Mapping the Trends on Our Doorstep: The Pace of Change Has Changed — from an article that I did out at — and with — evoLLLution.com [where LLL stands for lifelong learning]; my thanks to Mr. Amrit Ahluwalia, Managing Editor out at evolllution.com and to his staff as well!
The higher education industry has changed significantly over the past decade, and given the pace and significance of change hitting other industries as a result of technological advances, it’s fair to say the postsecondary space is ripe for further transformation.

 

From DSC:
From the perspective of those of us working within higher education, we see massive changes occurring in the corporate world, and we see innovations and changes also occurring in the world of K-12. Higher education should also be adapting, changing, questioning, and reflecting upon how we can best prepare our students for a rapidly changing workplace.

Below is another interesting item that I believe gives credence to the idea that we are now on an exponential pace of change. Companies are coming and going on the S&P Index…at an ever faster pace.

The 33-year average tenure of companies on the S&P 500 in 1964 narrowed to 24 years by 2016 and is forecast to shrink to just 12 years by 2027 (Chart 1).

 

Here is the video:

This is the transcript with the original graphs in it.

This is a nice PDF file from evoLLLution.com with the transcript, with some different graphics and some other

 

 

 

 

What is Artificial Intelligence, Machine Learning and Deep Learning — from geospatialworld.net by Meenal Dhande

 

 

 

 

 


 

What is the difference between AI, machine learning and deep learning? — from geospatialworld.net by Meenal Dhande

Excerpt:

In the first part of this blog series, we gave you simple and elaborative definitions of what is artificial intelligence (AI), machine learning and deep learning. This is the second part of the series; here we are elucidating our readers with – What is the difference between AI, machine learning, and deep learning.

You can think of artificial intelligence (AI), machine learning and deep learning as a set of a matryoshka doll, also known as a Russian nesting doll. Deep learning is a subset of machine learning, which is a subset of AI.

 

 

 

 

 


Chatbot for College Students: 4 Chatbots Tips Perfect for College Students — from chatbotsmagazine.com by Zevik Farkash

Excerpts:

1. Feed your chatbot with information your students don’t have.
Your institute’s website can be as elaborate as it gets, but if your students can’t find a piece of information on it, it’s as good as incomplete. Say, for example, you offer certain scholarships that students can voluntarily apply for. But the information on these scholarships are tucked away on a remote page that your students don’t access in their day-to-day usage of your site.

So Amy, a new student, has no idea that there’s a scholarship that can potentially make her course 50% cheaper. She can scour your website for details when she finds the time. Or she can ask your university’s chatbot, “Where can I find information on your scholarships?”

And the chatbot can tell her, “Here’s a link to all our current scholarships.”

The best chatbots for colleges and universities tend to be programmed with even more detail, and can actually strike up a conversation by saying things like:

“Please give me the following details so I can pull out all the scholarships that apply to you.
“Which department are you in? (Please select one.)
“Which course are you enrolled in? (Please select one.)
“Which year of study are you in? (Please select one.)
“Thank you for the details! Here’s a list of all applicable scholarships. Please visit the links for detailed information and let me know if I can be of further assistance.”

2. Let it answer all the “What do I do now?” questions.

3. Turn it into a campus guide.

4. Let it take care of paperwork.

 

From DSC:
This is the sort of thing that I was trying to get at last year at the NGLS 2017 Conference:

 

 

 

 


18 Disruptive Technology Trends For 2018 — from disruptionhub.com by Rob Prevett

Excerpts:

1. Mobile-first to AI-first
A major shift in business thinking has placed Artificial Intelligence at the very heart of business strategy. 2017 saw tech giants including Google and Microsoft focus on an“AI first” strategy, leading the way for other major corporates to follow suit. Companies are demonstrating a willingness to use AI and related tools like machine learning to automate processes, reduce administrative tasks, and collect and organise data. Understanding vast amounts of information is vital in the age of mass data, and AI is proving to be a highly effective solution. Whilst AI has been vilified in the media as the enemy of jobs, many businesses have undergone a transformation in mentalities, viewing AI as enhancing rather than threatening the human workforce.

7. Voice based virtual assistants become ubiquitous
Google HomeThe wide uptake of home based and virtual assistants like Alexa and Google Home have built confidence in conversational interfaces, familiarising consumers with a seamless way of interacting with tech. Amazon and Google have taken prime position between brand and customer, capitalising on conversational convenience. The further adoption of this technology will enhance personalised advertising and sales, creating a direct link between company and consumer.

 


 

5 Innovative Uses for Machine Learning — from entrepreneur.com
They’ll be coming into your life — at least your business life — sooner than you think.

 


 

Philosophers are building ethical algorithms to help control self-driving cars – from qz.com by Olivia Goldhill

 


 

Tech’s Ethical ‘Dark Side’: Harvard, Stanford and Others Want to Address It — from nytimes.com by Natasha Singerfeb

Excerpt:

PALO ALTO, Calif. — The medical profession has an ethic: First, do no harm.

Silicon Valley has an ethos: Build it first and ask for forgiveness later.

Now, in the wake of fake news and other troubles at tech companies, universities that helped produce some of Silicon Valley’s top technologists are hustling to bring a more medicine-like morality to computer science.

This semester, Harvard University and the Massachusetts Institute of Technology are jointly offering a new course on the ethics and regulation of artificial intelligence. The University of Texas at Austin just introduced a course titled “Ethical Foundations of Computer Science” — with the idea of eventually requiring it for all computer science majors.

And at Stanford University, the academic heart of the industry, three professors and a research fellow are developing a computer science ethics course for next year. They hope several hundred students will enroll.

The idea is to train the next generation of technologists and policymakers to consider the ramifications of innovations — like autonomous weapons or self-driving cars — before those products go on sale.

 


 

 

 

From DSC:
Here’s a quote that has been excerpted from the announcement below…and it’s the type of service that will be offered in our future learning ecosystems — our next generation learning platforms:

 

Career Insight™ enables prospective students to identify programs of study which can help them land the careers they want: Career Insight™ describes labor market opportunities associated with programs of study to prospective students. The recommendation engine also matches prospective students to programs based on specific career interests.

 

But in addition to our future learning platforms pointing new/prospective students to physical campuses, the recommendation engines will also provide immediate access to digital playlists for the prospective students/learners to pursue from their living rooms (or as they are out and about…i.e., mobile access).

 

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

 

 

Artificial intelligence working with enormous databases to build/update recommendation engines…yup, I could see that. Lifelong learning. Helping people know what to reinvent themselves to.

 

 


 

Career Insight™ Lets Prospective Students Connect Academic Program Choices to Career Goals — from burning-glass.com; also from Hadley Dreibelbis from Finn Partners
New Burning Glass Technologies Product Brings Job Data into Enrollment Decisions

BOSTON—Burning Glass Technologies announces the launch of Career Insight™, the first tool to show prospective students exactly how course enrollment will advance their careers.

Embedded in institutional sites and powered by Burning Glass’ unparalleled job market data, Career Insight’s personalized recommendation engine matches prospective students with programs based on their interests and goals. Career Insight will enable students to make smarter decisions, as well as improve conversion and retention rates for postsecondary institutions.

“A recent Gallup survey found that 58% of students say career outcomes are the most important reason to continue their education,” Burning Glass CEO Matthew Sigelman said. “That’s particularly true for the working learners who are now the norm on college campuses. Career Insight™ is a major step in making sure that colleges and universities can speak their language from the very first.”

Beginning an educational program with a firm, realistic career goal can help students persist in their studies. Currently only 29% of students in two-year colleges and 59% of those in four-year institutions complete their degrees within six years.

Career Insight™ enables prospective students to identify programs of study which can help them land the careers they want:

  • Career Insight™ describes labor market opportunities associated with programs of study to prospective students. The recommendation engine also matches prospective students to programs based on specific career interests.
  • The application provides insights to enrollment, advising, and marketing teams into what motivates prospective students, analysis that will guide the institution in improving program offerings and boosting conversion.
  • Enrollment advisors can also walk students through different career and program scenarios in real time.

Career Insight™ is driven by the Burning Glass database of a billion job postings and career histories, collected from more than 40,000 online sources daily. The database, powered by a proprietary analytic taxonomy, provides insight into what employers need much faster and in more detail than any other sources.

Career Insight™ is powered by the same rich dataset Burning Glass delivers to hundreds of leading corporate and education customers – from Microsoft and Accenture to Harvard University and Coursera.

More information is available at http://burning-glass.com/career-insight.

 


 

 

From DSC:
With some predictions saying that the workforce is going to be composed of upwards of ~50% of us being contingent workers, (I’ve already seen figures around mid 30’s and even 40%), the question I have is:

Are we teaching students how to protect themselves, how to sell themselves, how to sell their businesses, how to plan financially, etc.? 

Consider this article:

Would our students know about these types of mistakes?

Also, it seems to me that higher education should be helping students “future proof” themselves — or at least as much as possible. One of the values higher education should be bringing to the table is to identify which jobs are going to be around for the next 5-10 years and which ones aren’t.

Along these lines, lifelong learning and learning how to learn are becoming increasingly important. Thus, I will continue to try and post articles/resources on this blog in regards to metacognition and the like.

 

 

 

The 4th Next Generation Learning Spaces event is right around the corner! Make plans to attend this conference -- you won't regret it!

The 4th Next Generation Learning Spaces event is right around the corner!

Take a look at the latest agenda.

Here is just a fraction of what you can expect:

  • Explore what’s next in learning spaces + design thinking that breaks the barriers of tradition and inspire innovation
  • Retool your learning environments with virtual & augmented reality
  • Connect your learning space design with strategic planning initiatives
  • Discover next generation learning solutions during our networking breaks
  • Overcome institutional and financial roadblocks to building active learning spaces
  • Redesign spaces with limited budgets

 


From DSC:
I am honored to be serving on the Advisory Council for this conference with a great group of people. Missing — at least from my perspective — from the image below is Kristen Tadrous, Senior Program Director with the Corporate Learning Network. Kristen has done a great job these last few years planning and running this conference.

 

The Advisory Board for the 2018 Next Generation Learning Spaces Conference

NOTE:
The above graphic reflects a change for me. I am still an Adjunct Faculty Member
at Calvin College, but I am no longer a Senior Instructional Designer there.

 

This national conference will be held in Los Angeles, CA on February 26-28, 2018. It is designed to help institutions of higher education develop highly-innovative cultures — something that’s needed in many institutions of traditional higher education right now.

I have attended the first 3 conferences and I moderated a panel at last year’s conference out in San Diego. I just want to say that this is a great conference and I encourage you to bring a group of people to it from your organization! I say a group of people because a group of 5 of us (from a variety of departments) went one year and the result of attending the NGLS Conference was a brand new Sandbox Classroom — an active-learning based, highly-collaborative learning space where faculty members can experiment with new pedagogies as well as with new technologies. The conference helped us discuss things as a diverse group, think out loud, come up with some innovative ideas, and then build the momentum to move forward with some of those key ideas.

If you haven’t already attended this conference, I highly recommend that you check it out.

 


 

 

 

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.]

 

 

 

 

The next era of human|machine partnerships
From delltechnologies.com by the Institute for the Future and Dell Technologies

 


From DSC:
Though this outlook report paints a rosier picture than I think we will actually encounter, there are several interesting perspectives in this report. We need to be peering out into the future to see which trends and scenarios are most likely to occur…then plan accordingly. With that in mind, I’ve captured a few of the thoughts below.


 

At its inception, very few people anticipated the pace at which the internet would spread across the world, or the impact it would have in remaking business and culture. And yet, as journalist Oliver Burkeman wrote in 2009, “Without most of us quite noticing when it happened, the web went from being a strange new curiosity to a background condition of everyday life.”1

 

In Dell’s Digital Transformation Index study, with 4,000 senior decision makers across the world, 45% say they are concerned about becoming obsolete in just 3-5 years, nearly half don’t know what their industry will look like in just three years’ time, and 73% believe they need to be more ‘digital’ to succeed in the future.

With this in mind, we set out with 20 experts to explore how various social and technological drivers will influence the next decade and, specifically, how emerging technologies will recast our society and the way we conduct business by the year 2030. As a result, this outlook report concludes that, over the next decade, emerging technologies will underpin the formation of new human-machine partnerships that make the most of their respective complementary strengths. These partnerships will enhance daily activities around the coordination of resources and in-the-moment learning, which will reset expectations for work and require corporate structures to adapt to the expanding capabilities of human-machine teams.


For the purpose of this study, IFTF explored the impact that Robotics, Artificial Intelligence (AI) and Machine Learning, Virtual Reality (VR) and Augmented Reality (AR), and Cloud Computing, will have on society by 2030. These technologies, enabled by significant advances in software, will underpin the formation of new human-machine partnerships.

On-demand access to AR learning resources will reset expectations and practices around workplace training and retraining, and real-time decision-making will be bolstered by easy access to information flows. VR-enabled simulation will immerse people in alternative scenarios, increasing empathy for others and preparation for future situations. It will empower the internet of experience by blending physical and virtual worlds.

 

Already, the number of digital platforms that are being used to orchestrate either physical or human resources has surpassed 1,800.9 They are not only connecting people in need of a ride with drivers, or vacationers with a place to stay, but job searchers with work, and vulnerable populations with critical services. The popularity of the services they offer is introducing society to the capabilities of coordinating technologies and resetting expectations about the ownership of fixed assets.

 

Human-machine partnerships won’t spell the end of human jobs, but work will be vastly different.

The U.S. Bureau of Labor Statistics says that today’s learners will have 8 to 10 jobs by the time they are 38. Many of them will join the workforce of freelancers. Already 50 million strong, freelancers are projected to make up 50% of the workforce in the United States by 2020.12 Most freelancers will not be able to rely on traditional HR departments, onboarding processes, and many of the other affordances of institutional work.

 

By 2030, in-the-moment learning will become the modus operandi, and the ability to gain new knowledge will be valued higher than the knowledge people already have.

 

 

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

 

 

 


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.

 

 

 

 

Why Don’t Educators in Higher Ed Take Education Classes? — from insidehighered.com by Jillian Joyce
If we’re in higher education to educate, Jillian Joyce asks, what keeps college teachers from learning more about teaching?

Excerpt (emphasis DSC):

If we’re in higher education to educate, what keeps college teachers from learning more about teaching? You’re busy. You’ve been doing this a long time. It’s really up to the students to learn the material. You’re already an excellent lecturer. Anyone can teach; it’s not that complicated. While those phrases begin to scratch the surface, I propose we take a step back to examine the internal narratives and pervading ideologies that surround our ideas about teaching at the university.

Three Myths
In her 2003 text Practice Makes Practice, Deborah P. Britzman, a professor at York University in Toronto, describes three myths that summon teachers to the field of education: 1) everything depends upon the teacher, 2) the teacher is the expert and 3) teachers are self-made. While Britzman’s audience is largely teachers at the primary and secondary levels, these myths abound in higher education, as well.

Similarly, professors at a university are typically required to wear two hats: one hat as a researcher and another as a teacher. But only the researcher hat is fashionable. It brings in money for the university, it looks good on a curriculum vitae and it promotes the climb up the academic latter.

In contrast, the teacher hat is slumpy. It’s necessary but not pretty. It’s the kind of hat you wear grocery shopping hoping no one will recognize you. The fancy hat promotes the educator as the expert, while the slumpy hat is seen as “just” teaching. This distinction fosters the idea that teaching is easy and requires little effort. The uncomfortable adage “those who can’t do, teach” suggests that research is “doing,” while teaching is a second-rate activity.

 


From DSC:
Teaching effectively is a very complex, deep, and difficult task to do well. Those who say it’s easy have likely never tried doing it themselves. Also, in higher education, doing research is one thing, but teaching well is a whole different set of (often undervalued) skills.

My alma mater (Northwestern University) prides itself on faculty who are doing leading edge research. According to this page, there was $676.5 million in annual sponsored research back in 2016-2017. (Brief insert from DSC: For those who say higher ed isn’t a business, how would you respond to this kind of thing? Or this?*) I remember taking courses from researchers like these and many of them shouldn’t have been teaching at all — they weren’t nearly worth the cost of tuition. I also remember taking courses from graduate students who likely hadn’t had any coursework on how to teach either.

The tragedy here is that it’s the students who are paying increasingly huge tuition bills to attend Northwestern and other such universities and colleges. This is not right. Let’s lift up the craft of teaching and let those who do research, research. Researchers can relay the highlights of their research to those who have taken the time to work on their teaching-related skills. 

My vote? If you don’t care about your teaching, you shouldn’t be teaching at all.

As a relevant side question here: What would you say to your doctor if they didn’t keep learning and growing in their skillset?!? How would you feel about that?

If you are teaching, you should have taken some coursework in how to teach — and how people learn — and you should be required to attend several professional development related events: Every. Single. Year.

 


 

DSC: Higher education not a business you say? Are you sure about that!?
The University of Alabama is paying its football coach, Nick Saban, more than $11 million this season, which puts him ahead of every coach in the professional National Football League. Clemson University coach Dabo Sweeney will earn $8.5 million, and the University of Michigan’s Jim Harbaugh $7 million, not including money from endorsements.

 


 

 

TV is (finally) an app: The goods, the bads and the uglies for learning — from thejournal.com by Cathie Norris, Elliot Soloway

Excerpts:

Television. TV. There’s an app for that. Finally! TV — that is, live shows such as the news, specials, documentaries (and reality shows, if you must) — is now just like Candy Crunch and Facebook. TV apps (e.g., DirecTV Now) are available on all devices — smartphones, tablets, laptops, Chromebooks. Accessing streams upon streams of videos is, literally, now just a tap away.

Plain and simple: readily accessible video can be a really valuable resource for learners and learning.

Not everything that needs to be learned is on video. Instruction will need to balance the use of video with the use of printed materials. That balance, of course, needs to take in cost and accessibility.

Now for the 800 pound gorilla in the room: Of course, that TV app could be a huge distraction in the classroom. The TV app has just piled yet another classroom management challenge onto a teacher’s back.

That said, it is early days for TV as an app. For example, HD (High Definition) TV demands high bandwidth — and we can experience stuttering/skipping at times. But, when 5G comes around in 2020, just two years from now, POOF, that stuttering/skipping will disappear. “5G will be as much as 1,000 times faster than 4G.”  Yes, POOF!

 

From DSC:
Learning via apps is here to stay. “TV” as apps is here to stay. But what’s being described here is but one piece of the learning ecosystem that will be built over the next 5-15 years and will likely be revolutionary in its global impact on how people learn and grow. There will be opportunities for social-based learning, project-based learning, and more — with digital video being a component of the ecosystem, but is and will be insufficient to completely move someone through all of the levels of Bloom’s Taxonomy.

I will continue to track this developing learning ecosystem, but voice-driven personal assistants are already here. Algorithm-based recommendations are already here. Real-time language translation is already here.  The convergence of the telephone/computer/television continues to move forward.  AI-based bots will only get better in the future. Tapping into streams of up-to-date content will continue to move forward. Blockchain will likely bring us into the age of cloud-based learner profiles. And on and on it goes.

We’ll still need teachers, professors, and trainers. But this vision WILL occur. It IS where things are heading. It’s only a matter of time.

 

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

 

 

 

 

 

Looking for something?

Use the form below to search the site:

Still not finding what you're looking for? Drop a comment on a post or contact us so we can take care of it!

© 2017 | Daniel Christian