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Based on the success of Norvig and Thrun’s experiment, the university’s computer science department is planning to broadcast eight additional courses for free in the spring, most focusing on high-level concepts that require participants already to have a pretty good command of math and science.

It raises the question: Whose certification matters, for what purposes?

For one, the professors can only evaluate non-enrolled students via assessments that can be graded automatically.

it can be difficult to assess skills without being able to administer project-based assignments

With a player like Stanford doing something like this, they’re bringing attention to the possibilities of the Web for expanding open education

However as education in the developed world moves in new directions, we must be cognizant of how this move impacts the learners in the developing world. How will learners in these areas access, explore and contribute to the creation of knowledge? Will social networking technologies, and the emergence of next generation technologies further exclude the greatest number of undergraduate learners. Will this new reality result in too few voices connecting and validating knowledge? How can non-Eurocentric voices be heard? One must ensure that there is some democracy in this new model.

Educators and leaders in academia are confronted with important questions. How should institutions of learning be designed to serve the needs participative, social, and global information cycle? What assumptions about the system of higher education need to be abandoned due to technological advancements? How can the vital roles of research and teaching and learning be addressed through distributed means? How can accreditation be broadened to include the full spectrum of formal and informal learning activities?

Failure to recognize the pivotal role of digital technologies will result in institutions at odds with the world in which they operate.

The American Faculty: The Restructuring of Academic Work and Careers (Schuster & Finkelstein, 2006) propose that universities are experiencing a revolution—with tremendous consequences. They write, Everything is in play, as nearly every aspect of academic life is being driven by a host of inter-related developments: dazzling technological advances, globalization that permeates academic boundaries, rapid increase of tertiary students worldwide, expansion of proprietary higher education, a blurring of (the) public/private distinction, and entrepreneurial initiatives on and off campus. (p. xvii)

Technological innovations in bandwidth, storage, processing speed, and software directly impact education (Downes, 2009), creating new opportunities for learner-learner/educator and learner-information interactions.

ome researchers have turned to complexity theory to advance education, suggesting that emphasis be placed on the whole system rather than reductionist views often found in "mainstream science" (Mason, 2008). Increased collaboration in a model of "interlocking partnerships among researchers, among universities, and across international borders” (McFadden Allen, 2007, p. 3) promises a new model of not only what it means to be an academic, but also what it means to be an academic institution.

The bolded items above really represent one version (and certainly not the only one) of the complete package – open content, open learning support, and open badges that help you demonstrate competence to an employer.

- An initial list of OER (e.g., OLI courses) and Q/A services (e.g., StackOverflow.com or OpenStudy) which will help individuals develop the skills necessary to obtain the badges

• Combine these and other business models to generate enough revenue so that (1) the marking service can be free in addition to all the badge related materials being openly licensed and (2) employers will respect and recognize the badges resulting from the process.

If a digital artifact released under a CC BY license is posted on a public website it would qualify as an open educational resource for everyone with internet access. However, if a teacher downloaded a copy of the OER and placed it inside a learning management system it would suddenly cease to be an open educational resource – even though the resource hadn’t changed.

The efficacy ideal is not realizable in practice. Intuitively we would want the ideal OER to support the educational goals of every user, and some definitions limit OER to “high-quality” materials. However quality, like beauty, is in the eye of the beholder. A resource considered very high quality by an English speaking undergraduate might be very low quality for an English speaking primary school student or a Spanish speaking undergraduate.

While everyone wants the OER they use to be high quality for them, it is meaningless to talk about OER being “high quality” without simultaneous reference to the user.

In this chapter I have argued that we can view higher education as a long-tail content production environment. Much of what we currently aim to achieve through specific public engagement projects can be realised by producing digital artefacts as a by-product of typical scholarly activity. My intention is not to suggest that this is the only means of performing public engagement; for example, engaging with local schools works well by providing face-to-face contact with inspiring figures. As with other scholarly functions, some will remain, but the digital alternative not only allows for new ways of realising the same goals but also opens up new possibilities.

realistic

think in the same ways as professionals

Technology-based cognitive tools

the creation of real products and artefacts, and are more worthy of the investment of time and effort in higher education than decontextualised exercises and tasks.

The creation of genuine sharable products ensures that authentic learning is in a position to capitalize on the participatory culture afforded by social media.

our model to guide your design: http://web.me.com/janherrington/AuthenticLearning/

David Wiley and Rory McGreal urge universities to open their content; Wiley further envisions the future of education consisting of learner-generated materials;

Building rhizome-like learning networks can foster an environment more conducive to continuous knowledge acquisition and constructio

This does not match the way our brain process information, as we are better at learning incremental chunks of knowledge in a meaningful and authentic context.

Dave Cormie

Clark Quinn’s idea of slow learning

Here Jon Dron reminds us that tools themselves are not technology

Dron’s definitions of hard vs soft technologies relevant to both formal and informal learning, further help us to undertand that soft technologies are perhaps more useful in building learning and support communities and equipping learners with the ability to  navigate information in networks, thereby promoting lifelong learning.

The learners will end up leading the way, as they should.

Brown (2009) reports, Recently, the Nielsen Norman Group study of teenagers using the web noted: ‘We measured a success rate of only 55 percent for the teenage users in this study, which is substantially lower than the 66 percent success rate we found for adult users’. The report added: ‘Teens’ poor performance is caused by three factors: insufficient reading skills, less sophisticated research strategies, and a dramatically lower patience level’.

A new generation is behaving fundamentally differently – there seems little real evidence beyond the rhetoric that the net generation is in some way different from its predecessors as a result of having been exposed to digital technologies. There is some moderate evidence that they may have different attitudes. There is a general change in society which has relevance for learning – certainly the overall context is an ICT-rich one, and people are using the Internet for a variety of learning-related activities. People are learning in different ways – although firm evidence of informal learning is difficult to gather, there is much by the way of proxy activity that indicates this is the case. There is growing dissatisfaction with current practice in higher education – there seems little strong evidence for this. Probably more significant to the culture of education has been the shift to perceiving the student as a customer. There is certainly little evidence that the dissatisfaction is greater than it used to be, but what may be significant is that there are now viable alternatives for learners. Universities have lost their monopoly on learning, which reinforces the next point.

Higher education will undergo similar change to that in other sectors – there are some similarities between higher education and other sectors, such as the newspaper and music industries, but the differences are probably more significant. However, the blurring of boundaries between sectors and the viability of self-directed, community-based learning means that the competition is now more complex.

The first is that there is lag between society's acceptance of a technology and then its adoption in higher education. Brown (2009) suggests that in society the stages of technology diffusion can be defined as critical mass (ownership by 20–30 per cent of the population), ubiquity (30–70 per cent) and finally invisibility (more than 70 per cent). If higher education were to wait for the invisibility stage to be reached before it engaged with a technology, then given the time it takes to implement policies and technology, it really will look outdated. For example, in 2007, those using social networks might have been in the minority; now they will be in the majority. This is the problem with waiting for data to determine decisions – if you made a decision based on 2007 data that social networks were largely unused, it would look out of date in 2010. What is significant is the direction of travel, not the absolute percentages at any given time.

A curator is an expert learner. Instead of dispensing knowledge, he creates spaces in which knowledge can be created, explored, and connected.

Learning is an eliminative process. By determining what doesn’t belong, a learner develops and focuses his understanding of a topic. The teacher assists in the process by providing one stream of filtered information. The student is then faced with making nuanced selections based on the multiple information streams he encounters. The singular filter of the teacher has morphed into numerous information streams, each filtered according to different perspectives and world views.

Course content is similarly fragmented. The textbook is now augmented with YouTube videos, online articles, simulations, Second Life builds, virtual museums, Diigo content trails, StumpleUpon reflections, and so on.

Fragmentation of content and conversation is about to disrupt this well-ordered view of learning. Educators and universities are beginning to realize that they no longer have the control they once (thought they) did.

However, in order for education to work within the larger structure of integrated societal systems, clear outcomes are still needed.

How can we achieve clear outcomes through distributed means? How can we achieve learning targets when the educator is no longer able to control the actions of learners?

Thoughts, ideas, or messages that the teacher amplifies will generally have a greater probability of being seen by course participants.

Each RT amplifies the message much like an electronic amplifier increases the amplitude of audio or video transmitters.

A curatorial teacher acknowledges the autonomy of learners, yet understands the frustration of exploring unknown territories without a map. A curator is an expert learner. Instead of dispensing knowledge, he creates spaces in which knowledge can be created, explored, and connected.

In CCK08/09, Stephen and I produced a daily newsletter where we highlighted discussions, concepts, and resources that we felt were important. As the course progressed, many students stated they found this to be a valuable resource -a centering point of sorts.

Today’s social web is no different – we find our way through active exploration. Designers can aid the wayfinding process through consistency of design and functionality across various tools, but ultimately, it is the responsibility of the individual to click/fail/recoup and continue.

Fortunately, the experience of wayfinding is now augmented by social systems. Social structures are filters. As a learner grows (and prunes) her personal networks, she also develops an effective means to filter abundance. The network becomes a cognitive agent in this instance – helping the learner to make sense of complex subject areas by relying not only on her own reading and resource exploration, but by permitting her social network to filter resources and draw attention to important topics. In order for these networks to work effectively, learners must be conscious of the need for diversity and should include nodes that offer critical or antagonistic perspectives on all topic areas. Sensemaking in complex environments is a social process.

After all, why should we do the heavy cognitive work when technology is uniquely suited to analyzing and generating patterns?

I’d like a learning system that functions along the lines of RescueTime – actively monitoring what I’m doing – but then offers suggestions of what I should (or could) be doing additionally. Or a system that is aware of my email exchanges over the last several years and can provide relevant information based on the development of my thinking and work. With the rise of social media, and with it the attention organizations pay to how their brand is being represented, monitoring services such as Viral Heat are promising. Imagine a course where the fragmented conversations and content are analyzed (monitored) through a similar service. Instead of creating a structure of the course in advance of the students starting (the current model), course structure emerges through numerous fragmented interactions. “Intelligence” is applied after the content and interactions start, not before. This is basically what Google did for the web – instead of fully defined and meta-described resources in a database, organized according to subject areas (i.e. Yahoo at the time), intelligence was applied at the point of search. Aggregation should do the same – reveal the content and conversation structure of the course as it unfolds, rather than defining it in advance.

Filtering resources is an important educator role, but as noted already, effective filtering can be done through a combination of wayfinding, social sensemaking, and aggregation. But expertise still matters. Educators often have years or decades of experience in a field. As such, they are familiar with many of the concepts, pitfalls, confusions, and distractions that learners are likely to encounter. As should be evident by now, the educator is an important agent in networked learning. Instead of being the sole or dominant filter of information, he now shares this task with other methods and individuals.

By determining what doesn’t belong, a learner develops and focuses his understanding of a topic. The teacher assists in the process by providing one stream of filtered information. The student is then faced with making nuanced selections based on the multiple information streams he encounters. The singular filter of the teacher has morphed into numerous information streams, each filtered according to different perspectives and world views.

Given that coherence and lucidity are key to understanding our world, how do educators teach in networks? For educators, control is being replaced with influence. Instead of controlling a classroom, a teacher now influences or shapes a network.