From DSC:
Though slightly older, this article has some solid advice that I think we in higher education need to heed as well.


 

The Importance of Continuing Education for Digital Leaders — from strategy-business.com by Chris Curran — with thanks to tweets by Cathryn Marsh and G Athanasakopoulos

Excerpt (emphasis DSC):

Whether you’re a newly minted MBA or an experienced leader, you’re always honing your skills and navigating change. And technology is one discipline in which you really can’t afford to stagnate. With digital transformation so central to strategy for most companies, all executives — especially CEOs — must embrace a learning mind-set. Gone are the days you can delegate the job of keeping up with technology to the IT staff.

Chief information officers (CIOs), of course, should regularly brief the management team and the board on new developments, demoing exciting new technology, bringing in external speakers and vendors, and using other tactics that promote tech learning and engagement. But keeping up on technology trends is also the responsibility of every executive. And while that can be daunting given the vast tech landscape and seemingly limitless avenues for learning, it’s also incredibly exciting.

 

 

Indeed, the art of continuous learning itself may be the most sought-after skill for tomorrow’s workforce as well as the key to solving tomorrow’s problems. 

 

 


From DSC:
Tapping into streams of content (via RSS feeds and/or with tools like Google Alerts) is key here. Developing your personal learning networks and your communities of practice are key here. The article also mentions MOOCs and online learning. which I would also add to the list of helpful tools/avenues to pursue.


 

 

The 2017 Dean’s List: EdTech’s 50 Must-Read Higher Ed Blogs [Meghan Bogardus Cortez at edtechmagazine.com]

 

The 2017 Dean’s List: EdTech’s 50 Must-Read Higher Ed Blogs — from edtechmagazine.com by Meghan Bogardus Cortez
These administrative all-stars, IT gurus, teachers and community experts understand how the latest technology is changing the nature of education.

Excerpt:

With summer break almost here, we’ve got an idea for how you can use some of your spare time. Take a look at the Dean’s List, our compilation of the must-read blogs that seek to make sense of higher education in today’s digital world.

Follow these education trailblazers for not-to-be-missed analyses of the trends, challenges and opportunities that technology can provide.

If you’d like to check out the Must-Read IT blogs from previous years, view our lists from 2016, 2015, 2014 and 2013.

 

 



From DSC:
I would like to thank Tara Buck, Meghan Bogardus Cortez, D. Frank Smith, Meg Conlan, and Jimmy Daly and the rest of the staff at EdTech Magazine for their support of this Learning Ecosystems blog through the years — I really appreciate it. 

Thanks all for your encouragement through the years!



 

 

 

 

From DSC and Adobe — for faculty members and teachers out there:

Do your students an enormous favor by assigning them a digital communications project. Such a project could include images, infographics, illustrations, animations, videos, websites, blogs (with RSS feeds), podcasts, videocasts, mobile apps and more. Such outlets offer powerful means of communicating and demonstrating knowledge of a particular topic.

As Adobe mentions, when you teach your students how to create these types of media projects, you prepare them to be flexible and effective digital communicators.  I would also add that these new forms and tools can be highly engaging, while at the same time, they can foster students’ creativity. Building new media literacy skills will pay off big time for your students. It will land them jobs. It will help them communicate to a global audience. Students can build upon these skills to powerfully communicate numerous kinds of messages in the future. They can be their own radio station. They can be their own TV station.

For more information, see this page out at Adobe.com.

 

 

From DSC:
This is where we may need more team-based approaches…because one person may not be able to create and grade/assess such assignments.

 

 

Making sure the machines don’t take over — from raconteur.net by Mark Frary
Preparing economic players for the impact of artificial intelligence is a work in progress which requires careful handling

 

From DSC:
This short article presents a balanced approach, as it relays both the advantages and disadvantages of AI in our world.

Perhaps it will be one of higher education’s new tasks — to determine the best jobs to go into that will survive the next 5-10+ years and help you get up-to-speed in those areas. The liberal arts are very important here, as they lay a solid foundation that one can use to adapt to changing conditions and move into multiple areas. If the C-suite only sees the savings to the bottom line — and to *&^# with humanity (that’s their problem, not mine!) — then our society could be in trouble.

 

Also see:

 

 

 

The Enterprise Gets Smart
Companies are starting to leverage artificial intelligence and machine learning technologies to bolster customer experience, improve security and optimize operations.

Excerpt:

Assembling the right talent is another critical component of an AI initiative. While existing enterprise software platforms that add AI capabilities will make the technology accessible to mainstream business users, there will be a need to ramp up expertise in areas like data science, analytics and even nontraditional IT competencies, says Guarini.

“As we start to see the land grab for talent, there are some real gaps in emerging roles, and those that haven’t been as critical in the past,” Guarini  says, citing the need for people with expertise in disciplines like philosophy and linguistics, for example. “CIOs need to get in front of what they need in terms of capabilities and, in some cases, identify potential partners.”

 

 

 

Asilomar AI Principles

These principles were developed in conjunction with the 2017 Asilomar conference (videos here), through the process described here.

 

Artificial intelligence has already provided beneficial tools that are used every day by people around the world. Its continued development, guided by the following principles, will offer amazing opportunities to help and empower people in the decades and centuries ahead.

Research Issues

 

1) Research Goal: The goal of AI research should be to create not undirected intelligence, but beneficial intelligence.

2) Research Funding: Investments in AI should be accompanied by funding for research on ensuring its beneficial use, including thorny questions in computer science, economics, law, ethics, and social studies, such as:

  • How can we make future AI systems highly robust, so that they do what we want without malfunctioning or getting hacked?
  • How can we grow our prosperity through automation while maintaining people’s resources and purpose?
  • How can we update our legal systems to be more fair and efficient, to keep pace with AI, and to manage the risks associated with AI?
  • What set of values should AI be aligned with, and what legal and ethical status should it have?

3) Science-Policy Link: There should be constructive and healthy exchange between AI researchers and policy-makers.

4) Research Culture: A culture of cooperation, trust, and transparency should be fostered among researchers and developers of AI.

5) Race Avoidance: Teams developing AI systems should actively cooperate to avoid corner-cutting on safety standards.

Ethics and Values

 

6) Safety: AI systems should be safe and secure throughout their operational lifetime, and verifiably so where applicable and feasible.

7) Failure Transparency: If an AI system causes harm, it should be possible to ascertain why.

8) Judicial Transparency: Any involvement by an autonomous system in judicial decision-making should provide a satisfactory explanation auditable by a competent human authority.

9) Responsibility: Designers and builders of advanced AI systems are stakeholders in the moral implications of their use, misuse, and actions, with a responsibility and opportunity to shape those implications.

10) Value Alignment: Highly autonomous AI systems should be designed so that their goals and behaviors can be assured to align with human values throughout their operation.

11) Human Values: AI systems should be designed and operated so as to be compatible with ideals of human dignity, rights, freedoms, and cultural diversity.

12) Personal Privacy: People should have the right to access, manage and control the data they generate, given AI systems’ power to analyze and utilize that data.

13) Liberty and Privacy: The application of AI to personal data must not unreasonably curtail people’s real or perceived liberty.

14) Shared Benefit: AI technologies should benefit and empower as many people as possible.

15) Shared Prosperity: The economic prosperity created by AI should be shared broadly, to benefit all of humanity.

16) Human Control: Humans should choose how and whether to delegate decisions to AI systems, to accomplish human-chosen objectives.

17) Non-subversion: The power conferred by control of highly advanced AI systems should respect and improve, rather than subvert, the social and civic processes on which the health of society depends.

18) AI Arms Race: An arms race in lethal autonomous weapons should be avoided.

Longer-term Issues

 

19) Capability Caution: There being no consensus, we should avoid strong assumptions regarding upper limits on future AI capabilities.

20) Importance: Advanced AI could represent a profound change in the history of life on Earth, and should be planned for and managed with commensurate care and resources.

21) Risks: Risks posed by AI systems, especially catastrophic or existential risks, must be subject to planning and mitigation efforts commensurate with their expected impact.

22) Recursive Self-Improvement: AI systems designed to recursively self-improve or self-replicate in a manner that could lead to rapidly increasing quality or quantity must be subject to strict safety and control measures.

23) Common Good: Superintelligence should only be developed in the service of widely shared ethical ideals, and for the benefit of all humanity rather than one state or organization.

 

 

 

Excerpts:
Creating human-level AI: Will it happen, and if so, when and how? What key remaining obstacles can be identified? How can we make future AI systems more robust than today’s, so that they do what we want without crashing, malfunctioning or getting hacked?

  • Talks:
    • Demis Hassabis (DeepMind)
    • Ray Kurzweil (Google) (video)
    • Yann LeCun (Facebook/NYU) (pdf) (video)
  • Panel with Anca Dragan (Berkeley), Demis Hassabis (DeepMind), Guru Banavar (IBM), Oren Etzioni (Allen Institute), Tom Gruber (Apple), Jürgen Schmidhuber (Swiss AI Lab), Yann LeCun (Facebook/NYU), Yoshua Bengio (Montreal) (video)
  • Superintelligence: Science or fiction? If human level general AI is developed, then what are likely outcomes? What can we do now to maximize the probability of a positive outcome? (video)
    • Talks:
      • Shane Legg (DeepMind)
      • Nick Bostrom (Oxford) (pdf) (video)
      • Jaan Tallinn (CSER/FLI) (pdf) (video)
    • Panel with Bart Selman (Cornell), David Chalmers (NYU), Elon Musk (Tesla, SpaceX), Jaan Tallinn (CSER/FLI), Nick Bostrom (FHI), Ray Kurzweil (Google), Stuart Russell (Berkeley), Sam Harris, Demis Hassabis (DeepMind): If we succeed in building human-level AGI, then what are likely outcomes? What would we like to happen?
    • Panel with Dario Amodei (OpenAI), Nate Soares (MIRI), Shane Legg (DeepMind), Richard Mallah (FLI), Stefano Ermon (Stanford), Viktoriya Krakovna (DeepMind/FLI): Technical research agenda: What can we do now to maximize the chances of a good outcome? (video)
  • Law, policy & ethics: How can we update legal systems, international treaties and algorithms to be more fair, ethical and efficient and to keep pace with AI?
    • Talks:
      • Matt Scherer (pdf) (video)
      • Heather Roff-Perkins (Oxford)
    • Panel with Martin Rees (CSER/Cambridge), Heather Roff-Perkins, Jason Matheny (IARPA), Steve Goose (HRW), Irakli Beridze (UNICRI), Rao Kambhampati (AAAI, ASU), Anthony Romero (ACLU): Policy & Governance (video)
    • Panel with Kate Crawford (Microsoft/MIT), Matt Scherer, Ryan Calo (U. Washington), Kent Walker (Google), Sam Altman (OpenAI): AI & Law (video)
    • Panel with Kay Firth-Butterfield (IEEE, Austin-AI), Wendell Wallach (Yale), Francesca Rossi (IBM/Padova), Huw Price (Cambridge, CFI), Margaret Boden (Sussex): AI & Ethics (video)

 

 

 

ngls-2017-conference

 

From DSC:
I have attended the Next Generation Learning Spaces Conference for the past two years. Both conferences were very solid and they made a significant impact on our campus, as they provided the knowledge, research, data, ideas, contacts, and the catalyst for us to move forward with building a Sandbox Classroom on campus. This new, collaborative space allows us to experiment with different pedagogies as well as technologies. As such, we’ve been able to experiment much more with active learning-based methods of teaching and learning. We’re still in Phase I of this new space, and we’re learning new things all of the time.

For the upcoming conference in February, I will be moderating a New Directions in Learning panel on the use of augmented reality (AR), virtual reality (VR), and mixed reality (MR). Time permitting, I hope that we can also address other promising, emerging technologies that are heading our way such as chatbots, personal assistants, artificial intelligence, the Internet of Things, tvOS, blockchain and more.

The goal of this quickly-moving, engaging session will be to provide a smorgasbord of ideas to generate creative, innovative, and big thinking. We need to think about how these topics, trends, and technologies relate to what our next generation learning environments might look like in the near future — and put these things on our radars if they aren’t already there.

Key takeaways for the panel discussion:

  • Reflections regarding the affordances that new developments in Human Computer Interaction (HCI) — such as AR, VR, and MR — might offer for our learning and our learning spaces (or is our concept of what constitutes a learning space about to significantly expand?)
  • An update on the state of the approaching ed tech landscape
  • Creative, new thinking: What might our next generation learning environments look like in 5-10 years?

I’m looking forward to catching up with friends, meeting new people, and to the solid learning that I know will happen at this conference. I encourage you to check out the conference and register soon to take advantage of the early bird discounts.

 

 
 

Why can’t the “One Day University” come directly into your living room — 24×7? [Christian]

  • An idea/question from DSC:
    Looking at the article below, I wonder…“Why can’t the ‘One Day University‘ come directly into your living room — 24×7?”

 

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

 

This is why I’m so excited about the “The Living [Class] Room” vision. Because it is through that vision that people of all ages — and from all over the world — will be able to constantly learn, grow, and reinvent themselves (if need be) throughout their lifetimes. They’ll be able to access and share content, communicate and discuss/debate with one another, form communities of practice, go through digital learning playlists (like Lynda.com’s Learning Paths) and more.  All from devices that represent the convergence of the television, the telephone, and the computer (and likely converging with the types of devices that are only now coming into view, such as Microsoft’s Hololens).

 

LearningPaths-LyndaDotCom-April2016

 

You won’t just be limited to going back to college for a day — you’ll be able to do that 24×7 for as many days of the year as you want to.

Then when some sophisticated technologies are integrated into this type of platform — such as artificial intelligence, cloud-based learner profiles, algorithms, and the ability to setup exchanges for learning materials — we’ll get some things that will blow our minds in the not too distant future! Heutagogy on steroids!

 

 


 

 

Want to go back to college? You can, for a day. — from washingtonpost.com by Valerie Strauss

Excerpt:

Have you ever thought about how nice it would be if you could go back to college, just for the sake of learning something new, in a field you don’t know much about, with no tests, homework or studying to worry about? And you won’t need to take the SAT or the ACT to be accepted? You can, at least for a day, with something called One Day University, the brainchild of a man named Steve Schragis, who about a decade ago brought his daughter to Bard College as a freshman and thought that he wanted to stay.

One Day University now financially partners with dozens of newspapers — including The Washington Post — and a few other organizations to bring lectures to people around the country. The vast majority of the attendees are over the age 50 and interested in continuing education, and One Day University offers them only those professors identified by college students as fascinating. As Schragis says, it doesn’t matter if you are famous; you have to be a great teacher. For example, Schragis says that since Bill Gates has never shown to be one, he can’t teach at One Day University.

We bring together these professors, usually four at at a time, to cities across the country to create “The Perfect Day of College.” Of course we leave out the homework, exams, and studying! Best if there’s real variety, both male and female profs, four different schools, four different subjects, four different styles, etc. There’s no one single way to be a great professor. We like to show multiple ways to our students.

Most popular classes are history, psychology, music, politics, and film. Least favorite are math and science.

 

 


See also:


 

 

OneDayUniversity-1-April2016

 

OneDayUniversity-2-April2016

 

 

 


Addendum:


 

 

lyndaDotcom-onAppleTV-April2016

 

We know the shelf-life of skills are getting shorter and shorter. So whether it’s to brush up on new skills or it’s to stay on top of evolving ones, Lynda.com can help you stay ahead of the latest technologies.

 

 

How top liberal arts colleges prepare students for successful lives of leadership and service — from educationdive.com by John I. Williams, Jr.

Excerpt (emphasis DSC):

This year’s World Economic Forum (WEF) in Davos, Switzerland, discussed the top ten skills that will be needed for careers in 2020:

  1. Complex problem solving
  2. Critical thinking
  3. Creativity
  4. People management
  5. Coordinating with others
  6. Emotional intelligence
  7. Judgment and decision making
  8. Service orientation
  9. Negotiation
  10. Cognitive flexibility

The list is remarkable, both for what it includes and for what it doesn’t; and for the fact that it is as timeless as it is forward-looking. For our purposes, it serves as a useful gauge for the value of the education our students receive at highly-selective liberal arts colleges.

As I reflect upon the list, I realize graduates of top liberal arts colleges will smile as they read it, reminded that their education focuses on skills that will be valuable across a lifetime.

 

Going forward, college graduates may work for nine or more organizations over the course of their careers.

 

Yet, for all this techno-wizardry, the critical skills on WEF’s list for careers in 2020 resemble closely those that have defined the leaders who have emerged from top liberal arts colleges for decades. 

 

At the same time, top liberal arts colleges have always been committed to preparing students for more than just career success, including contributions to society more broadly. These colleges have always focused not only on the development of students’ intellect but on their character as well.

 

 

 

 

DanielSChristian-CognitiveHooks-LiberalArts-Oct-2015

 

Chapter 2 of the Daniel Willingham’s book entitled,  Why Don’t Students Like School: A Cognitive Scientist Answers Questions About How the Mind Works and What It Means for the Classroom, lays out the best case for the liberal arts degree that I’ve ever seen or read about.

First of all, a description of the book:
Easy-to-apply, scientifically-based approaches for engaging students in the classroom
Cognitive scientist Dan Willingham focuses his acclaimed research on the biological and cognitive basis of learning. His book will help teachers improve their practice by explaining how they and their students think and learn. It reveals-the importance of story, emotion, memory, context, and routine in building knowledge and creating lasting learning experiences.

  • Nine, easy-to-understand principles with clear applications for the classroom
  • Includes surprising findings, such as that intelligence is malleable, and that you cannot develop “thinking skills” without facts
  • How an understanding of the brain’s workings can help teachers hone their teaching skills

 

From DSC:
Though more tangential to my main point here, I really appreciate Daniel’s bridging the worlds of research and teaching. He is knowledgeable about the relevant research that’s been done out there, and he uses that knowledge to inform his recommendations for how best to apply that research in the classroom. Often, it seems, these two worlds don’t get connected.  I also like how he models solid ways of teaching. For example, he knows that repetition helps, so he summarizes/repeats his main points throughout a chapter.

Speaking of chapters, here are some of my notes from chapter 2:

  • Factual knowledge must proceed skill. (p. 25)
  • We need factual knowledge before we can practice critical thinking or have the ability to analyze something (p. 25)
  • “Thinking well requires knowing facts, and that’s true not simply because you need something to think about. The very processes that teachers care about most — critical thinking processes such as reasoning and problem solving – are intimately  intertwined with factual knowledge that is stored in long-term memory…” (p. 28)
  • Critical thinking processes are tied to background knowledge (p. 29)
  • Thinking skills and knowledge are bound together (p.29)
  • “The phenomenon of tying together separate pieces of information from the environment is called chunking. The advantage is obvious: you can keep more stuff in working memory if it can be chunked. The trick, however, is that chunking works only when you have applicable factual knowledge in long-term memory.” (p. 34)
  • “Thus, background knowledge allows chunking, which makes more room in working memory, which makes it easier to relate ideas, and therefore to comprehend.” (p.35)
  • “…we don’t take in new information in a vacuum. We interpret new things we read in light of other information we already have on the topic.”  (p. 36)
  • “Not only does background knowledge make you a better reader, but it also is necessary to be a good thinker.” (p.37)
  • “When it comes to knowledge, those who have more gain more.” (p. 42)
  • “When it comes to knowledge, the rich get richer. (p.45 )
  • “…having background knowledge in long-term memory makes it easier to acquire still more factual knowledge.” (p. 44)
  • “Knowledge…is a prerequisite for imagination.” (p.46)
  • “The cognitive processes that are most esteemed — logical thinking, problem solving, and the like — are intertwined with knowledge.” (pgs. 46-47)

 

From DSC:
So the saying that “you get what you pay for” again turns out to be true.  That is, you will likely pay more for a 4-year liberal arts degree than what you will pay for a 10-12 week bootcamp.  But if you go to a bootcamp and come out knowing only how to code using programming language XYZ, you have far fewer cognitive “hooks” on which to hang new hats (i.e., new information).

A liberal arts degree covers and provides a great deal of knowledge — and it builds upon that knowledge with higher order skills. Such a degree provides a broader foundation of knowledge that creates numerous hooks on which to hang new hats in the future. 

These reflections regarding foundational knowledge and having hooks to hang new information on (and make new connections with) reminds me of Bloom’s Taxonomy.  Factual knowledge was the foundational layer of his original taxonomy:


Original

 

 

Revised

 

So it seems to me that the size/breadth of the foundational layer that’s been built from a liberal arts degree is far broader and deeper than a foundational layer obtained from attending a bootcamp.  The numerous number of cognitive hooks that it provides will help a sharp, hard-working graduate of a liberal arts program be able to not only understand the business at hand, but to practice creative thinking, to practice critical thinking, and to be able to innovate.

I’m not saying that a graduate of a bootcamp can’t do some of those things as well. (I also think that bootcamps can definitely have a place in our learning ecosystems.) But chances are that such a person has already built a broader foundation of remembering and understanding to draw upon.

 

What do you think, am I off base here or does this thinking accurately reflect
one of the areas in which a liberal arts degree is important and provides real, lasting value?

 
© 2016 Learning Ecosystems