How to be an ed tech futurist — from campustechnology.com by Bryan Alexander
While no one can predict the future, these forecasting methods will help you anticipate trends and spur more collaborative thinking.

Excerpts:

Some of the forecasting methods Bryan mentions are:

  • Trend analysis
  • Environmental scanning
  • Scenarios
  • Science fiction

 

 

 

 

From DSC:
I greatly appreciate the work that Bryan does — the topics that he chooses to write about, his analyses, comments, and questions are often thought-provoking. I couldn’t agree more with Bryan’s assertion that forecasting needs to become more realized/practiced within higher education. This is especially true given the exponential rate of change that many societies throughout the globe are now experiencing.

We need to be pulse-checking a variety of landscapes out there, to identify and put significant trends, forces, and emerging technologies on our radars. The strategy of identifying potential scenarios – and then developing responses to those potential scenarios — is very wise.

 

 

 

 

 

 

 

 

 

 

 

 

 

Updating Education for the Evolving Job Market: Learning at the Pace of Life and Work — from huffingtonpost.com by Sophie Wade

Excerpt (emphasis DSC):

A technology-stimulated, connected, and accelerated marketplace is generating different roles and additional skills requirements for us as workers. The traditional model of completing our lifelong education needs before we enter the workforce is now obsolete. On-the-job experience must now be supplemented as business and technological requirements evolve significantly and rapidly. Compelling new multilevel learning options are emerging to cater to the new necessity of updating important knowledge and capabilities at work. Many new offerings are online and modular in order to be accessible and flexible, giving labor force participants greater opportunity to remain relevant and competitive.

Since the beginning of the Industrial Era, evolution typically occurred from generation to generation. New developments were adopted by incoming cohorts, adding to and then replacing well-established workers’ existing practices of which could be phased out gradually. However, the exponential pace that is characteristic of the Fourth Industrial Revolution is requiring modifications to be absorbed and adapted within a generation accompanied by frequent incremental updates and revisions. Innovative learning models and modules that target incoming and existing working populations are being built out to respond to business-related requirements as new fields, disciplines, and roles appear and are established.

I talked to Anant Agarwal, CEO and Founder of edX, and Professor of Electrical Engineering and Computer Science at MIT about the situation for new workforce entrants and the future education of workers. He spoke of what he called “MOOC 2.0” as the next phase of evolution of this high-profile MOOC (Massively Open Online Course) platform and the strategic rationale and content of edX’s new MicroMasters program offerings.

 

 

As a member of the International Education Committee, at edX we are extremely aware of the changing nature of work and jobs. It is predicted that 50 percent of current jobs will disappear by 2030.

Anant Agarwal, CEO and Founder of edX, and
Professor of Electrical Engineering and Computer Science at MIT

 

From DSC:
We are moving towards providing up-to-date, relevant “streams of content” (which will in many cases represent unbundled content/courses). Mark my words, that’s the future that we’re heading for — and the future that we’ll need to successfully adapt to the new, exponential pace of change. Organizations offering such streams will be providing a valuable service in terms identifying, presenting, curating the most relevant, up-to-date content.

 

 

 

 

 

 

 

 

 

 

Udacity Launches a ‘Learn ARKit’ Course Created in Collaboration with Unity — from roadtovr.com by Scott Hayden

Excerpt:

With ARKit already baked into the mobile operating system of “hundreds of millions of iPhones and iPads,” the massive potential install base means there’s plenty of reasons for developers to start making new augmented reality apps for Apple’s App Store. Now Udacity, the for-profit online education site that was spawned from free Stanford University computer science classes, has created a course that says will take you one month to complete so you can start making your own AR apps for iOS.

 

 

From DSC:
Again, how many of these types of courses/programs are in the works right now throughout traditional institutions of higher education? My guess? Very few.

 

 

What’s keeping us from being more responsive?

 

 

 

 

 

Excerpt:

The Top 200 Tools for Learning 2017 (11th Annual Survey) has been compiled by Jane Hart of the Centre for Learning & Performance Technologies from the votes of 2,174 learning professionals worldwide, together with 3 sub-lists

  • Top 100 Tools for Personal & Professional Learning (PPL)
  • Top 100 Tools for Workplace Learning (WPL)
  • Top 100 Tools for Education (EDU)

 

Excerpt from the Analysis page (emphasis DSC):

Here is a brief analysis of what’s on the list and what it tells us about the current state of personal learning, workplace learning and education.

Some facts

Some observations on what the Top Tools list tells us personal and professional learning
As in previous years, individuals continue to using a wide variety of:

  • networks, services and platforms for professional networking, communication and collaboration
  • web resources and courses for self-improvement and self-development
  • tools for personal productivity

All of which shows that many individuals have become highly independent, continuous modern professional learners – making their own decisions about what they need to learn and how to do it.

 

 

 

 

Amazon and Codecademy team up for free Alexa skills training — from venturebeat.com by Khari Johnson

Excerpt:

Amazon and tech training app Codecademy have collaborated to create a series of free courses. Available today, the courses are meant to train developers as well as beginners how to create skills, the voice apps that interact with Alexa.

Since opening Alexa to third-party developers in 2015, more than 20,000 skills have been made available in the Alexa Skills Store.

 

 

 

 

Udacity adds a new ‘Intro to Self-Driving Cars’ Nanodegree — from techcrunch.com by Darrell Etherington

Excerpt:

You likely won’t be surprised when I tell you that building a self-driving car is difficult and complex. Udacity has tried to help address that difficulty with flexible, online education for self-driving engineers through its Self-Driving Cars Nanodegree program, and now it’s expanding its offerings with a new Intro to Self-Driving Cars Nanodegree being introduced at TechCrunch Disrupt SF 2017 that’s designed to help funnel more talent into the intermediate-level course, and from there into the workforce, where demand is incredibly strong and growing.

Udacity’s Nanodegrees are designed from the start to help democratize education in areas of tech where there’s a strong appetite from the employer side, and not nearly enough talent to go around. But what the company found with its self-driving material was that it was actually quite advanced compared to the skill level of interested students, so it set out to create a kind of fundamentals introductory program to help make sure more could enter the main course with a better foundation.

Also new to this program, and again in the spirit of increasing access to education for these very high demand skills, Udacity is teaming up with Lyft, which will be providing 400 full scholarships (covering the total $800 value) for the Intro program. Applications for those open today, too.

 

 

 

Under the Hood: Learning Design Behind Georgia Tech’s Degrees at Scale — from evolllution.com by Shabana Figueroa and Yakut Gazi

Excerpt:

Rolling out the MM program in May and the degree program in August meant design coordination and creation of eight new online courses in less than a year. We needed a new approach that employed strategies for efficiency and effectiveness.

The Learning Design Team
GTPE’s learning design team partners with faculty members to develop their online courses from start to end, providing the heavy lifting for course production. A director of learning design oversees both the instructional design and production aspects of the course production across the entire program. This cross-functional team approach eliminates the silos created by independent instructional design and studio production teams, which in turn, minimizes hand-off points, decreases friction among teams, allows for long-term thinking that leads to smarter course design and development decisions, provides fluidity of talent and roles within the team, and fuels productivity.

…the paradigm shift to a learner-focused, team-based approach to course production and delivery, and collaboration of campus partners and groups…

 

 

From DSC:
Note the use of a team-based approach here. I think that the team-based approach will be the most beneficial to the world at large. Those teams will be able to deliver a high-quality learning experience, with high production values and carefully planned/crafted instructional designs. 

 



Also see:

Learning How to Learn: Anatomy of a good MOOC — from linkedin.com by Bill Ferster

Excerpts:

Barbara Oakley’s MOOC, Learning How to Learn [2] is the exception to this trend. It is well-produced, informative, and fully embraces the new medium. With over 2 million registered students and completion rates of over 20% [3], (the average MOOC completion rate is 5%), Learning How to Learn is clearly resonating with its audience.

The question is why is it so popular? Intrigued, I enrolled the short MOOC to understand why it was so popular, and what lessons it might have for other MOOC authors to make their offerings more effective their “filmed plays.”

Oakley has clearly bucked the overall MOOC trend and has made good use of the inexpensive technologies with well-lit scenes that are clearly edited and make use of the green screen overlay technologies found in her Adobe Premiere video editor. She used a large teleprompter to ensure a fluid delivery of her message and high-quality audio.

Learning to Learn is effective because Oakley put a significant amount of effort making it effective. Good content, coupled with high production values, and sound pedagogy take time to produce and clearly pays off in the final product.

 



 

 

Google and Udacity offer scholarships for 75,000 aspiring developers — from thenextweb.com

Excerpt:

Google has announced its plans to extend its partnership with Udacity to offer 75,000 Android scholarships for aspiring developers and data scientists seeking to pursue careers in the digital field.

The initiative builds on the company’s two-year long collaboration with Udacity, which granted 1,000 and 10,000 scholarships for passionate newbie coders in 2015 and 2016, respectively. German media giant Bertelsmann will also be contributing to this effort.

 

 

Also see:

 

 

Making a MOOC — from harvardmagazine.com by Jonathan Shaw

Excerpts:

Now, as one of a small number of Harvard faculty members each year whose course is selected to become a MOOC (a massive, online, open course), he is about to go global. Just 20 new courses are chosen by a faculty review committee annually, all of them ultimately offered to learners in at least one free version—part of Harvard’s commitment to improve access to education globally through HarvardX (HX), the University’s online course initiative. Hernán’s course is based on Epidemiology (EPI) 289: “Models for Causal Inference,” the core offering he’s taught for 14 years at the Harvard Chan School of Public Health (HSPH). Harvard Magazine accompanied Hernán during the making of his MOOC to find out what it takes to produce one, and how that compares to creating a traditional course.

Faculty members typically spend 96 to 142 hours helping produce and run an eight-week MOOC, according to HarvardX estimates. …But when complete, it will free him from much of the time and expense of traveling to teach this fundamental introductory material.

It takes a team of skilled professionals—HX employs a staff of about 45, including managers, videographers, graphic designers, digital editors, and even a copyright attorney and an accessibility coordinator (who helps make the materials usable for sight- and hearing-impaired learners)—to make each MOOC, at a cost that ranges widely, depending on the nature of the course and the sites of location shoots. This one cost about $100,000 to make.

Among the University’s goals in supporting the production of courses like Hernán’s is maximizing their “reach” as part of “Harvard’s contribution to a rising tide of education globally,” says HX faculty director Robert Lue.

A video lecture therefore becomes a short unit in which to make one point, “not five. Because if I try to make five points, I need 50 minutes.” The hooks—the real-world applications—mean that “I start each lesson by telling students why this is important, why they should keep watching….You are in a competition for attention…

 

“For example, it seems obvious, but there’s only one Miguel Hernán. And he can either teach a class of 70” once a year, “or develop this course that reaches many more around the world and across different disciplines.”

 

 

 

 

 

Video: 4 FAQs about Watson as tutor — from er.educause.edu by Satya Nitta

Excerpt:

How is IBM using Watson’s intelligent tutoring system? So we are attempting to mimic the best practices of human tutoring. The gold standard will always remain one on one human to human tutoring. The whole idea here is an intelligent tutoring system as a computing system that works autonomously with learners, so there is no human intervention. It’s basically pretending to be the teacher itself and it’s working with the learner. What we’re attempting to do is we’re attempting to basically put conversational systems, systems that understand human conversation and dialogue, and we’re trying to build a system that, in a very natural way, interacts with people through conversation. The system basically has the ability to ask questions, to answer questions, to know who you are and where you are in your learning journey, what you’re struggling with, what you’re strong on and it will personalize its pedagogy to you.

There’s a natural language understanding system and a machine learning system that’s trying to figure out where you are in your learning journey and what the appropriate intervention is for you. The natural language system enables this interaction that’s very rich and conversation-based, where you can basically have a human-like conversation with it and, to a large extent, it will try to understand and to retrieve the right things for you. Again the most important thing is that we will set the expectations appropriately and we have appropriate exit criteria for when the system doesn’t actually understand what you’re trying to do.

 

 

 

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