a false sense of mastery. They review a passage and move on without realizing that they haven’t thoroughly understood and absorbed the material.

Metacognition helps students recognize the gap between being familiar with a topic and understanding it deeply. But weaker students often don’t have this metacognitive recognition—which leads to disappointment and can discourage them from trying harder the next time.

To promote students’ metacognition, middle and high school teachers can implement the following strategies. Elementary teachers can model or modify these strategies with their students to provide more scaffolding.

During class, students should ask themselves:

  • What are the main ideas of today’s lesson?
  • Was anything confusing or difficult?
  • If something isn’t making sense, what question should I ask the teacher?
  • Am I taking proper notes?
  • What can I do if I get stuck on a problem?

Before a test, students should ask themselves:

  • What will be on the test?
  • What areas do I struggle with or feel confused about?
  • How much time should I set aside to prepare for an upcoming test?
  • Do I have the necessary materials (books, school supplies, a computer and online access, etc.) and a quiet place to study, with no distractions?
  • What strategies will I use to study? Is it enough to simply read and review the material, or will I take practice tests, study with a friend, or write note cards?
  • What grade would I get if I were to take the test right now?

After a test, students should ask themselves:

  • What questions did I get wrong, and why did I get them wrong?
  • Were there any surprises during the test?
  • Was I well-prepared for the test?
  • What could I have done differently?
  • Am I receiving useful, specific feedback from my teacher to help me progress?

 



From DSC:
Below are a few resources more about metacognition and learning how to learn:

 

 

 

  • Students should be taught how to study. — from Daniel Willingham
    Excerpt:
    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).

 

 

 

  • The Lesson You Never Got Taught in School: How to Learn! — from bigthink.com
    Excerpt:
    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.There is however a major catch – do you ever find that the amount of studying you do massively increases before an exam? Most students fall in to the “procrastination scallop” – we are all guilty at one point of cramming all the knowledge in right before an exam, but the evidence is pretty conclusive that this is the worst way to study, certainly when it comes to remembering for the long term. What is unclear is whether cramming is so popular because students don’t understand the benefits of distributed practice or whether testing practices are to blame – probably a combination of both. One thing is for sure, if you take it upon yourself to space your learning over time you are pretty much guaranteed to see improvements.

 

 



Addendum on 1/22/18:

Using Metacognition to Promote Learning
IDEA Paper #63 | December 2016
By Barbara J. Millis

Excerpt:

Some Definitions of Metacognition
Metacognition, simplistically defined, can be described as “cognition about cognition” or “thinking about thinking” (Flavell, Miller & Miller, 2002, p. 175; Shamir, Metvarech, & Gida, 2009, p. 47; Veeman, Van Hout-Wolters, & Afflerbach, 2006, p. 5). However, because metacognition is multifaceted and multi-layered (Dunlosky & Metcalf, 2009, p. 1; Flavell, 1976; Hall, Danielewicz, & Ware , 2013, p. 149; Lovett, 2013, p. 20), more complex definitions are called for. Basically, metacognition must be viewed as an ongoing process that involves reflection and action. Metacognitive thinkers change both their understandings and their strategies. The clearest definitions of metacognition emphasize its nature as a process or cycle.

Several authors (Nilson, 2013, p. 9; Schraw, 2001; & Zimmerman, 1998; 2000; 2002) narrow this process down to three ongoing stages. The first stage, pre-planning, emphasizes the need for reflection on both one’s own thinking and the task at hand, including reflection on past strategies that might have succeeded or failed. Following this self-reflection, during planning, metacognitive thinkers develop and implement—put into action—a plan. In the third and final stage—post-planning adjustments/revisions—subsequent analysis following implementation leads to modifications, revised decisions, and new future plans. In an excellent summary, Wirth states that “metacognition requires students both to understand how they are learning and to develop the ability to make plans, to monitor progress and to make adjustments” (as cited in Jaschik, 2011, p. 2).

 

Conclusion: As we have seen, metacognition is a complex but valuable skill that can nurture students’ learning and their self-awareness of the learning process. It is best conceived as a three-step process that can occur through deliberately designed activities. Such activities can take place before, during, and after face-to-face lessons or through online learning. They can also be built around both multiple choice and essay examinations. Immersing students in these metacognitive activities—assuming there are opportunities for practice and feedback—can result in students who are reflective learners.

 

 

 

 

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