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Personalized Learning 3.0 — Creating Personalized 'Bicycles for the Mind'

In a typical classroom, 30 students sit in neat rows and watch a teacher at the front of the room as she/he gives a lecture, carries out a demonstration, shows a video or animation, etc. But in a personalized learning classroom, each student has his or her own teacher – in the guise of a computer screen – that delivers a lecture, video,  textual material, demonstrations, that are adapted to each learner's particular needs and achievement level.

But a short history lesson about technology and computers may be illuminating here:

  • When the motion picture camera was invented in 1892, it was used initially to capture plays – theater. It took Hollywood to say, no, no, we can use the motion picture camera to make a movie – to create a whole new media genre, to tell a whole new type of story!
  • In the early 1990s Web 1.0 was just a series of static Web pages – just like pages in a book; the hyperlinks made it easier to jump around in that "big book." It took 10 years for the Web to provide interactive media and new ways to communicate – so-called Web 2.0.
  • Initially, manufacturing companies used computers to do a better job of tracking parts in their inventories; but Dell came along and used Internet-connected computers to eliminate inventory by creating just-in-time manufacturing.

Over and over again, new technology is initially used to do an existing process to gain some efficiencies – show a play but time-shifted; move among more pages, faster; keep track of parts more effectively. Then someone comes along and uses the new technology to invent a completely new process to gain significant new advantage or opportunities – create a movie, create interactive media and new modes of communication or manufacture complex objects on a heretofore unheard of schedule. In 1998 Soshanna Zuboff, in her now classic book, In the Age of the Smart Machine, called the former process of using computers "automating" and the later "informating."

Using Zuboff's terminology, then, Personalized Learning – PL 1.0 – described in our first paragraph and implemented in classrooms (e.g., in Carpe Diem schools in Arizona) is simply automating direct instruction pedagogy. Yes, there are some gains, e.g., the cost of instruction per pupil is reduced. But the real gains from using computers are not realized in PL 1.0; indeed, even when it's personalized, direct instruction pedagogy does not prepare children for the world  they will enter – the knowledge-work, global economy.  

Where is the "informating" in education? After all, as Steve Jobs has commented:  "... [A] computer is ... the most remarkable tool that we've ever come up with;... it's the equivalent of a bicycle for our minds." PL 1.0 is not using the computer as the "bicycle for our minds."

So, taking a page from Microsoft, who came out recently with Windows 10, skipping Windows 9, so as to really, REALLY distance itself from Windows 8, we want to explore what Personalized Learning 3.0 might look like – and really, REALLY distance ourselves from the pedagogical dinosaur of Personalized Learning 1.0.

Warning: Analogies do break down: while Windows 10 is in fact a commercial product, Personalized Learning 3.0 environments are still, by and large, twinkles in the eye!

Here are two examples, two elements, then, of what a Personalized Learning 3.0 environment will eventually support.

Software and its Interface: Learners grow and change; that's what it means to be a learner! But, the software and its interface that learners use is the same, for all the learners in the class, in September, at the start of the school year, as it is in June, at the end of the school year. Why doesn't the software change, for each of the learners, as the learners change? 

For example: in September, fourth-graders should be able to use a PL 3.0 drawing tool  to create static images on their computing device; but by June, some of those fourth-graders should be able to use animation – moving images – to express their ideas and their evolving understanding. In a Personalized Learning 3.0 drawing tool that animation functionality will be revealed, automatically, to those students who are ready to use it.

How will that PL 3.0 tool make such a decision? "Big data!" There will be thousands of fourth-graders who have been using drawing tools, and, based on analyses of the performance and achievement of those fourth-graders, PL 3.0 environments will discern patterns of effective and ineffective use and thus will identify the characteristics of students who are ready for animation.

Scaffolding the learning:  Educators talk about providing learners with "scaffolding" to help them learn, and then fading that scaffolding as the learner develops her or his own expertise. For example, in a classroom 10 three-student groups are reading in a textbook about infectious diseases and using a PL 3.0 concept mapping tool to create a concept map that identifies the key ideas in that chapter. 

The students' concept mapping tool is providing them with "meta-cognitive scaffolding" to support their verbal conversations and helping them to resolve the disagreements that invariably arise in a collaborative group's conversation. As each student in each group develops the skills to effectively resolve those disagreements, the meta-cognitive scaffolding will fade – will be removed – for that student.

How will that PL 3.0 concept mapping tool know to make the decision to fade the scaffolding? "Big data"! Again, based on analyses of thousands of students who have engaged in collaborative groups using the concept mapping tool (and other collabrified tools), PL 3.0 environments will discern patterns of effective and ineffective collaboration and thus will identify the characteristics of students who are ready for their scaffolding to be eliminated.

And, collaboration is but one of the many 21st century skills that students need to develop. Indeed, the Next-Generation Science Standards identify a range of "practices" – in contrast to identifying facts to be memorized - that leaners need to engage in if they are to truly come to understand modern science.

Personalized Learning 3.0 environments, which, again, draw upon "Big Data" to provide personalized scaffolding – and its fading – are the only cost-effective way to insure that each and every student develops the key 21st century skills that are required to be effective participants in that global, knowledge-work economy.

There is a growing R&D community exploring "smart learning environments." PL 3.0 is one example of a "smart learning environment."

On the way to Personalized Learning 3.0, we may well need to "pass through" Personalized Learning 1.0 environments, but we mustn't tarry! Educational automation is not an interesting goal! The vision of a personalized "bicycle for the mind" for each and every child must drive us to informate – to create Personalized Learning 3.0 environments!!

About the Authors

Cathie Norris is a Regents Professor and Chair in the Department of Learning Technologies, School of Information at the University of North Texas. Visit her site at www.imlc.io.

Elliot Soloway is an Arthur F. Thurnau Professor in the Department of CSE, College of Engineering, at the University of Michigan. Visit his site at www.imlc.io.

Find more from Elliot Soloway and Cathie Norris at their Reinventing Curriculum blog at thejournal.com/rc.

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