Introducing several new ideas to provide personalized, customized learning experiences for all kinds of learners! [Christian]

From DSC:
I have often reflected on differentiation or what some call personalized learning and/or customized learning. How does a busy teacher, instructor, professor, or trainer achieve this, realistically?

It’s very difficult and time-consuming to do for sure. But it also requires a team of specialists to achieve such a holy grail of learning — as one person can’t know it all. That is, one educator doesn’t have the necessary time, skills, or knowledge to address so many different learning needs and levels!

  • Think of different cognitive capabilities — from students that have special learning needs and challenges to gifted students
  • Or learners that have different physical capabilities or restrictions
  • Or learners that have different backgrounds and/or levels of prior knowledge
  • Etc., etc., etc.

Educators  and trainers have so many things on their plates that it’s very difficult to come up with _X_ lesson plans/agendas/personalized approaches, etc.  On the other side of the table, how do students from a vast array of backgrounds and cognitive skill levels get the main points of a chapter or piece of text? How can they self-select the level of difficulty and/or start at a “basics” level and work one’s way up to harder/more detailed levels if they can cognitively handle that level of detail/complexity? Conversely, how do I as a learner get the boiled down version of a piece of text?

Well… just as with the flipped classroom approach, I’d like to suggest that we flip things a bit and enlist teams of specialists at the publishers to fulfill this need. Move things to the content creation end — not so much at the delivery end of things. Publishers’ teams could play a significant, hugely helpful role in providing customized learning to learners.

Some of the ways that this could happen:

Use an HTML like language when writing a textbook, such as:

<MainPoint> The text for the main point here. </MainPoint>

<SubPoint1>The text for the subpoint 1 here.</SubPoint1>

<DetailsSubPoint1>More detailed information for subpoint 1 here.</DetailsSubPoint1>

<SubPoint2>The text for the subpoint 2 here.</SubPoint2>

<DetailsSubPoint2>More detailed information for subpoint 2 here.</DetailsSubPoint2>

<SubPoint3>The text for the subpoint 3 here.</SubPoint3>

<DetailsSubPoint3>More detailed information for subpoint 3 here.</DetailsSubPoint1>

<SummaryOfMainPoints>A list of the main points that a learner should walk away with.</SummaryOfMainPoints>

<BasicsOfMainPoints>Here is a listing of the main points, but put in alternative words and more basic ways of expressing those main points. </BasicsOfMainPoints>

<Conclusion> The text for the concluding comments here.</Conclusion>

 

<BasicsOfMainPoints> could be called <AlternativeExplanations>
Bottom line: This tag would be to put things forth using very straightforward terms.

Another tag would be to address how this topic/chapter is relevant:
<RealWorldApplication>This short paragraph should illustrate real world examples

of this particular topic. Why does this topic matter? How is it relevant?</RealWorldApplication>

 

On the students’ end, they could use an app that works with such tags to allow a learner to quickly see/review the different layers. That is:

  • Show me just the main points
  • Then add on the sub points
  • Then fill in the details
    OR
  • Just give me the basics via an alternative ways of expressing these things. I won’t remember all the details. Put things using easy-to-understand wording/ideas.

 

It’s like the layers of a Microsoft HoloLens app of the human anatomy:

 

Or it’s like different layers of a chapter of a “textbook” — so a learner could quickly collapse/expand the text as needed:

 

This approach could be helpful at all kinds of learning levels. For example, it could be very helpful for law school students to obtain outlines for cases or for chapters of information. Similarly, it could be helpful for dental or medical school students to get the main points as well as detailed information.

Also, as Artificial Intelligence (AI) grows, the system could check a learner’s cloud-based learner profile to see their reading level or prior knowledge, any IEP’s on file, their learning preferences (audio, video, animations, etc.), etc. to further provide a personalized/customized learning experience. 

To recap:

  • “Textbooks” continue to be created by teams of specialists, but add specialists with knowledge of students with special needs as well as for gifted students. For example, a team could have experts within the field of Special Education to help create one of the overlays/or filters/lenses — i.e., to reword things. If the text was talking about how to hit a backhand or a forehand, the alternative text layer could be summed up to say that tennis is a sport…and that a sport is something people play. On the other end of the spectrum, the text could dive deeply into the various grips a person could use to hit a forehand or backhand.
  • This puts the power of offering differentiation at the point of content creation/development (differentiation could also be provided for at the delivery end, but again, time and expertise are likely not going to be there)
  • Publishers create “overlays” or various layers that can be turned on or off by the learners
  • Can see whole chapters or can see main ideas, topic sentences, and/or details. Like HTML tags for web pages.
  • Can instantly collapse chapters to main ideas/outlines.

 

 

Reflections on “Inside Amazon’s artificial intelligence flywheel” [Levy]

Inside Amazon’s artificial intelligence flywheel — from wired.com by Steven Levy
How deep learning came to power Alexa, Amazon Web Services, and nearly every other division of the company.

Excerpt (emphasis DSC):

Amazon loves to use the word flywheel to describe how various parts of its massive business work as a single perpetual motion machine. It now has a powerful AI flywheel, where machine-learning innovations in one part of the company fuel the efforts of other teams, who in turn can build products or offer services to affect other groups, or even the company at large. Offering its machine-learning platforms to outsiders as a paid service makes the effort itself profitable—and in certain cases scoops up yet more data to level up the technology even more.

It took a lot of six-pagers to transform Amazon from a deep-learning wannabe into a formidable power. The results of this transformation can be seen throughout the company—including in a recommendations system that now runs on a totally new machine-learning infrastructure. Amazon is smarter in suggesting what you should read next, what items you should add to your shopping list, and what movie you might want to watch tonight. And this year Thirumalai started a new job, heading Amazon search, where he intends to use deep learning in every aspect of the service.

“If you asked me seven or eight years ago how big a force Amazon was in AI, I would have said, ‘They aren’t,’” says Pedro Domingos, a top computer science professor at the University of Washington. “But they have really come on aggressively. Now they are becoming a force.”

Maybe the force.

 

 

From DSC:
When will we begin to see more mainstream recommendation engines for learning-based materials? With the demand for people to reinvent themselves, such a next generation learning platform can’t come soon enough!

  • Turning over control to learners to create/enhance their own web-based learner profiles; and allowing people to say who can access their learning profiles.
  • AI-based recommendation engines to help people identify curated, effective digital playlists for what they want to learn about.
  • Voice-driven interfaces.
  • Matching employees to employers.
  • Matching one’s learning preferences (not styles) with the content being presented as one piece of a personalized learning experience.
  • From cradle to grave. Lifelong learning.
  • Multimedia-based, interactive content.
  • Asynchronously and synchronously connecting with others learning about the same content.
  • Online-based tutoring/assistance; remote assistance.
  • Reinvent. Staying relevant. Surviving.
  • Competency-based learning.

 

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

 

 

 

 

 

 

 

We’re about to embark on a period in American history where career reinvention will be critical, perhaps more so than it’s ever been before. In the next decade, as many as 50 million American workers—a third of the total—will need to change careers, according to McKinsey Global Institute. Automation, in the form of AI (artificial intelligence) and RPA (robotic process automation), is the primary driver. McKinsey observes: “There are few precedents in which societies have successfully retrained such large numbers of people.”

Bill Triant and Ryan Craig

 

 

 

Also relevant/see:

Online education’s expansion continues in higher ed with a focus on tech skills — from educationdive.com by James Paterson

Dive Brief:

  • Online learning continues to expand in higher ed with the addition of several online master’s degrees and a new for-profit college that offers a hybrid of vocational training and liberal arts curriculum online.
  • Inside Higher Ed reported the nonprofit learning provider edX is offering nine master’s degrees through five U.S. universities — the Georgia Institute of Technology, the University of Texas at Austin, Indiana University, Arizona State University and the University of California, San Diego. The programs include cybersecurity, data science, analytics, computer science and marketing, and they cost from around $10,000 to $22,000. Most offer stackable certificates, helping students who change their educational trajectory.
  • Former Harvard University Dean of Social Science Stephen Kosslyn, meanwhile, will open Foundry College in January. The for-profit, two-year program targets adult learners who want to upskill, and it includes training in soft skills such as critical thinking and problem solving. Students will pay about $1,000 per course, though the college is waiving tuition for its first cohort.

 

 

 

NEW: The Top Tools for Learning 2018 [Jane Hart]

The Top Tools for Learning 2018 from the 12th Annual Digital Learning Tools Survey -- by Jane Hart

 

The above was from Jane’s posting 10 Trends for Digital Learning in 2018 — from modernworkplacelearning.com by Jane Hart

Excerpt:

[On 9/24/18],  I released the Top Tools for Learning 2018 , which I compiled from the results of the 12th Annual Digital Learning Tools Survey.

I have also categorised the tools into 30 different areas, and produced 3 sub-lists that provide some context to how the tools are being used:

  • Top 100 Tools for Personal & Professional Learning 2018 (PPL100): the digital tools used by individuals for their own self-improvement, learning and development – both inside and outside the workplace.
  • Top 100 Tools for Workplace Learning (WPL100): the digital tools used to design, deliver, enable and/or support learning in the workplace.
  • Top 100 Tools for Education (EDU100): the digital tools used by educators and students in schools, colleges, universities, adult education etc.

 

3 – Web courses are increasing in popularity.
Although Coursera is still the most popular web course platform, there are, in fact, now 12 web course platforms on the list. New additions this year include Udacity and Highbrow (the latter provides daily micro-lessons). It is clear that people like these platforms because they can chose what they want to study as well as how they want to study, ie. they can dip in and out if they want to and no-one is going to tell them off – which is unlike most corporate online courses which have a prescribed path through them and their use is heavily monitored.

 

 

5 – Learning at work is becoming personal and continuous.
The most significant feature of the list this year is the huge leap up the list that Degreed has made – up 86 places to 47th place – the biggest increase by any tool this year. Degreed is a lifelong learning platform and provides the opportunity for individuals to own their expertise and development through a continuous learning approach. And, interestingly, Degreed appears both on the PPL100 (at  30) and WPL100 (at 52). This suggests that some organisations are beginning to see the importance of personal, continuous learning at work. Indeed, another platform that underpins this, has also moved up the list significantly this year, too. Anders Pink is a smart curation platform available for both individuals and teams which delivers daily curated resources on specified topics. Non-traditional learning platforms are therefore coming to the forefront, as the next point further shows.

 

 

From DSC:
Perhaps some foreshadowing of the presence of a powerful, online-based, next generation learning platform…?

 

 

 

100 things students can create to demonstrate what they know — from teachthought.com

Excerpt:

[Here] is a diverse list adapted from resources found at fortheteachers.org of potential student products or activities learners can use to demonstrate their mastery of lesson content. The list also offers several digital tools for students to consider using in a technology-enriched learning environment.

 

 

 

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.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

“The 2017 Readers’ Choice Awards” in K-12 — from thejournal.com by David Nagel

 

“Google was the absolute winner overall.”

 

Excerpt:

In an open-ended question asking for educators’ favorite technologies currently in use at their schools, respondents overwhelmingly chose Google’s G Suite for Education as their top overall pick.

The top overall categories were:

  • Mobile devices
  • Interactive whiteboards/displays/projectors
  • eLearning/learning management systems and reading software — Lexia Learning’s Core5 scored big in the reading software area, while Google Classroom, Schoology, Moodle, Canvas, and Blackboard Learn were often mentioned in the LMS area

 

 

 

 

Also, there was an article in there on learning spaces. Some ideas mentioned include:

 

 

 

 

 

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.

 

 

 

 

Smartwatches Deemed Least Valuable Technology in the Classroom — from campustechnology.com by Rhea Kelly
In our second annual Teaching with Technology Survey, faculty revealed what technologies they use in the classroom, the devices they most value, what they wish for and more.

Excerpts:

Smartwatches may be one of the hottest gadgets in the consumer market — making up nearly a third of all wearables sales this year — but the climate in the classroom is noticeably cooler for the wrist-worn devices. In our 2017 Teaching with Technology Survey, smartwatches came in dead last in the list of technologies faculty consider essential or valuable for teaching and learning. Just 9 percent of faculty called the devices “valuable” (an increase from 5 percent in 2016), and not a one deemed them “essential.” What’s more, 9 percent of respondents considered smartwatches “detrimental.”

When we asked faculty what computing devices were most valuable for teaching and learning, laptops came out on top, considered “essential” by 54 percent of respondents (up from 49 percent in 2016). Workstations (defined as higher-end computers with faster processors, more RAM, more storage and dedicated graphics cards) came in second, followed by all-in-one computers, traditional desktops and detachable tablets. (The lineup was similar last year.)

 

 

 
 
 

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