Lessons from the Digital Classroom — from technologyreview.com by Nanette Byrnes
Technologists and venture capitalists are betting that the data online learning generates will reshape education.

Excerpt:

In four small schools scattered across San Francisco, a data experiment is under way. That is where AltSchool is testing how technology can help teachers maximize their students’ learning.

Founded two years ago by Max ­Ventilla, a data expert and former head of personalization at Google, AltSchool runs schools filled with data-gathering technology.

Information is captured from the moment each student arrives at school and checks in on an attendance app. For part of the day, students work independently, using iPads and Chromebooks, on “playlists” of activities that teachers have selected to match their personal goals. Data about each student’s progress is captured for teachers’ later review. Classrooms are recorded, and teachers can flag important moments by pressing a button, as you might TiVo your favorite television show.

The idea is that all the data from this network of schools will be woven into a smart centralized operating system that teachers will be able to use to design effective and personalized instruction. There is even a recommendation engine built in.

 

Opinion: Apple and IBM have big data plans for education— from computerworld.com by Jonny Evans
Apple and IBM are developing solutions that underpin a future of personalized mobile learning that lasts a lifetime.

Excerpt:

Apple and IBM have been developing the “Student Achievement App” for several months and this is due to enter real world tests this year. The partners recently began approaching US school districts to trial the new technologies. For example, in June a large delegation of Apple and IBM folk met with the Coppell ISD Board of Trustees.

They discussed a proposed partnership between IBM, Apple and CISD to develop these solutions, which are described as “content analytics for student learning”, according to the meeting minutes.

 

From DSC:
One paragraph reads:

It’s no surprise Apple wants to do what it can to improve the education industry. Co-founder Steve Jobs was famously frustrated with the way the sector works in the US. Speaking to Fortune, Denise Young Smith, Apple’s vice president of human resources said Apple CEO Tim Cook is also committed to and involved in the company’s educational technology programs. “Education and learning is our legacy but Tim goes above and beyond,” she says.

Though I’m a huge fan of Apple, I’d have to disagree here. I’m much more skeptical/dubious as to whether Apple’s leadership is as committed to education as they once were; and if they still are, it hasn’t been showing much these last few years. Instead, they’ve let Google make major inroads on this turf; to the point that I would even say that Google is blowing Apple out of the water in this space.

So from my edtech-based perspective, Apple has dropped the ball on education in recent years — instead, leadership focused far more on the iPhone, music, and other consumer-oriented goods and services. From a business standpoint, I get it. They’re the largest company in the world (by market cap) and their strategies are clearly working for them.

That said, I am encouraged when I see items like the one mentioned above and I hope that such education-related projects/endeavors — and the budgets and resources allocated to them — play a larger role at Apple in the future.

 

10 C-Suite jobs of the future — from fastcompany.com by Jared Lindzon; with thanks to Norma Owen for posting this on her Future Workforce newsletter
Step aside, chief innovation officers, and make way for chief automation officers and chief freelance relationship officers.

Excerpts:

With questions about the future of middle management, many believe that corporations will soon beef up their core leadership teams, allowing them to keep foundational business knowledge close to the top while delegating the increasingly complex attributes of the modern organization to in-house, executive-level experts.

These changes are expected to bring a slew of new positions into the C-suite…

With many considering a significant expansion of the C-suite imminent, here are a few new titles that we may see added in the near future:

  • Chief Ecosystem Officer
  • Chief User Experience Officer
  • Chief Automation Officer
  • Chief Freelance Relationship Officer
  • Chief Intellectual Property Officer
  • Chief Data Officer
  • Chief Privacy Officer
  • Chief Compliance Officer
  • …and others
 

So you want to be a data scientist: A guide for college grads — from datanami.com by Alex Woodie

Excerpt:

The first piece of advice for budding data scientists is not to get frustrated by the job requirements. No recent college grad can fill is simultaneously a math/statistics genius, an expert in marketing/derivatives /cybersecurity, and a pro Python/Java/R coder. (Hint: That’s why data scientists are called unicorns—because they don’t exist!)

“There are many skills under the umbrella of data science, and we should not expect any one single person to be a master of them all,” says Kirk Borne, a data scientist with Booz Allen Hamilton. “The best solution to the data science talent shortage is a team of data scientists. So I suggest that you become expert in two or more skill areas, but also have a working knowledge of the others.”

According to Borne, you’ll do well by yourself to bone up on core data science skills such as machine learning, information retrieval, statistics, and data and information visualization. You’ll also want to know your way around a databases and data structures and have at least some programming languages under your belt, such as Python, R, SAS, or Spark. Familiarity with graph analysis, natural language processing, and optimization also looks good on your data science resume, as do data modeling and simulation.

“The good news for physics, biology, astronomy, chemistry, and other science students is that they can easily translate their science skills into a data science profession,” he says.

 

IBM announces major commitment to advance Apache®Spark™, calling it potentially the most significant open source project of the next decade — from ibm.com
IBM joins Spark community, plans to educate more than 1 million data scientists

Excerpt:

ARMONK, NY – 15 Jun 2015: IBM (NYSE:IBM) today announced a major commitment to Apache®Spark™, potentially the most important new open source project in a decade that is being defined by data. At the core of this commitment, IBM plans to embed Spark into its industry-leading Analytics and Commerce platforms, and to offer Spark as a service on IBM Cloud. IBM will also put more than 3,500 IBM researchers and developers to work on Spark-related projects at more than a dozen labs worldwide; donate its breakthrough IBM SystemML machine learning technology to the Spark open source ecosystem; and educate more than one million data scientists and data engineers on Spark.

 

The Internet of Things will give rise to the algorithm economy — from blogs.gartner.com by Peter Sondergaard

Excerpt:

It’s hard to avoid. Almost every CEO’s conversation about how IT is driving innovation inevitably comes back to the potential of big data. But data is inherently dumb. It doesn’t actually do anything unless you know how to use it. And big data is even harder to monetize due to the sheer complexity of it.

Data alone is not going to be the catalyst for the next wave of IT-driven innovation. The next digital gold rush will be focused on how you do something with data, not just what you do with it. This is the promise of the algorithm economy.

Algorithms are already all around us. Consider the driver-less car. Google’s proprietary algorithm is the connective tissue that combines the software, data, sensors and physical asset together into a true leap forward in transportation. Consider high frequency trading. It’s a trader’s unique algorithm that drives each decision that generates higher return than their competitors, not the data that it accesses. And while we’re talking about Google, what makes it one of the most valuable brands in the world? It isn’t data; it’s their most closely guarded secret, their algorithms.

A brave new world of opportunities
Where does this ultimately lead? Software that thinks. Software that does. Cognitive software that drives autonomous machine-to-machine interactions. Dare I say artificial intelligence? I dare. I did.

 

From DSC:
Besides Training/L&D departments and those developing strategy & vision within the corporate world…Provosts Offices take note. Computer Science programs take note. Interested students take note. Those who want to take a right turn in their careers take note.

 

What’s next? GM predicts jobs of the future — from media.gm.com; with thanks to Norma Owen for the resource
Top 10 jobs of the future that will drive exciting technologies

Excerpt:

  • Electrical engineers
  • Analytics expert
  • Interaction designers
  • Web programmer
  • Autonomous driving engineer
  • Customer care experts
  • Sustainability integration expert
  • Industrial engineer
  • 3D Printing engineer
  • Alternative propulsion engineer

 

 

 

What work will look like in 2025 — from fastcompany.com by Gwen Moran
The experts weigh in on the future of work a decade from now.

Excerpt (emphasis):

Seismic Shift In Jobs
The jobs picture either delivers on technology’s promise or plunges us into a dystopian future. The same interconnected technology that will change how goods and services are delivered will “hollow out” a number of skilled jobs, Brynjolfsson says. Clerical work, bookkeeping, basic paralegal work, and even some types of reporting will be increasingly automated, contracting the number of jobs available and causing a drop in wages. And while more technology might create new and different types of jobs, so far we’ve seen more job loss than creation in these areas, he says.

Who wins? Specialists, the creative class, and people who have jobs that require emotional intelligence like salespeople, coaches, customer-service specialists, and people who create everything from writing and art to new products, platforms and services, Brynjolfsson says. Jobs in health care, personal services, and other areas that are tough to automate will also remain in demand, as will trade skills and science, technology and mathematics (STEM) skills, says Mark J. Schmit, PhD, executive director of the Society of Human Resource Management (SHRM) Foundation in Alexandria, Virginia.

However, this winner/loser scenario predicts a widening wealth gap, Schmit says. Workers will need to engage in lifelong education to remain on top of how job and career trends are shifting to remain viable in an ever-changing workplace, he says.

 

 

 

 

FutureDigitalLearningDede-Adobe-April2015

 

From DSC:
Chris uses ecoMOBILE and ecoMUVE to highlight the powerful partnerships that can exist between tools and teachers — to the benefits of the students, who can enjoy personalized learning that they can interact with.  Pedagogical approaches such as active learning are discussed and methods of implementing active learning are touched upon.

Chris pointed out the National Research Council’s book from 2012 entitled, “Education for Life and Work: Developing Transferable Knowledge & Skills in the 21st Century” as he spoke about the need for all of us to be engaged in lifelong learning (Chris uses the term “life-wide” learning).

Also, as Chris mentioned, we often teach as we were taught…so we need communities that are able to UNlearn as well as to learn.

 

 

ecomobile-april2015

 

Also see:

 

AdobeCreate-YouTubeChannel

 

 

Certifying skills and knowledge: Four scenarios on the future of credentials — from knowledgeworks.org by Jason Swanson

Excerpts:

Disruptions to the education system and employment sector are changing what it means to acquire knowledge and skills. Fundamental changes in how we educate learners promise to change how we credential learning. In turn, changes to the way we work could alter the value placed on credentials and how individuals earn them.

This paper considers trends in the education and employment sectors to explore four possible scenarios reflecting how credentials might reflect individuals’ knowledge and skills in ten years’ time.

Exploring the Future of Credentials
In order to explore what credentials might look like in ten years, this paper considers four scenarios for the future of credentials:

A baseline future, “All Roads Lead to Rome,” imagines a future in which degrees awarded by the K-12 and post-secondary sectors still serve as the dominant form of credentials, but there are many roads toward gaining those credentials, such as diverse
forms of school and educational assessments.

An alternative future, “The Dam Breaks,” explores a future in which the employment sector accepts new forms of credentials, such as micro-credentials, on a standalone basis, leading to major shifts in both the K-12 and post-secondary sectors and new relationships between the academic and working worlds.

 

TheDamBreaksScenario-SwansonApril2015

 

A second alternative future, “Every Experience a Credential,” considers what credentials might look like if new technologies enabled every experience to be tracked and catalogued as a form of credential for both students and employees.

A wild card scenario, “My Mind Mapped,” imagines a future in which breakthroughs in both the mapping and tracking of brain functions have created a new type of credential reflecting students’ cognitive abilities and social and emotional skills.

Each scenario in this paper reflects different drivers of change and a different set of fundamental assumptions about how changes affecting credentials might play out across the K-12, post-secondary, and employment sectors.

 

 

From DSC:
I appreciate Jason’s futurist approach here and his use of scenarios. Such an approach helps stimulate our thinking about the potential “What if’s” that could occur — and if they did occur, what would our game plan be for addressing each one of these scenarios?

 

————-

 

A related addendum on 4/24/15:

 

Excerpt:

If you were an academic institution, you might feel a little bit threatened. Over 60% of organisations now believe that the crown jewel of traditional educators – certifications and diplomas – is about to be dethroned by a new uprising: Digital Badges. That’s the finding of research by Extreme Networks on the current adoption of Digital Badges and prospects for the future.

 

13 new trends in Big Data and Data Science — from bigdatanews.com by Mike Beneth

Excerpt:

  1. The rise of data plumbing, to make big data run smoothly, safely, reliably, and fast through all “data pipes” (Internet, Intranet, in-memory, local servers, cloud, Hadoop clusters etc.), optimizing redundancy, load balance, data caching, data storage, data compression, signal extraction, data summarization and more. We bought the domain name DataPlumbing.com last week.
  2. The rise of the data plumber, system architect, and system analyst (a new breed of engineers and data scientists), a direct result of the rise of data plumbing
  3. Use of data science in unusual fields such as astrophysics, and the other way around (data science integrating techniques from these fields)
  4. The death of the fake data scientist.

 

Top online engineering school responds to industry appetite for data science, energy, and cloud expertise — from prnewswire.com
NYU School of Engineering’s 3-course immersion offerings bridge technology skills gap

Excerpt:

NEW YORK, April 16, 2015 /PRNewswire-USNewswire/ — Fortune 500 companies looking to move the talent needle forward are now able to send employees through online certificate courses in data science, power engineering, and data center and cloud technologies. The NYU Polytechnic School of Engineering’s online learning unit has launched certificates of completion in these new three-course immersion programs.

The new Data Science certificate includes three courses in big data analysis, machine learning, and principles of database systems, with substitutions allowed for visualization or cloud computing courses. “Organizations are drowning in data but starving for insights,” said Professor Nasir Memon, chair of the Computer Science and Engineering Department. “The Data Science certificate provides coursework immediately applicable to data scientists working on complex data problems.”

 

 

 

     

 

 

 

 

 

 

For marketers every tech trend hinges on big data and analytics — from forbes.com by Daniel Newman

Excerpt:

But as we talk incessantly about new technologies, we may overlook the fact that it isn’t really technology that’s driving this revolution, but the data and the insights these technologies create. With this data we are able to better understand what interests people and motivates them to engage with a brand and buy their products, and we can also use this data to innovate products that are a perfect fit for our target audience. Let’s discuss how data and analytics underlie the true value of the technology we are so obsessed with.

 

3 big data science trends that will change business software — from diginomica.com by Phil Wainewright
The appliance of big data science to enterprise applications and data is driving rapid innovation in the business software market. Watch these three trends. 

 

From DSC:
Are we developing our students to be able to ride these waves?

 

 

Also see:

 

New from Educause:
Higher Ed IT Buyers Guide

 

HEITBuyersGuideEducauseApril2015

 

Excerpt:

Quickly search 50+ product and service categories, access thousands of IT solutions specific to the higher ed community, and send multiple RFPs—all in one place. This new Buyers Guide provides a central, go-to online resource for supporting your key purchasing decisions as they relate to your campus’s strategic IT initiatives.

Find the Right Vendors for Higher Education’s Top Strategic Technologies

Three of the Top 10 Strategic Technologies identified by the higher education community this year are mobile computing, business intelligence, and business performance analytics.* The new Buyers Guide connects you to many of the IT vendors your campus can partner with in the following categories related to these leading technologies, as well as many more.

View all 50+ product and service categories.

 

What does ‘learning’ have to learn from Netflix? — from donaldclarkplanb.blogspot.com by Donald Clark

Excerpts:

Of course, young people are watching way less TV these days, TV is dying, and when they do watch stuff, it’s streamed, at a time that suits them. Education has to learn from this. I’m not saying that we need to replace all of our existing structures but moving towards understanding what the technology can deliver and what learners want (they shape each other) is worth investigation. Hence some reflections on Netflix.

Areas discussed:

  • Timeshifting
  • Data driven delivery — Netflix’ recommendations engine
  • Data driven content
  • Content that’s accessible via multiple kinds of devices
  • Going global

 

From DSC:
I just wanted to add a few thoughts here:

  1. The areas of micro-credentials, nano-degrees, services like stackup.net, big data, etc. may come to play a role with what Donald is talking about here.
  2. I appreciate Donald’s solid, insightful perspectives and his thinking out loud — some great thoughts in that posting (as usual)
  3. Various technologies seem to be making progress as we move towards a future where learning platforms will be able to deliver a personalized learning experience; as digital learning playlists and educationally-related recommendation engines become more available/sophisticated, highly-customized learning experiences should be within reach.
  4. At a recent Next Generation Learning Spaces Conference, one of the speakers stated, “People are control freaks — so let them have more control.”  Along these lines…ultimately, what makes this vision powerful is having more choice, more control.

 

 

MoreChoiceMoreControl-DSC

 

 

 

Also, some other graphics come to my mind:

 

MakingTVMorePersonal-V-NetTV-April2014

 

EducationServiceOfTheFutureApril2014

 

 

 

Part 3: Google Search will be your next brain — from medium.com by Steven Levy
Inside Google’s massive effort in Deep Learning, which could make already-smart search into scary-smart search

Excerpt:

But about ten years ago, in Hinton’s lab at the University of Toronto, he and some other researchers made a breakthrough that suddenly made neural nets the hottest thing in AI. Not only Google but other companies such as Facebook, Microsoft and IBM began frantically pursuing the relatively minuscule number of computer scientists versed in the black art of organizing several layers of artificial neurons so that the entire system could be trained, or even train itself, to divine coherence from random inputs, much in a way that a newborn learns to organize the data pouring into his or her virgin senses. With this newly effective process, dubbed Deep Learning, some of the long-standing logjams of computation (like being able to see, hear, and be unbeatable at Breakout) would finally be untangled. The age of intelligent computers systems?—?long awaited and long feared?—?would suddenly be breathing down our necks. And Google search would work a whole lot better.

This breakthrough will be crucial in Google Search’s next big step: understanding the real world to make a huge leap in accurately giving users the answers to their questions as well as spontaneously surfacing information to satisfy their needs. To keep search vital, Google must get even smarter.

This is very much in character for the Internet giant. From its earliest days, the company’s founders have been explicit that Google is an artificial intelligence company. It uses its AI not just in search?—?though its search engine is positively drenched with artificial intelligence techniques?—?but in its advertising systems, its self-driving cars, and its plans to put nanoparticles in the human bloodstream for early disease detection.

Indeed, as of now, all Google’s deep learning work has yet to make a big mark on Google search or other products. But that’s about to change.

 

Also see the other parts in this series:

Part 1: The never ending search

Excerpt:

Google’s flagship product has been part of our lives for so long that we take it for granted. But Google doesn’t. Part One of a study of Search’s quiet transformation.

 

Part 2: How Google knows what you want to know
Eight times a day Google asks test subjects about their information needs. Their replies can be sobering.

Excerpt:

Google search really isn’t threatened by competition from other search engines. But the people on the search team constantly worry that they may be falling short in satisfying the needs of their users. To address that problem, of course, Google needs to know what those needs are. One way to do this is by examining the logs to see what queries are unsatisfied. But there are lots of things people want to know that they aren’t asking Google about.

How does Google know what those needs are?

It asks them.

Every year since 2011 Google has run an annual study to learn what people really, really want to know, whether it’s something Google provides or not. It’s called Daily Information Needs, but the psychologists at Google involved with the project just call it DIN.

 

Part 4: The Deep Mind of Demis Hassabis — from medium.com by Steven Levy
Google’s prize AI prodigy tells all. In the race to recruit the best AI talent, Google scored a coup by getting the team led by a former video game guru and chess prodigy

Excerpt:

From the day in 2011 that Demis Hassabis co-founded DeepMind—with funding by the likes of Elon Musk—the UK-based artificial intelligence startup became the most coveted target of major tech companies. In June 2014, Hassabis and his co-founders, Shane Legg and Mustafa Suleyman, agreed to Google’s purchase offer of $400 million. Late last year, Hassabis sat down with Backchannel to discuss why his team went with Google—and why DeepMind is uniquely poised to push the frontiers of AI. The interview has been edited for length and clarity.

 

 

 

Addendum on 3/16/15:

 

DeepLearning-Moz-March2015

 

 

Cognitoy-ElementalPath-March2015
CognitoyFramed-March2015

 

 

From DSC:
Given the above…what are the ramifications of that in our/your work?

 

 

Also see:

 

 

A related addendum on 3/11/15
Look at the different expectations of the generations found in this article:

 

A related addendum on 3/17/15:

Excerpt:
The overall goal for DragonBot (which, as far as I can tell, is a common platform used for many different projects) is to develop “personalized learning companions” for children. In other words, MIT is finding ways in which robots like DragonBot can effectively help kids learn.

DragonBot isn’t intended to work like that IBM Watson-based dinosaur robot; it’s not a primary source of knowledge, and it’s not actively teaching a whole bunch of new facts to kids who use it. Rather, DragonBot is intended to help with the process of learning itself, encouraging kids to be interactively engaged in whatever they happen to be learning about.

 

 
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