From DSC:
Some very frustrated reflections after reading:

Excerpt:

Right now, boys are falling out of the kindergarten through 12th grade educational pipeline in ways that we can hardly imagine.

 

This situation continues to remind me of the oil spill in the Gulf (2010), where valuable resources spilled into the water untapped — later causing some serious issues:
.

From DSC:
What are we doing?!!! We’ve watched the dropout rates grow — it doesn’t seem we’ve changed our strategies nearly enough! But the point that gets lost in this is that we will all pay for these broken strategies — and for generations to come!  It’s time to seriously move towards identifying and implementing some new goals.

What should the new goals look like? Here’s my take on at least a portion of a new vision for K-12 — and collegiate — education:

  • Help students identify their God-given gifts and then help them build up their own learning ecosystems to support the development of those gifts. Hook them up with resources that will develop students’ abilities and passions.
    .
  • Part of their learning ecosystems could be to help them enter into — and build up — communities of practice around subjects that they enjoy learning about. Those communities could be local, national, or international. (Also consider the creation of personalized learning agents, as these become more prevalent/powerful.)
    .
  • Do everything we can to make learning enjoyable and foster a love of learning — as we need lifelong learners these days.
    (It doesn’t help society much if students are dropping out of K-12 or if people struggle to make it through graduation — only to then harbor ill feelings towards learning/education in general for years to come.  Let’s greatly reduce the presence/usage of standardized tests — they’re killing us!  They don’t seem to be producing long-term positive results. I congratulate the recent group of teachers who refused to give their students such tests; and I greatly admire them for getting rid of a losing strategy.)

    .
  • Give students more choice, more control over what their learning looks like; let them take their own paths as much as possible (provide different ways to meet the same learning objective is one approach…but perhaps we need to think beyond/bigger than that. The concern/fear arises…but how will we manage this? That’s where a good share of our thinking should be focused; generating creative answers to that question.)
    .
  • Foster curiosity and wonder
    .
  • Provide cross-disciplinary assignments/opportunities
    .
  • Let students work on/try to resolve real issues in their communities
    .
  • Build up students’ appreciation of faith, hope, love, empathy, and a desire to make the world a better place. Provide ways that they can contribute.
    .
  • Let students experiment more — encourage failure.
    .

 

From DSC:

In real estate, one hear’s the mantra:
Location. Location. Location.

In higher education, I have it that we’ll be hearing this for a while:
Experimentation. Experimentation. Experimentation.

Consider the following reflections on Steve’ Kolowich’s solid article, The new intelligence (from InsideHigherEd.com)

Excerpt:

And for the largest public university in the country, it is hardly fiction. Arizona State University has become ground zero for data-driven teaching in higher education. The university has rolled out an ambitious effort to turn its classrooms into laboratories for technology-abetted “adaptive learning” — a method that purports to give instructors real-time intelligence on how well each of their students is getting each concept.
.

 

From DSC:
Besides being used in blended learning environments…some predictions:

  • These technologies will become integrated into what MOOCs eventually morph into and provide a significant piece of the assessment/guidance puzzle
  • Such tools will be a part of one’s future learning ecosystem
  • Such tools will be part of interactive, massively open online educationally-related games
  • Such tools will be integrated into personalized learning agents — spiders/recommendation engines that scan the web for relevant items that one needs to complete one’s cognitive gaps in a subject/topic
  • They will be accessible from your living room as well as from your mobile devices
  • They will integrate into web-based learner profiles

It’s the sort of thing I was trying to get at with this graphic from 3 years ago:
.

Like a mechanic...

 

Please don’t misunderstand me, the human mind is far beyond the complexity of an engine. But I still think that there will be more tools & technologies developed that will help the teachers/professors in their efforts to guide students into the knowledge of a discipline.

I beseech the corporate world to get involved more here — and not with the end goal of earning profits — but rather, with the aim of making the world a better place and giving a huge gift to the generations yet born. 

I urge the corporate world to reach into their deep pockets (1.X trillion in cash at this point in time) and team up with our youth/teachers/professors/instructional designers/programmers/etc. to develop sophisticated, educationally-related, engaging games that are relevant to the world that our youth will be growing up in; and/or create interactive simulations that provide more choice/more control to the learners. 

I urge more of the corporate world to join Knewton and Pearson and allocate some significant resources to help develop the next gen learning tools.  I’ll bet that we’ll be amazed at what can be produced! Your daughters, sons, granddaughters, and grandsons will really appreciate the work that you did for them!!!

 

 

From DSC:
I understand that Mr. George Lucas is going to express his generosity in donating the $4.05 billion from the sale of Lucasfilm to education.

Here’s a question/idea that I’d like to put forth to Mr. Lucas (or to the United States Department of Education, or to another interested/committed party):

Would you consider using the $4+ billion gift to build an “Online Learning Dream Team?”

.

Daniel Christian -- The Online Learning Dream Team - as of November 2012

.

 Original image credit (before purchased/edited by DSC)
yobro10 / 123RF Stock Photo

 

 

From DSC:
What do you think? What other “players” — technologies, vendors, skillsets, etc. — should be on this team?

  • Perhaps videography?
  • Online tutoring?
  • Student academic services?
  • Animation?
  • Digital photography?

 

 

Excerpt:

Agarwal believes that education is about to change dramatically. The reason is the power of the Web and its associated data-crunching technologies. Thanks to these changes, it’s now possible to stream video classes with sophisticated interactive elements, and researchers can scoop up student data that could help them make teaching more effective. The technology is powerful, fairly cheap, and global in its reach. EdX has said it hopes to teach a billion students.

.

Which brings me to this graphic:

 

asdfsadf

 

Also see:

 

Embedded ubiquitous learning — from the Upside Learning blog by Abhijit Kadle

Excerpt:

What would ubiquitous learning look like? Well, there isn’t an easy answer to that. It is hard to foresee what will come about personal computing technologies in the next decade. In my eyes, from a learning perspective, there are a few key themes (emphasis DSC):

  1. Discovery and delivery – the ability to use agents that comprehend context, are able to make ‘coherent’ sense of varied data streams to search for information, discover, and provide content – just in time, in the correct context and in the appropriate format.
  2. Machine to Machine communication – While there is no doubt that this will happen, and that the ‘internet of things’ isn’t very far away in the future. One thing I found fascinating is the idea that you could create a ‘learning profile’, an identity that is essentially a digital package of your learning preferences and the contents of your past learning, that can be accessed by machines. This would let the ‘machine’ actually tailor its user interfaces, learning content and the experience itself, and present information in a way that suits the preferences of the human.
  3. Embedded learning – networked learning that is built into every device, every tool, every physical resource humans use; there is no need for specific training; the latest information is available just in time, from authentic sources, judged valuable by network analysis, provided with the right context and assists humans to complete tasks

Establishing Better Collaboration Between the Corporate World and Higher Education -- by Daniel Christian

 

From DSC:
The above article I wrote for evoLLLution.com (for LifeLong Learning) mentions the need for — and the opportunities to build:

  • More streams of content flowing between these two worlds
  • Web-based learner profiles
  • Tools that students can begin using in their collegiate days that they can later tap into long after they’ve graduated
  • Using teams of specialists
  • MOOCs
  • Collaboration between a corporation and an entire classroom
  • and more

 

 

 

 

.

Excerpt from website:

Your Classroom Just Got A Little Bigger. OK, A Lot Bigger.
There are millions of people around the globe with a thirst for educational content but have little available to them. You have tremendous educational resources and a desire to reach more people.
The ClevrU platform offers educators the marketplace to reach across the barriers of today’s classroom and out to the rest of the world.  Our service combines the power of a complete online learning environment with a scalable platform designed to handle from 1 to a billion users while adapting to the users language of choice, their available bandwidth, and their type of mobile device or internet access.
We welcome free, open source material as well as fee based learning programs for which we can provide in country e-commerce support.
.
Excerpt from University? There’s an app for that  — from oncampus.macleans.ca by Cathy Gulli
A Waterloo start-up provides courses on smartphones
For Tushar Singh, the 32-year-old co-founder of ClevrU and chief technology officer, the potential impact of providing education to those who are too poor or isolated to get one locally is what’s driving the company forward. “Education is a lifeline. It doesn’t just change a person, it also changes a community.”

A couple of nice illustrations  from What’s Next for Education: The New Course Ecosystem that depict the need for learning ***ecosystems*** — from yesterday’s presentation by Blackboard’s Katie Blok and Outsell’s Kate Worlock

Description/about the presentation:
A recent survey notes that students are purchasing tablets and mobile devices at a rate far faster than predicted. And, it’s no surprise that the greatest growth sector in education is expected to be in the adoption of digital textbooks, multimedia and tools, a sector that topped the $1 billion dollar mark in 2011. Content is not the only area in higher education undergoing transition. The mission of the learning management system (LMS) seems to be changing also. All types of content will soon be accessible within a single course experience, uniquely delivered by the learning management system. With the LMS as a new channel for digital content, instructors and students both can expect manifold benefits from greater choice in teaching materials to more options for consuming instructional content. During this event, you will hear an insightful view into the evolution of digital technology in the higher education landscape.

.

.
.
.

 

.

 

.
.
From DSC:
I’m not so sure it will be the LMS or CMS that will host all of this…at least not the type of CMS/LMS systems that we know of today. A cloud-based marketplace of educational apps — that save results to cloud-based learner profiles — may be more likely.

Barriers to adoption of online learning systems in U.S. Higher Education - May 1, 2012

 

Excerpt from the preface:

Digital technology has already changed the way colleges and universities function, but no matter how significant those changes feel today, real transformation is just beginning. Every day, a new program in online learning is announced, and on the horizon is the promise of using new adaptive learning technologies —or what we have come to call Interactive Learning Online—to educate more students than ever before at lower cost and with similar or even better learning outcomes.

This Ithaka S+R report is the first in a series that will provide leaders in higher education insight into what has been learned from online learning efforts to date and new research to help them move forward with the development and deployment of more advanced systems in the future.

Many of the lessons in this report can readily be applied locally; that is, they will help leaders make sound decisions for their own institutions. We have also identified two critical issues that if addressed at a system-level, will lead to better outcomes for all: the need for open, shared data on student learning and performance tracked through interactive online learning systems, and the need for investment in the creation of sustainable and customizable platforms for delivering interactive online learning instruction. We hope this report will help to stimulate discussion and planning among leaders on these important topics.

 

Also see:

  • Tempering the Rise of the Machines— from insidehighered.com by Steve Kolowich
    Excerpt (emphasis DSC):
    The report, called “Barriers to Adoption of Online Learning Systems in U.S. Higher Education,” was co-written by Lawrence S. Bacow and William G. Bowen, the former presidents of Tufts and Princeton Universities, respectively, along with several Ithaka analysts. It was bankrolled by the Bill & Melinda Gates Foundation. The report contained little advocacy one way or another; rather, the authors appeared to strive for a dispassionate analysis driven by a general sense that the rise of machine learning is inevitable and universities should be prepared. Their findings were based on interviews with senior administrators at 25 public and private, four-year and two-year colleges, including “deep dive” analyses at five of them.

From DSC:
As Brian Crosby points out in the title of his blog — “Learning is Messy.” 

There is no silver bullet in the world of education that can be used to effectively teach everyone. In fact, if you were to get 100 instructional designers/teachers/professors/instructors/trainers in the same room, you will not be able to find anything close to a strong agreement on what constitutes the best and most effective learning theory as well as the practical implementations of applying that learning theory (even if we were to be talking about the same age range of students). In my Master’s work, I was looking for that silver bullet…but I never found one.

It is very difficult for a professor or a teacher to deliver truly personalized/customized learning to each student in their classroom:

  • How can a teacher consistently know and remember what motivates each particular student?
  • Because so much of learning depends upon prior learning, what “hooks” exist — per student — that he/she can use to hang new information on?
  • Then, what’s the most effective method of delivering the content for each particular student that might shift the content from their working memories to their long-term memories? (And in the process, do so in a way that develops a love for learning that will serve the student well over his lifetime)
  • What’s the best way to assess the learning for each student?
  • Which students cognitive loads are being eaten up due to the nervousness around being assessed?
  • What are the best methods of passing along those learnings onto the students’ future teachers’ for the students’ benefit?

In my estimation, the way we have things setup throughout most K-16 education, this is an impossible task. When there’s typically only 1-2 teachers trying to teach to 20-30 students at a time, how can this type of personalized instruction occur?

However, I believe digital learning and its surrounding tools/ecosystems hold enormous promise for delivering truly customized/personalized learning opportunities.  Such technologies will be able to learn where a student is at, how to motivate them, how fast to push them, and how they best progress through a type of content.  Such tools will provide real-time, learning-related, diagnostic dashboards for professors or teachers to leverage in order to guide and optimize a student’s education.

.

.

So I believe that the promise is there for delivering truly customized/personalized learning opportunities available 24x7x365 — even though we aren’t completely there yet.  But think of the power a teacher would have if he or she had IBM’s Watson AI-based analysis on each student at their disposal! A “guide on the side” using such diagnostic tools could be a ***potent*** ally for a student.*

As such, I see innovative approaches continuing to come to fruition that will harness the power of serious games, analytics, web-based learner profiles, and multimedia-based/interactive learning content. Eventually, a piece of this type of personalized education will enter in via the Smart/Connected TVs of our living rooms…but that’s a post I’m building out for another day in the near future.

.

*Another hope I have here is that such technologies will
enable students to identify and pursue their passions.

 


Some items that reinforced this notion for me include:


 

The key link from Bloom (1913-1999) one e-learning paper you must read plus his taxonomy of learning — an excellent item from Donald Clark Plan B (also see Donald’s archives for postings re: 50 top learning theorists)

The 2 Sigma Problem: The Search for Methods of Group Instruction as Effective as One-to-One Tutoring
Benjamin Bloom
University of Chicago | Northwestern University

Excerpt:
Most striking were the differences in final achievement measures under the three conditions. Using the standard deviation (sigma) or the control (conventional) class, it was typically found that the average student under tutoring was about two standard deviations above the average of the control class (the average tutored student was above 98% of the students in the control class). The average student under mastery learning was about one standard deviation above the average of the control class(the average mastery learning student was above 84% of the students in the control class).

Two key items from EdNet Insight’s Anne Wujcik:

Mapping a Personalized Learning Journey – K-12 Students and Parents Connect the Dots with Digital Learning — from Project Tomorrow

Personalizing Learning in 2012 — The Student & Parent Point of View [infographic] — from Project Tomorrow
Excerpt from Anne’s posting:

This first report focuses on how today’s students are personalizing their own learning, and how their parents are supporting this effort. That personalization centers around three student desires: including how students seek out resources that are digitally-rich, untethered and socially-based. The report share the unfiltered views of K-12 students and parents on these key trends and documents their aspirations for fully leveraging the technologies supporting these trends to transform their learning lives.

From DSC:
This is exactly what I was getting at with The Forthcoming Walmart of Education (2008) and it points out, again, that innovation is much faster and stronger in the online world than it is in the face-to-face world. The tools being developed to engage, track, diagnose, and adapt continue to be developed. What may have once been poo-pooed continues to pick up steam. (Christensen, Johnson, & Horn are right on track.) The trend will be towards more team-based endeavors that can be made available at a greatly reduced price. They will be multimedia-based, highly-interactive, and state-of-the-art (technically and pedagogically).

Treating Higher Ed’s ‘Cost Disease’ With Supersize Online Courses — from The Chronicle by Marc Parry

Excerpt (with emphasis from DSC):

Professors should move away from designing foundational courses in statistics, biology, or other core subjects on the basis of “intuition,” she argues. Instead, she wants faculty to work with her team to put out the education equivalent of Super Bowl ads: expensively built online course materials, cheaply available to the masses.

“We’re seeing failure rates in these large introductory courses that are not acceptable to anybody,” Ms. Thille says. “There has to be a better way to get more students—irrespective of where they start—to be able to successfully complete.”

Her approach brings together faculty subject experts, learning researchers, and software engineers [from DSC — a TEAM-based approach] to build open online courses grounded in the science of how people learn. The resulting systems provide immediate feedback to students and tailor content to their skills. As students work through online modules outside class, the software builds profiles on them, just as Netflix does for customers. Faculty consult that data to figure out how to spend in-person class time.

From DSC:
Such learner profiles will most likely reside in the cloud and eventually standards will be established to insert new data into these profiles. The access to view/edit these profiles will be controlled by the individual learners (hopefully!).  What if learners could selectively grant corporations access to this type of profile as their new resume?

For items concerning team-based approaches, see this recording (June 2009) as well as this collection of items.

For items concerning consortia and pooling resources, see here and here.

 

 

Next on TV: Data driven programming — from wired.co.uk by Matt Locke

Excerpt:

Quiz shows such as The Million Pound Drop Live on Channel 4 use real-time data from hundreds of thousands of online players to feed interesting stats and observations to host Davina McCall. [From DSC: What if this related to an online-based learning exercise/class/module/training session?]

This is the real revolution that is about to hit TV production — data is moving off the servers and in front of the cameras. With this comes a new generation of creative talent — data storytellers for whom the spreadsheet is as important as a script when it comes to content. TV is no longer stuck behind the screen — around 60 per cent of people in the UK watch with a “second screen” (a mobile or laptop) at the same time, and a lot of them are talking online about what they’re watching. TV is now back in the crowd, and if you make, commission or distribute content right now, you’d better learn to love data, and fast.

Also see:

  • What comes after Siri? A web that talks back — from gigaom.com by Stacey Higginbotham
    Siri may be the hottest personal assistant since I Dream of Jeannie, but Apple’s artificial intelligence is only the tip of the iceberg as we combine ubiquitous connectivity, sensor networks, big data and new methods of AI and programming into a truly connected network.
  • Ball State University Center for Media Design to Host Workshop Session — from thetvoftomorrowshow.com
    Entitled “Researching the Second Screen and Social Viewing: Two Recent Studies,” the workshop will see CMD researchers summarizing the findings from: 1) an eye-tracking study of viewers’ distribution of visual attention between the TV and second screen during use of two commercially released second-screen apps; and 2) a study of show-specific Twitter traffic rates during programming and ad pods for multiple episodes of three shows from different genres.

There's no time for baby steps -- Wireless Generation

Also see their information on Burst — for early literacy

and their estimate product launch dates:

 

Tagged with:  

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!

© 2019 | Daniel Christian