<li>Immediate feedback prevents subsequent confusion and limits the likelihood for continued inappropriate retrieval practice.</li> <li>Delayed feedback creates a beneficial spacing effect.</li> <li>When in doubt about the timing of feedback, you can (a) give immediate feedback and then a subsequent delayed retrieval opportunity, (b) delay feedback slightly, and/or (c) just be sure to give some kind of feedback.</li> <li>Feedback should usually be provided before learners get another chance to retrieve incorrectly again.</li>

For neuroscience to mean something to teachers, it must provide information beyond what is available without neuroscientific methods. It’s not enough to describe what’s happening in the brain, and pretend that you’ve learned something useful.

In general, if you are interested in describing effects at a given level of analysis, you are most likely to make progress by sticking to that level of analysis. If you’re interested in describing ways that students learn best, it makes sense to study classroom situations. To the extent that neuroscience will inform good teaching practice, it seems most likely that this influence will be funneled through the cognitive level of analysis: For example, neuroscience will help us better understand memory, and this improved understanding of memory might be used to improve classroom practice. It’s unlikely that leapfrogging the cognitive level analysis and going straight from the brain to the classroom will work out very often.

Connectivism is the application of network principles to define both knowledge and the process of learning. Knowledge is defined as a particular pattern of relationships and learning is defined as the creation of new connections and patterns as well as the ability to maneuver around existing networks/patterns.

As a result, while N-Gens interact with the world through multimedia, online social networking, and routine multitasking, their professors tend to approach learning linearly, one task at a time, and as an individual activity that is centered largely around printed text (Hartman, Dzubian, and Brophy-Ellison <a target="_blank" href="http://www.webcitation.org/5Xw4B5bKP">2007</a>).

However, these digital texts do not necessarily lack style, coherence, or organization; they simply present meaning in ways unfamiliar to the instructor. For example, a collection of images on Flickr with authorial comments and tags certainly does not resemble the traditional essay, but the time spent on such a project, the motivation for undertaking it, and its ability to communicate meaning can certainly be equal to the investment and motivation required by the traditional essay—and the photos may actually provide more meaningful communication for their intended audience.

Texts that do not look like books or essays and that are structured in unfamiliar ways may leave educators with the perception that the authors of these texts lack necessary literacy skills. Are these students missing something, or are they coming to us with skills as researchers, readers, writers, and critical thinkers that have been developed in a context that faculty members may not understand and appreciate? The striking differences between the linear, print-based texts of instructors and the interactive, fluctuating, hyperlinked texts of the N-Gen student may keep instructors from fully appreciating the thought processes behind these texts. Learning how to teach the wired student requires a two-pronged effort: to understand how N-Gen student understand and process texts and to create a pedagogy that leverages the learning skills of this type of learner.

<p>Downes’ and Siemens’ discussions shed new light on fundamental concepts, such as rules versus patterns, complicated vs. complex, equivalence vs. similarity, and coping with ambiguity and uncertainty. And these consideration render many entrenched practices of the entire knowledge industry questionable.</p> <p>All these aspects have one thing in common: that they can be illustrated by the neuronal <strong>metaphor</strong>, the metaphor of a network with nodes and connections, where</p> <blockquote><p><em>“Not all connections are of equal strength in this metaphor”</em> (<a href="http://en.wikipedia.org/wiki/Connectivism_%28learning_theory%29">Wikipedia</a>)</p></blockquote>

So, connectivism and its neuronal connections metaphor, allow to distinguish more clearly between two types of knowledge, one of which is the more adequate one for coping with complexity and uncertainty: <em>connective</em> knowledge.

We argue that learning occurs in networks, and therefore, that the properties of successful networks are also the properties of successful learning environments. We don't 'apply' this in any strict sense - we would never force people to be connectivists. Indeed, within the learning environment, we believe there should be diversity; we believe people should be free to choose their own form of learning.

To me, <span style="font-style: italic;">far more</span> complex - and insightful - forms of reasoning are being created through the interplay among thousands, or millions, of individual content elements. Where each content element may by itself appear to be <span style="font-style: italic;">simple</span>, it is the interconnections between them that creates a much more complex, deep, and <span style="font-style: italic;">rich</span> tapestry of meaning, <span style="font-style: italic;">far more</span> than could be created merely using linguistic devices.

It is substantially <span style="font-style: italic;">harder</span> to work with the disorder and complexity we see within a connectivist network. Because linguistic (syntactical and semantical) descriptions of the concepts and entities in such a network just barely touch the surface, and students must therefore immerse themselves in the process of reasoning in such a system, rather than merely reading about it.

However, nobody would assume that in order to know that wood one has to know exactly every tree, one by one, its shape, age and location. Every plant. Every leave of every plant. Every animal and where every animal is and what every animal is doing at any instant. Every stone. Every particle.

Those of you who've taken political science know that all of human history in political science is the division between the individual and the state. Right? The person and the group, right? And these are the two divides. And the whole purpose of politics is to find some sort of accommodation for them or if you're Ayn Rand, to favor the individual and ignore the group.<br><br> And it seems to me that networks offers that middle way. Networks offers that path that isn't the individual and isn't the group, doesn't force you to choose between the individual and the group.

But more or less, a group is a collection of entities or members according to their nature or their feature or their properties or whatever, their essential nature, maybe, their accidental nature, maybe, whatever, but according to their nature. What defines a group is the quality the members possess in common and then the number of members in that group. Groups are about nature, they're about quality, they're about mass. They're about number. <br><br>A network, by contrast, is an association – I use that word very precisely – an association of entities or members where this association is facilitated or created by a set of connections between those entities. And if you say, "Well what is a connection?" A connection is merely some conduit along which a signal can run. Well, that clarified it, didn't it? What defines a network is the nature and the extent of this connectivity. The nature and the extent to which these individuals are connected together.

I want to change the system of assessment in schools because right now we have tests and things like that that are scrupulously fair, particularly distance learning where we outline the objectives the performance metrics and the outcomes and all of that. I want to scrap that system. I want testing to be done by at random by comments from your peers and other people and strangers based on no criteria whatsoever and applied unequally and unfairly.

Networks are almost defined by the opposite, defined by their diversity. A network thrives on diversity. It wouldn't be a network without diversity.

Internet technology that encourages diversity rather than conformity includes things like personal home pages or these days, blogs. I should add to this slide MySpace profiles and things like that, your account on Flickr. All of these things that allows the individual to express themselves rather than the individual being part of some larger entity.

A little while ago, <a href="http://www.jarche.com">Harold Jarche</a> sent this quotation: “”Information overload does not exist. Failing information strategies do exist. ”

1. How to predict consequences

The prediction of consequences is part science, part mathematics, and part visualization.

2. How to read

Oddly, by this I do not mean 'literacy' in the traditional sense, but rather, how to look at some text and to <span style="font-style: italic;">understand</span>, in a deep way, what is being asserted

<span style="font-weight: bold;">3. How to distinguish truth from fiction</span>

The first thing to learn is to actually question what you are told, what you read, and what you see on television. Do not simply accept what you are told. Always ask, how can you know that this is true? What evidence would lead you to believe that it is false?

<span style="font-weight: bold;">4. How to empathize</span>

Empathy isn't some sort of bargain. It isn't the application of the <a href="http://en.wikipedia.org/wiki/Ethic_of_reciprocity">Golden Rule</a>. It is a <span style="font-style: italic;">genuine</span> feeling in yourself that operates in synch with the other person, a way of accessing their inner mental states through the sympathetic operation of your own mental states. You are polite because <span style="font-style: italic;">you</span> feel bad when you are rude; you are honest because <span style="font-style: italic;">you</span> feel offended when you lie.

5. How to be creative

Creativity, in other words, often operates by <span style="font-style: italic;">metaphor</span>, which means you need to learn how to <span style="font-style: italic;">find things in common</span> between the current situation and other things you know.

<span style="font-weight: bold;">6. How to communicate clearly</span>

Communicating clearly is most of all a matter of knowing what you want to say, and then employing some simple tools in order to say it.

7. How to Learn

Learning to learn is the same as learning anything else. It takes practice.

8. How to stay healthy

Finally, remember: you never have to justify protecting your own life and health.

9. How to value yourself

You can have all the knowledge and skills in the world, but they are meaningless if you do not feel personally empowered to use them; it's like owning a <a href="http://www.lamborghini.co.uk/">Lamborghini</a> and not having a driver's license.

10. How to live meaningfully

If you don't decide what is worth doing, someone will decide for you, and at some point in your life you will realize that you haven't done what is worth doing at all.

We can't "create" learning<br>- We can design environments conducive to learning.<br>- We design learning experiences.

Don't design CONTENT, design EXPERIENCES<br>- Design the "Flow".<br>- Start bringing in emotions and the actions they take

So basically when you blog, you have to think about what you have read, how that compares to what you already know or what you have experienced, and that comparison helps you to construct new mental models that you articulate in written form (your blog).