Connectivist Enterprises

I wrote this in 2011 but it seems almost current in terms of relevance. Some links may not work.

Introduction

Education has morphed across centuries of foundational thought and practice on what is learning, teaching and knowledge. Whether they are ancient practices and beliefs like in the Vedas or are contemporary like Connectivism, the landscape has been shaped by and has shaped events of culture, technology and society. What has remained constant is the change itself, the constant evolution and revolution of thought applied to the domain of learning and teaching.

These progressions reach a strategic inflection point every once in a while resulting in a fundamental change of perception and belief. I believe we are at one such point now given the rapid advances in learning theory, technology, market characteristics and consumer preferences in turn fuelled by recessionary trends.

These strategic inflection points are marked by a change in the frame of reference. Traditional methods are overturned and new technologies and practices reshape the landscape creating new models for efficiency and investment in organizations. The theory and practice of Connectivism marks such a strategic inflection point.

A key dimension in this inflection is technology, with Web 2.0, the promise of ubiquitous networks, cloud computing and social networking. Personal Learning Environments are quickly emerging as de facto learning environments.

But a far greater change seems to be manifesting itself – the emergence of the millenials or Generation Y or the Net Generation by Don Tapscott in his recent book Grown Up Digital (p 16) – terms multifariously used to describe the fast evolving digital generation for whom networking, sharing, gaming and online collaboration are breaking down boundaries of thought and location.

Learners are changing from passive receptors of information and training to active participants in their own learning. This is a viral change, so it is really fast. Today’s digital learners are part of communities. They share their interests with members of their community. They twitter. They blog. They rake in RSS feeds and bookmark their favorities on de.li.ci.ou.s. They share photos on Flickr and videos on YouTube. They share knowledge on Slideshare and Learnhub or Ning. They share ideas. They grow by meeting and engaging peers and gurus alike using the LinkedIn or Facebook. On their laptops and on their mobile phones.

https://learnos.wordpress.com/2008/08/31/xos-in-learning-and-technology/

Don characterizes the Net Generation, those born between January 1977 and December 1997, as having 8 distinct characteristics or norms (Grown Up Digital, p 74) – freedom, customization, scrutiny, integrity, entertainment, collaboration & relationship, need for speed and innovation.

A predominant contribution to social networking sites, life streams, instant messaging, blogs and media sharing tools, seems to be emanating from this younger generation. This in itself is a key dimension because this generation is getting access to media and practices that traditional learning mechanisms cannot provide. The Pew / Internet report Teens and Social Media reports that “The use of social media gains a greater foothold in teen life as they embrace the conversational nature of interactive online media.” The MacArthur report suggests that “New media forms have altered how youth socialize and learn, and this raises a new set of issues that educators, parents, and policymakers should consider.” Privacy concerns are raised by Don (Grown Up Digital, pp 65-70) and Pew Internet, among others; to highlight the issue that this generation is sharing too much of what is personal.

What we’re seeing right now is a cultural shift due to the introduction of a new medium and the emergence of greater restrictions on youth mobility and access. The long-term implications of this are unclear. Regardless of what will come, youth are doing what they’ve always done – repurposing new mediums in order to learn about social culture.

(http://www.danah.org/papers/AAAS2006.html)

Another key dimension contributing immediately to this inflection, but will have enduring effects beyond it, is the immense pressure in the current marketplace on expenses. As Josh Bersin says:

And best of all, an informal learning strategy saves money.  By empowering people to publish their expertise and learn from each other, you can cut spending on content development, external content, and formal training – focusing your energies on the “upper right” training programs in your organization.

Suppliers and vendors are changing over to incorporating 2.0 technology and crafting new consulting services to meet the new challenges. LMS providers such as SABA have already incorporated social media technologies like blogs and wikis in their offering. Authoring and content development providers are fast incorporating social media strategies as part of both the design and deployment of content.

Substantial opinion has also been generated with Jay Cross’s Learnscapes, James Suroweicki’s Wisdom of Crowds, Malcolm Gladwell’s Outliers, Valdis Kreb’s Social Network Analysis and many books, articles, blog posts and publications reflecting the changing technology, culture and social landscapes and impacts on learning, organization and innovation.

Jay Cross suggests the inflection point is upon us.

Clearly we have reached an inflection point.   Where “e-learning” was the big craze in corporate training in the early 2000’s, and “blended learning” was the craze in 2003 and 2004, today, thanks to the slowing economy and the widespread availability of social networking and online wikis and portals, “informal learning” is the next big thing.

The underlying message is that there is a significant change happening that promises to change not only the way we do business but also the way we teach and learn.

Connectivism

The Theory

Connectivism is a new theory of learning for the digital age propounded by George Siemens with its epistemological roots in the theory of Connective Knowledge postulated by Stephen Downes. Connectivism stands contrasted to major existing theories of learning and knowledge by its emphasis on learning as the ability to make connections in a network of resources, both human and device and by the amalgamation of theories of self-organization, complexity and chaos as applied the process of learning.

Connectivism embraces and extends the following principles:

• Learning is the process of making new connections
• Connections are a primary point of focus and could be to people or devices
• Connections expose patterns of information and knowledge that we use (recognize, adapt to) to further our learning
• Networked learning occurs at neural, conceptual and social levels
• Types of connections define certain types of learning
• Strength and nature of connections define how we learn
• Networks are differentiated from Groups (by factors such as openness, autonomy, diversity, leadership and nature of knowledge)
• Knowledge is the network, learning is to be in a certain state of connectedness
• All knowledge is associative in nature and resides across our connections
• Chaos, complexity theory, theories of self-organization and developments in neurosciences are all extremely important contributors for us to understand how we learn in a volatile, constantly evolving landscape

Connectivism focuses on the distributed nature of learning and knowledge, the explicit focus on networks as the primary means of learning. As George Siemens states, connectivism, as a networked theory of learning, draws on and informs emerging pedagogical views such as informal, social, and community learning.

Other theories such as Jay Cross’s Informal Learning, Lave and Wenger’s Communities of Practice (CoP) and Brown and Duguid’s Network of Practice build upon the networked and distributed nature of learning.

For example, defined by knowledge rather than the task, CoPs are different from social networks or teams because they are not only about relationships or tasks. Rather they are about the shared learning and interest of its members.

Connectivism is very different from existing theories of Behaviorism, Cognitivism and Constructivism and is more readily and effectively applied to today’s learners and their needs. Learning 2.0 as a style or Connectivism as a theory are diametrically opposed to the traditional 1.0 styles of learning or the prior learning theories. Every aspect, whether it be setting goals for learning, providing content, organizing learning groups, measuring & tracking progress and managing schedule constraints, needs to be re-evaluated for it’s equivalent in the 2.0 connective world.

In Connectivism, learning becomes the process of making connections and knowledge is the network. As Stephen explains:

Just as the activation of the pixels on a television screen form an image of a person, so also the bits of information we create and we consume form patterns constituting the basis of our knowledge, and learning is consequently the training our own individualized neural networks – our brains – to recognize these patterns.

Connectivism as applied to contemporary challenges facing educators is nothing short of an inflection point. In an appeal to end course-o-centrism, Siemens writes:

What is really needed is a complete letting go of our organization schemes and open concepts up to the self/participatory/chaotic sensemaking processes that flourish in online environments.

Impacts

Connectivism impacts all aspects of education & training design, development and delivery – from the role of the educator , the role of the learner, the roles of the developers (instructional design, visual design, technical design) to the very structure of the learning organization and its vendors. This aspect is critical to understand while implementing designs based on this theory. As I have written before:

The enormity of what Connectivism asks us to do can be realized in this very context – re-evaluate the role of educators, think of the network or connectedness as the base architecture for learning and re-assess notions of identity, power, law, authority, expertise, assessment and control in the light of the new theory.

Wendy Drexler’s Networked Student brings this into sharp focus.  Nancy White reviews 14 characteristics of Network Weavers (a contemporary metaphor for educators)

Janet Clarey’s series of posts on the evolution of LMS systems also provides information on how LMS and Talent Management System vendors are fast incorporating social media and informal learning into their systems.

Connective Learning for the Enterprise

Organizations are fast aligning their learning and development ecosystems to this new way of learning. John Chambers, CISCO’s CEO had to say:

…”Without changing the structure of your organization,” Chambers told the analysts in September, “I would argue that [innovation] will not work.””

Cisco, Chambers argues, is the best possible model for how a large, global business can operate: as a distributed idea engine where leadership emerges organically, unfettered by a central command.

C.K. Prahalad and M.S. Krishnan, in their book The New Age of Innovation argue that there is a fundamental transformation in the way we do business and it is critical for companies to negotiate two fundamental pillars of this change – co-created experiences (N=1) and access (rather than ownership) to global resources (R=G). In their mind the social architecture of the organization (structure, performance measurement, training, skills and organizational values) is equally an important pillar as is the technology architecture.

According to Tim O’Reilly, the founder and chief executive of O’Reilly Media, creativity is no longer about which companies have the most visionary executives, but who has the most compelling “architecture of participation.” That is, which companies make it easy, interesting and rewarding for a wide range of contributors to offer ideas, solve problems and improve products?

Josh Bersin makes the clarion call:

It’s now official. After surveying our entire research membership and having more than 30 conversations with leading HR and learning leaders (including with Xerox, Accenture, British Telecom, Edward Jones, Department of Defense, and Network Appliance), I am now 100% convinced that “informal learning” has become “formal.”  That is, if you want to build a high-impact, cost-effective, modern training organization you must “formally adopt” informal learning.

78% of corporate managers believe that “rapid rate of information change” is one of their top learning challenges (800+ HR and L&D managers surveyed in 2008).

Need quantified

The fundamental enterprise need addressed by Connectivism is of creating an agile, innovation led workforce. If we view agility as the capability to make effective decisions in response to fast changing market conditions and the capability to learn new skills quickly and efficiently, we need a workforce that can learn informally, with minimal supervision, with greater involvement in and control of in their own learning, that can keep itself abreast with fast changing information, that can encourage diversity of opinion and thought which are at the core of effective decision making and that can self organize in order to bring a sense of orderliness in a mostly chaotic and competitive business scenario.

At the same time, since attempting to maintain large budgets and teams to structure formal training (and maintaining the associated infrastructure, processes and overheads), is fast becoming impossible given the pace and the nature of the inflection point upon us, there is a huge need for us  to rethink our approach and strategy for training.

What could the solutions be?

Ideally, connectivist solutions for the enterprise would at the very least require the following:

1. Ability to connect
2. Ability to self-organize
3. Ability to engage in meaningful sharing and collaboration

The ability to connect involves focusing on the tools, processes and policies maintained by the organization. On the tools side, this would typically involve creating multidimensional visibility to people and resources – across dimensions such as roles, departments, learning context, domain, locations and perhaps even customer accounts. This transcends the thought of simply having an address book with contacts.

Also, since the connections are crucial, there must be a way to model and represent the building of these connections using group and network behaviour theory and by measuring/representing the strength of ties.

As one of the key success factors is the ability to build a core inner network of people and resources (the “right” filters) so that relevant information and learning becomes available when you need it, these representations could be multi-level, distributed and contextual.

The policies and processes for connection forming, by themselves constitute a large area of focus. Networks, truly autonomous and diverse ones, would have no barriers to information and connection making – and that is their strength. However, organizations would be wary of breaking silos unless there are clear and compelling reasons to do so. The answer lies somewhere in between – in a balance between the two – unique to every organization.

The second requirement – the ability to self manage – exists both at the level of the person and the group/network. Personal Learning Environments (PLEs), an ecology of tools and techniques to manage access to and interaction with knowledge and networks, assume special significance in this context. Existing knowledge management system architectures need to embrace this concept.

The ability to self-organize is critical for collaborative problem solving, for instance, where small focused groups get together to combat a learning challenge or solve a problem. At the personal level, it could refer to capacity to react in a structured and critical manner to a learning problem or challenge. This ability is also contingent, in group settings, on the ability of the group to engage in practice and reflection. As Stephen Downes puts it:

The PLE is not an application, but rather, a description of the process of learning in situ from a variety of courses and according to one’s personal, context-situated, needs. The process, simply, is that learners will be presented with learning resources according to their interests, aptitudes, educational levels, and other factors (including employer factor and social factors) while they are in the process of working at their job, engaging in a hobby, or playing a game.

The third requirement, the ability to collaborate and share meaningfully in a given context, and its corollary, the ability to record these conversations for access and retrieval by an audience in a similar context at a different point in time is also a key requirement.

Collaboration acquires a different complexity in Connectivism. Firstly, the media for collaboration itself is diverse (blogs, video, visualizations, mind maps, media mash-ups, slide-sharing, image sharing etc). Secondly, the collaboration types span a large range between synchronous, immediate & immersive to asynchronous, “slow” & virtually isolated collaborations. Thirdly, key skills for the learner are reflection and practice that really call for a higher level of engagement with the network.

To this end the current landscape offers little, if any, support for structured brainstorming or collaborative construction (imagine an application of Six Thinking Hats on SecondLife, for instance), although tools are emerging as we speak. Therefore, the need of the hour is to bring complex collaboration possibilities using a mix of new tools and formats to learning. For example, the Delphi technique as a means of bringing about consensus and predictability in a discussion area would be a powerful mechanism, as would be the capability to don various thinking hats in a discussion.

While researching structured collaboration techniques, I came across some interesting work people are doing. Mindquarry, for example, provides a model of collaboration patterns based on 4 elements – people, productivity software, collaborative software and methods. I had earlier referred to Mindtools, who provide a rich set of structured collaboration techniques, like for example starbusting, which is a form of brainstorming. Also, Value based management offers a host of techniques, models and theories.

Essentially, structured technology aided collaboration techniques are a medium through which learning efficiencies can be increased. These techniques:

• are contextual to domain
• are contextual to collaboration type (say, brainstorming vs voting)
• are open or close ended (in terms of time, scope, boundaries etc)
• could be ad-hoc or planned
• are quantifiable (both quantitatively and qualitatively speaking)
• are historically referenceable (audit trails for recorded collaborations)
• have rules of engagement
• can be structured to the desired level (sequence of activities, organization of inputs, permissions and access roles)
• are sensitive to scale of audience, available knowledge and other physical parameters
• result in trackable outputs/analytics

The logical next step, from a design perspective, is to attempt to model them.  Aldo de Moor’s paper on Community Memory Activation with Collaboration patterns yields some insights on what patterns could be modelled. The abstract for the paper is:

We present a model of collaboration patterns as reusable conceptual structures capturing essential collaboration requirements. These patterns include goal patterns (what is the collaboration about?), communication patterns (how does communication to accomplish goals take place?), information patterns (what content knowledge is essential to satisfy collaborative and communicative goals?), task patterns (what particular information patterns are needed for particular action or interaction goals?), and meta-patterns (what patterns are necessary to interpret, link and assess the quality of the other collaboration patterns?). We show how these patterns can be used to activate communities of practice by improving their collective, distributed memory of communicative interactions and information. We outline an approach that structures how collaboration patterns in communities of practice can be elicited, represented, analyzed, and applied. By presenting a realistic scenario, we illustrate how community memory could be activated in practice.

The other key component is to understand what the need to collaborate is and the forces impeding the required collaboration. This is key to understanding whether collaboration techniques shall be used, substituted by informal methods or not used at all. It is important to understand if they are “over sold and under used” or are “methods seeking an application” or are really cost-effective or intuitive. We have seen that in software engineering too and this may require change management to implement in enterprises.

In other words, the challenge is not quite really all about the technology or process, but is perhaps more about the individual mindset and the overall objectives with which structured collaboration techniques are to be implemented (basically saying that a great process or tool does not automatically ensure collaboration that follows the process or uses the tool or format).

It goes back to us, as individuals, and how we collaborate as subjects, alone or in teams or in networks. If the capability to collaborate in structured ways is learnt and becomes “native” so will adoption on a more widespread basis. On the other hand, organizations or learning delivery modalities can include, as mandatory components, such patterns, tools or processes as part of the workflow.

There also need to be mechanisms that are able to keep communities and ideas alive and receptive to new inputs past their lifecycle. As Harold Jarche says:

If learning is conversation, then online conversations are the essential component of online learning.

Or, as Nancy White puts it, learning is more than conversation:

…conversation is one of the three legs of my learning stool.

Conversation – making meaning, getting different perspectives, trying out and testing ideas, challenging assumptions.

• Individual reflection – (because group reflection is a subset of conversation, no?) Stepping back, reviewing, observing, evaluating our own learning both in terms of process and content. Reflection provides us needed self awareness and the ideas we bring back into conversation.
• Reification – borrowing from Communities of Practice theory, what we create that expresses what we are learning or have learned. With internet tools makeing self publishing so easy, this area has blossomed – videos, images, blogs — things that manifest both our conversations and our reflections and put them out for wider consideration.

These three are a vortex, always intersecting with each other, even competing for our attention

Obviously, while blogs and wikis provide a good starting point, these three requirements go beyond, perhaps, the sophistication of existing technology and practice, thus building the case for rapid innovations in educational technology and the establishment of best practices.

Benefits to the enterprise

Implementing Connectivist principles in learning and development will bring many benefits to the enterprise. Some of these are:

• Agile, adaptable workforce
• Knowledge base kept current by the learning community
• Community decides using collective insight
• Important challenges are immediately highlighted
• Diversity brings creativity to the forefront
• More space for innovation
• Self organizing learning formations become responsible for managing change
• Informal learning gets channelized/formalized
• Connected enterprise can more efficiently meet needs – now and in future
• Reductions in cost in many ways such as in content development and management of centralized systems and their supporting processes
• Styles of learning more in line with the expectations of the Net Generation

Wenger states the following as a benefit of CoPs:

They are nodes for the exchange and interpretation of information. Because members have a shared understanding, they know what is relevant to communicate and how to present information in useful ways. As a consequence, a community of practice that spreads throughout an organization is an ideal channel for moving information, such as best practices, tips, or feedback, across organizational boundaries.

They can retain knowledge in “living” ways, unlike a database or a manual. Even when they routinize certain tasks and processes, they can do so in a manner that responds to local circumstances and thus is useful to practitioners. Communities of practice preserve the tacit aspects of knowledge that formal systems cannot capture. For this reason, they are ideal for initiating newcomers into a practice.

They provide homes for identities. They are not as temporary as teams, and unlike business units, they are organized around what matters to their members. Identity is important because, in a sea of information, it helps us sort out what we pay attention to, what we participate in, and what we stay away from. Having a sense of identity is a crucial aspect of learning in organizations.

They can steward competencies to keep the organization at the cutting edge. Members of these groups discuss novel ideas, work together on problems, and keep up with developments inside and outside a firm. When a community commits to being on the forefront of a field, members distribute responsibility for keeping up with or pushing new developments. This collaborative inquiry makes membership valuable, because people invest their professional identities in being part of a dynamic, forward-looking community.

Challenges

What are the challenges that organizations will face in this environment?

“Legacy” everything

The first challenge will be related to legacy content, infrastructure and training programs. An important thing to note is that the “legacy” qualifier applies not only to content but also to infrastructure and training processes in the Connectivist context. We need to ask what the migration or transformation path is for all three, not just content.

From the content perspective, a key factor shall be the generation of content by the participants in the learning process, not just by the traditional content developer. Therefore existing content shall be either referenced as-is or repurposed into new formats for easy consumption by the network (e.g. WBT to Wiki sections). Let us take the example of software training. Content that is traditionally found in user manuals or web based training could be used as-is or converted into a wiki. This wiki content could then be updated by the community itself when there is a new release or when they need to update or correct existing content. Obviously, the community will need a process and controls that it owns and is accountable for when making these changes.

For multiple reasons, as discussed above, we shall be challenged to introduce new technology that will render large components of existing technology incongruently positioned. How Learning and Development functions (and vendors of these systems) adapt the infrastructure shall be critical and will go beyond mere addition of (say) a blog component to an existing LMS product. For example, SCORM compliance is something that is a given for most organizations that need to standardize reporting and tracking of learning activity on online courses. With the new technologies, this will certainly no longer be a core requirement for informal learning.

Learning platforms are being “re-examined.”  Most of the companies we talk with are significantly rethinking their entire learning platform strategy (LMS) to understand how to evolve or add new systems which support collaboration.  And today’s LMS is not as successful as one would believe:  across all the organizations we studied (approximately 900 different organizations), on average only 51% of employees use the learning platform at all.

 I firmly believe that this new form of software-enabled collaboration is a revolution, not an evolution.  Like many of the software innovations that I have personally witnessed over my career (e.g. the first color graphics PC, the CD-ROM, the web-browser, Flash, SaaS architectures, and others), social networking is really going to shake things up.  The reason is that these systems are both complex, data-rich, and require a new type of software architecture.  A system which supports 200,000 employees and customers with in-depth employee and customer profiles, active communication and blogging, tagging, content management, custom branding, and tracking each and every communication is quite a complex software solution.  As we examine these vendors we are finding some very significant new areas of functionality which are going to change and upset the traditional HR software companies.

The training processes themselves will need to be rethought from a networked learning perspective. For example, in traditional systems, resource scheduling and management is an important activity for scheduling instructor-led training. This is usually a centralized activity. In a networked learning environment, this would in effect be a decentralized activity managed by the community itself. Similarly, collection of learner feedback from scheduled learning events shall again become a function of the community.

Return on Investment

Secondly, how will return on investment be measured? This is a question that needs to be answered for every initiative. To craft an effective response we must be able to understand what constitute metrics in an organization and what would substitute or complement these metrics at a community level.

Currently metrics that are used are both quantitative and qualitative. In quantitative terms, metrics are based on tracking of attendance, satisfaction surveys, scores and completion in a hierarchical manner across the organizational structure (by division, department, location, portfolio etc). The collection of raw data for the performance metrics is from test and survey questions and their responses. The crucial point here to appreciate is that these metrics are already an ineffective measure of learning in the enterprise, something that leads enterprises to spend time and effort for validating from a variety of supporting sources.

Even a brief survey of the field of assessment design can inform us of the problems in classical test design and development. Due to these, recognized testing agencies like ETS (e.g. GRE and SAT) and psychometric assessment providers use rigorous techniques for item creation and validations (computer adaptive testing, item response theory and now perhaps simulations & virtual worlds led testing) long before these tests make it to the learner.

Secondly, SCORM as a standard or most LMSs do not provide any way to capture more complex performance data such as, for example, the path taken by a learner in a case study or role-play (although there are some current initiatives that may help, such as HLA for simulations, gaming and the convergence between SCORM, DITA and s1000d).

Thirdly, existing content developers may not have an appreciation (even if enterprises had the budgets) of the challenges involved in effective (reliable and valid) item creation and validation in the context of these classical testing theories. A similar challenge may perhaps arise in processes such as the identification of competencies for a specific role in the organization and aligning learning and development plans with existing competency models. Obviously, every effort is made by Learning and Development organizations to correlate and validate this data from a variety of sources.

But if these metrics are inefficient already, the question that needs to be asked is – are the RoI estimates generated on the basis of these metrics efficient? Or are these claims valid?

Over 30% of all corporate training programs (ie. classroom or other formal programs) are not delivering any measurable value (data provided through the same survey).

Qualitatively, the assessment mechanism also suffers significantly. Did the learners actually learn? We know that given already low organizational budgets for training and development, most corporations are unable to deploy more expensive, but qualitatively more efficient, learning materials and experiences to their learners.

As a direct result, a large component of learning (estimated to be as large as 80% by Bersin) is by way of conversations, not included in computing any RoI metric.

80% of all corporate learning takes place through on-the-job interactions with peers, experts, and managers (estimated data collected from over 1,100 L&D managers late in 2008).

Intuitively it seems to be a plausible assertion too. People reach out to their network of people and knowledge for help and mentorship quite regularly, even if it is to ask a question or clarify a procedure. A lot of that time spent goes undocumented, perhaps because the individual instances of learning there are in the form of compressed and short and short bursts, not track-able because of the medium of conversation (often verbal) and the frequency.

These learning events take place outside the formal learning event itself, and in some cases, are the equivalent of the formal learning event (where no formal learning exists). A lot of these conversations also result in serendipitous learning. As Polanyi believed, knowledge is personal and tacit, not directly expressible but “known” and demonstrable through action. Tacit knowledge is hard to measure and possibly a large component of informal learning (“the aim of a skilful performance is achieved by the observance of a set of rules which are not known as such to the person following them”).

If it is a plausible assertion, then it is plausible as well to think that enterprises are spending 80% of their budgets on the 20% of formal learning.

Then there are questions, like the one below, on the effectiveness of RoI as a measure in it self.

“I don’t know how useful ROI is in determining the value of training,” Valenti says. “Most of the real ROI is wrapped up in the initiative that training is supposed to support, such as a new product launch or a process improvement. I’d rather see people think about return on expectations, such as whether employees actually are following the new process they’re supposed to be following. Being able to demonstrate ROI is great, but there’s lots of training that supports organizational objectives and goals even if the ROI can’t be shown.”

[Diane Valenti, Applied Learning Solutions]

Thus, the other key impact of Connectivism is on re-evaluating the metrics that have traditionally been employed to judge training effectiveness and RoI. Instead of traditional measures, the appropriate quantitative and qualitative metrics could be based on (Albert Bandura’s) self-efficacy (“relates to a person’s perception of their ability to reach a goal”) of the employee and the question “how connected am I?” or “how do I deal with fast changing and exploding information?”. Accordingly, metrics in this context could be based on the following factors:

1. the degree of connectedness of an individual to the network
2. the collaboration between any two networks
3. the quality of interaction in the network, something that network domain managers could be held accountable for (in addition to the learners) and could be measured in a host of different ways – reviews, rating, external assessment, relevance ratings etc.
4. the impact on the business (by measures that correlate things such as the quality of tasks performed by role and the degree or frequency of use of just-in-time materials or resources used in completing that task)
5. tracing the dynamics of performance over a period of time as reflecting in the growth of and participation in individual networks for each individual learner
6. reviews and ratings by peers, experts and managers – both for individual contribution and quality of resources

Charles Coy from Cornerstone makes an interesting comment:

Incorporating multiple modalities of learning is not the challenging part. We can build communities of practice into business workflows and develop social media environments. The challenges, in Cornerstone’s view, revolve around engagement and tracking. Getting people to contribute and then assessing the value of this 80% social learning element for the organization. (emphasis added)

Impact on Talent Management

Thirdly, what will be the impact on Talent Management? There are obvious applications for talent acquisition and retention that can effectively utilize Web 2.0 technologies, but what are the connotations when we deem job descriptions, roles and competencies as emergent in learning cultures – shaped by and shaping enterprises continuously in ways that are as influential as external market factors confronting a business. The organization decides what it needs to do at a point in time and decides to be evaluated in a particular way. In many ways, this mirrors what learners do today – build new competencies regularly to adapt and negotiate in a fast moving environment.

A key question is on how we should include “learning through connection-forming” or “sense-making” as an organization wide competency. Dave Pollard states it succinctly when he writes:

In a world with a billion people online, connected in multiple and unfathomably complex ways, how do you find, and then connect, with just the right people to do what you need to do?

IP Protection

Fourthly, it is important to consider protection of confidential information. In a recent study commissioned by AT&T and conducted by Dynamic Markets, a sample of 2510 adult employees were interviewed who used a computer at work. The top two challenges mentioned were distraction to employees and leaking of confidential company and employee information.

Networks and Evolution

Communities of Practice

Wenger’s approach to Communities of Practice (CoP) also provides specific implementation cues. As Wenger states, CoPs form around three dimensions – what it is about, how it functions and what capability does it (or needs to) produce. This is a useful way of identifying areas of implementation for connective learning.

This will require specialized processes and tools. Processes and workflow (roles, rules and routing) will need to be placed, in-context of the learning and business goals, and best practices created.

For example, Wenger provides a blueprint for some of the roles that can exist for the internal leadership of the CoP, which he believes are key to its development. The roles are:

# The inspirational leadership provided by thought leaders and recognized experts

# The day-to-day leadership provided by those who organize activities

# The classificatory leadership provided by those who collect and organize information in order to document practices

# The interpersonal leadership provided by those who weave the community’s social fabric

# The boundary leadership provided by those who connect the community to other communities

# The institutional leadership provided by those who maintain links with other organizational constituencies, in particular the official hierarchy

# The cutting-edge leadership provided by those who shepherd “out-of-the-box” initiatives.

Network of Practice

Building upon Lave and Wenger’s communities of practice, Brown and Duguid developed the concept of Network of Practice. Ranging from communities of practice to electronic or virtual communities, and differentiated from formal work teams, it focuses on how individuals come together to learn and collaborate in the context of their daily practice or tasks.

Defining networks as a set of individuals that are connected together in a social relationship (strong or weak ties) and practice representing the common area of focus or substrate that links the individuals together, the network of practice is differentiated from other types of networks such as photo sharing insofar as this kind of a network is based on a practice area where individuals engage in a conversation to ask and share in order to perform at their work.

Networks of Practice (NoPs) include communities of practice (where ties are strong and face to face interaction is predominant) at one end of the spectrum, to electronic networks of practice (typically virtual/electronic communities brought together by weak ties) at the other end.

NoPs differ from formal work teams primarily in the way they are structured and by their control mechanisms. They also differ in terms of their size (they can get very large) and by restrictions on membership.

Existing Technology Vendor Approaches

Janet Clarey’s interviews with LMS providers reveal other implementation perspectives, perhaps not all as well informed by connectivist theory, but nonetheless cognizant of the power of networked learning and social media. For example, Jeff Whitney from Outstart states:

We developed our social media platform separate from our LMS as many informal learning initiatives do not require the formal reporting and tracking features of an LMS.

Generation21 believes that the network function is really a feature, an option to customers to exercise if they so require. And Mzinga is prepared to allow customers to balance emphasis between formal and informal learning modes with “deep direct links” to the former for “certifications, compliance, curriculum…”.

Just as CBTs (computer based training) evolved into WBTs (Web based training), we are seeing now the emergence of, what I call, NBTs (Network based Training) and blended training options that include blogs and wikis as one of the components of the blend. Whatever be the exact mode of bringing in networked learning, enterprises can now start assessing this new framework for their own specific uses.

In essence, then, there is the conflict between adopting networked learning as a standalone social platform, a “hybrid” blend of formal and informal learning and as part of a pure Connectivist model of learning.

The LMS providers are thinking of informal learning as either ancillary (supporting a formal learning program, like an additional component that is blended in), optional (that users can use if they want) or for pure collaboration purposes (the individual knowledge sharing community purpose).

However, a pure connectivist model would start from individuals discovering others through weak ties around an area of shared inquiry; a model where learning and knowledge evolves in parallel with the ability of learners to make connections. Too much structure and control upfront, as in the standalone or hybrid approaches, will inhibit the fundamental aim of a connectivist learning approach, which is to build key learning abilities such as wayfinding and sensemaking. It may also mute and morph the change and lull us into believing that Connectivism is yet another way to teach, learn and administer training using Web 2.0 technologies.

For organizations, Connectivist approaches may be applied to some areas, while there may be a mix of other approaches for other areas including the formal training approaches.

Learning Ecologies

As opposed to other theories, Connectivism provides a framework that is based on an explicit understanding of the role of networked, distributed learning. Of core importance to educators, the ecology for learning becomes a key for engendering connectivist learning.

As Jane Hart, Harold Jarche, Clark Quinn, and Jay Cross state:

Most of us agree on where we’re headed: to ecologies where work and learning are one and the same, where people help one another build competency and master new crafts, where members of self-sustaining communities of professionals participate because they take pride in maintaining their standards and doing a great job, and where everyone strives to be all she can be. Open, participative, bottom-up, networked, flexible, responsive: that’s what we’re after.

A Connectivist learning ecology inherently:

• Enables us to recognize and interpret patterns that exist (way finding, sense making); indeed, generate our own new patterns
• Helps us build adaptively on and capture existing patterns given a rapid changing core and diverse knowledge sources
• Provides a distributed environment (both for knowledge and people)
• Provides avenues for social collaboration
• Is technologically enhanced to deal with diverse processes/circumstances such as negotiating information overload, self organization, determining order within chaos etc.
• Enables us to leverage and expand on a network that is diverse
• Helps us build ties at varying strengths that in turn may determine the efficacy/effectiveness of our learning
• Enables us to negotiate complex learning needs

These ecologies force us to reconsider the roles of the educator, the instructional designer, the visual designer and the learning technologist even as it impacts how managers and vendors contribute to the learning organization.

Learning Formations

In this context, it is important to consider two dimensions – how do groups form and how do they evolve in an enterprise context. Stephen Downes clearly demarcates networks from groups.

A group is elemental, defined by mass and sameness – like an ingot of metal 

A network is diverse and changing, defined by interactions – like an ecosystem

Stages of Evolution

This distinction is an important one because it spans different types of learning collaborations possible. In a learning network, we may expect different types of such collaborations – that I term Learning Formations. Three possible types are:

1. Instant, ad-hoc, workflow based, just-in-time learning formations – these are characterized by short bursts of interactions and great diversity, typically simple collaboration types with no structure that needs to be defined, such as in Twitter, IM and simple media sharing
2. Short term learning formations characterized by heavy bursts of interaction and purposeful collaboration – typically what we would find in training contexts today or blogs
3. Long term learning formations – formations that are cohesively built around a reasonably long term commitment, focussed goals and complex domains. These would be highly structured environments such as in CoPs.

If we tried to map models of group development, such as Bruce Tuckman’s Forming-Storming-Norming-Performing-Adjourning model, or George Charrier’s Cog’s Ladder Polite-Why we are here-Power-Cooperation-Esprit stage model, we can perhaps look at instant learning formations occupying the early stages, the short term learning formations placed somewhere in the middle and the long term learning formation at the end of the spectrum.

It is important to emphasise how network formations could possibly evolve. If we look at George Charrier’s Cog’s Ladder model, there are five stages to forming efficient groups. These are:

• the Polite stage – where members get acquainted with each other, engage in dialogue and verbal spars to really assess each other and what they bring to the group
• the Why we are here stage – where members rally around a common context, whatever their individual motivation is, facilitated by a moderator or leader
• the Power stage – where opinions, dissensions or simple abstentions dominate the interaction
• the Cooperation stage – where members realize that to meet the common goal they need to accept diversity of thought and opinion
• the Esprit stage – where mutual acceptance, team spirit and learning efficiency is the highest

If we look at Bruce Tuckman’s five stage model, it has:

• Forming – similar to the polite stage in terms of making acquaintances and assessing the other members and their abilities, but includes context setting and motivation with a lot of direction being provided by the team leadership
• Storming – where different perspectives compete for attention and conflict may undermine progress towards achieving goals
• Norming – where trust, motivation, agreement on rules of the game and participation become enhanced and team members get more acquanted with the how of achieving shared objectives
• Performing – where team members are highly motivated, become really knowledgeable, manage conflicts amicably and participate at a deep level
• Adjourning – where when the goal has been achieved, teams disband to pursue new tasks or learning goals.

Wenger also depicts about the 5 stages of development for a Community of Practice. These are:

• Potential – people face similar situations without the benefit of a shared practice
• Coalescing – Members come together and recognize their potential
• Active – Members engage in developing a practice
• Dispersed – Members no longer engage very intensively, but still the community is alive as a force and a center of knowledge
• Memorable – The community is no longer central, but people still remember it as a significant part of their identities

In all models, there may be iterative cycles as new members are inducted or issues arise that force the group back to a prior stage.

Whether they are called groups, networks, connectives, collectives or communities, these are learning formations that are characterized by factors such as:

• life cycle – duration and phases (length of the interactions, the progression from one stage to the other)
• interaction frequency (index of user participation in the interactions)
• interaction depth (index of user participation in terms of the quality and inter-relationships in the interactions)
• complexity of domain (quality and amount of knowledge and its complexity)
• extent of formal structures and processes (roles, workflow, leadership, accountability, open-ness)
• formation size (the number of people involved)

If we attempt to connect learning to Tuckman’s stages in development for learning formations and to Web 2.0 technologies that are available today, we can perhaps group them into three segments as depicted above.

The first segment (Ad hoc) is characterized by a high level of diversity of opinion, open-ness, ad-hoc relationship creation and a very utilitarian workflow or just-in-time type of interaction. Examples include a twitter network, IM or Facebook, simple sharing of photos or videos or presentations and quick queries through services such as Yahoo! Answers.

The second segment is where I would place traditional learning and some part of the learning 2.0 style. Formations that occur here are typically those who will get to some extent to the performing phase (and thereon to organizational or institutional excellence). A degree of formal structure starts becoming visible here, whether it is an LMS controlling enrolments or an instructor leading a class.

The third segment is where things start getting complex. These formations are tightly focussed and driven by commonly accepted goals. Examples include CoPs (Communities of Practice) and massively multi-player on-line role playing games (MMORPGs) and where gaming, simulation, e-portfolios and immersive learning environments would fit naturally and play a great role. These formations would be highly structured, deal with higher complexity, have higher frequency of interaction, higher indices of user participation and would move all the way up into the performing stage relatively quickly.

However, as George Siemens cautions when he quotes Uzzi Shapiro in Connectives and Collectives: Learning Alone, together,

“Intense connectivity can homogenize the pool…high cohesiveness can lead to the sharing of common rather than novel information” Uzzi, Spiro (2005)

The thought is that as ties become stronger and individuals aggregate into groups and collectives, the discourse becomes normed (in fact there is a veritable coercion to the norm) that leads to a drying up of new ideas that are novel and diverse.

Barry Wellman describes how communities have evolved from being in “Little Boxes” (densely-knit, linking people door-to-door) to “Glocalized ” networks (sparsely-knit but with clusters, linking households both locally and globally) to “Networked Individualism ” (sparsely-knit, linking individuals with little regard to space).

The basic thesis is that since learning formations may be manifested and may evolve in many ways, an understanding of these types is important to build effective learning ecologies at the enterprise level.

Enterprise Implementation

This brings us to an important question. If there is a strong case for Connectivism in the Enterprise, is there also an implementation methodology that is established and can be immediately used?

One perspective, that was heavily process oriented & steeped in real life experiences, argues that unless processes and workflows (and related metrics) are established, implementing these tools in the enterprise would be exhausting and with little return for the amount of effort it would take to manage and the money it would cost.

Then there are formal approaches for CoPs such as the one laid down in the Defence Acquisition University (DAU)  Community of Practice Implementation Guide, which provides a 14-step, 3 phase process for setting up practices that could contain CoPs, Shared Interest Areas (SIA) and collaborative workspaces. This document is very elaborate and covers processes, roles, permissions, workflow, engagement rules and metrics for setting up CoPs and community knowledge bases.

With true process orientation, this document provides a fairly detailed best practice for the DAU in its community development initiatives. What is important is the fact that it leverages the same principles that we would use to create and manage an enterprise unit.

Another perspective revolves around how useful or participated in really are blogs and wikis. Talk CoPs or networked learning, and all that people think of is Web 2.0 technology and tools, the hype not really difficult to understand, given that major technology vendors are pushing for implementation of these tools in their recent launches.

Endgame. The perception that the process and/or the technology are responsible for making networked learning happen is problematic. This is especially true given the power laws we have experienced in terms of community participation and effectiveness or the constant refrain that elearning is not, perhaps, living upto its potential.

Stephen explains in his post, Connectivist Dynamics in Communities, that connectivist networks produce connective knowledge. Four elements distinguish a knowledge-generating network from a mere set of connected elements. These are autonomy, diversity, open-ness and interactivity & connectedness. There are compelling arguments that Stephen makes, as in the past, that we need to respect these elements if we want to increase the probability of generating new knowledge (and make sense of the current base of knowledge). These elements can also be the basis of metrics and tracking.

George laments the inadequacy of tools for sense-making. He also declares “…But any view of society that does not start with the individual is disconcerting.“

All these views, taken together, suggest that there is something more to networked learning than just processes and technology. It is a connectivist approach, a model that focuses on how we learn, that provides us a different lens through which to regard fundamental questions such as how do we learn to perform in a fast changing environment or how do we get incited to participate in a network to create new knowledge.

The Connectivism Development Cycle

In his book Knowing Knowledge, George Siemens painstakingly describes a possible implementation model (pp124-141) for organizations to adopt. He states (p 128):

Connectivism implementation begins with the creation of new organizational structures. New organizational structures then direct or allow for new affordances. The combination of new spaces and structures and affordances permit the implementation of Connectivist approaches to learning and knowledge flow in learning, communicating, collaborating, marketing and other organizational activities.

Giving us a sense of how deep the change is, Siemens writes (p 128):

Tinkering around the edges, in constant conflict with the balance of the organization, is a taxiing and frustrating process. For these reasons, I have chosen to present a wide scale implementation of Connectivism, instead of smaller scale views.

The Connectivism Development Cycle (CDC), according to Siemens, includes the following domains:

• Analysis and Validation – analyzing and validating the existing knowledge processes (how does knowledge flow?), the social network, structure of the organization, learning mission and culture
• Ecology and Network Design and fostering – the external design of nodes of information, tools and techniques along with the processes for fostering and guiding internal (knowledge) networks.
• Adaptive Learning and knowledge cycle – where digital, network and network formation (connection-making) skills are a new competency to be developed by organizations in their employees. In this domain, organizations can play a crucial role in establishing the purpose of the learning ecology, defining individual and ecology identity, establishing the relevance to daily work, making it easy to use and accessible, allowing network formation through social relationships, encouraging diversity and monitoring change & contribution.
• System review and evaluation – how the organization evaluates the effectiveness of the ecology (metrics such as those for innovation, quality of learning, better customer service) and RoI (metrics such as those for reduced expenses, increased revenue, increased personal effectiveness, capacity to meet new challenges and organizational ability to adapt & transform
• Impacting factors – factors such as the time available for development, budgets for development and change, learning intent, availability of technology and competence to use the new technology.

An alternative approach to Implementation

To this end, I propose a phased approach.

A starting point, in my opinion, would be to create an environment wherein employees could get engaged with the new medium inside the workplace and learn the skills required to operate in this ecology – making connections, navigating information, sharing and collaborating through weak and strong ties. The primary movers in this phase would be community coordinators and subject matter experts who would be responsible for setting up most of the content in a way that can be disseminated to the rest of the community. This would be akin to a Norming stage.

The second step would be to allow the members of the learning enterprise to practice these skills to access information and organize it in a way that is aligned to their work. For example, they could view and comment on what the experts have put together. And this could be among other special initiatives designed by the coordinators to engage members and help them build expertise and interest in participating. At this point, we should see many more ideas from all over the network on how they should be organized into sub-networks or communities of practice and some amount of self organization will begin to emerge. This would be similar to a Storming stage.

Once this has been accomplished, these skills need to be placed inside a work context – a specific domain area, a problem to be solved or an innovation to be pioneered. As individuals and departments experience the power of this framework, and the learning implicit within it, connective learning should be formalized within the context of a business goal – e.g. launching a new product and making sure all employees learn how to market and support the product. The first RoI will and should emerge from demonstrable business results from engaging this framework. This is where networks in the enterprise shall have started performing in response to business needs.

Summary

In summary, enterprises today can greatly benefit from a Connectivist approach to learning and development. Not only that, it is fast becoming imperative for Enterprises to embrace networked learning, leverage social media, recognize changing learner preferences and reduce training costs to survive and grow in an intensely challenging marketplace. Connectivism provides a framework for learning in the digital age that allows us to do exactly that.

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The Digital Isolation of Classrooms

Our classrooms are digitally isolated by their very design. It is a distortion of our bureaucratic education systems wherein, on the one hand, grade levels are broken down into separate groups/classrooms, insulated from each other, while each group is encouraged (or mostly not) to independently interact with the outside world.

As a result, students learning the same concepts (from perhaps the same teachers), cannot break the confines of their own classroom group, to celebrate their own local diversity, far less the diversity offered by classrooms worldwide doing almost exactly the same thing, separated by time and space.

This distortion is brought upon us by our approach to managing scale in the education system. Although at one end, developing nations like India still see a significant number of one-room schools (multi-grade single teacher classrooms; in India the figure is around 10%), the vast majority of our classrooms at any level of education stand singularly insulated.

Is this distortion healthy? It is not. In an inter-connected world, fast augmented by accessible technology, our research shows us that increased diversity in the classroom leads to more tolerance, better thinkers, stronger communities, more successful employees and happier lives. It improves the self-efficacy of learners so they become exponentially better performers for the long-term and not just at a particular grade level or assessment. By also co-operating and sharing, they increase their own capacity to learn – a skill that is severely under-rated by bureaucratic systems of education, leading to reflections such as Do Schools Kill Creativity. Clearly, group wise insulation implies a loss of shared experience, so vital for individual sense-making.

This distortion permeates other aspects as well – for example, teacher performance is measured group-wise and in isolation from teacher performance elsewhere. Even for teachers, there is this near-complete isolation between the classrooms she teaches and what others teach, in the same location or worldwide. Thus this impacts teacher self-efficacy as well – her ability to evolve and grow. The same could be said for school leaders.

In a system so shorn of collaboration, we cannot celebrate the benefits of diversity and connected-ness. The distortion in the system ensures greater isolation, thereby lower levels of efficiency for all stakeholders. So far, this distortion is likened to commonsense, with increased diversity desirable but deemed impractical at scale. As a result, very little, if at all, of our education system is geared towards connection-making (in the Connectivist sense) for teaching and learning.

It behoves us to step outside the frame. By looking at increasing connected-ness and diversity in and across our classrooms, we can generate more opportunities for achieving high levels of quality in our systems of education.

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Imagining another future: Teacher Cooperatives

Let us for a moment imagine a future where schools are run by teachers’ cooperatives. That is, instead of an administrative and financial superstructure of wealthy philanthropists or businesspersons or trusts, political muscle, non-academic leadership and all the trappings of modern world schools, teachers would cooperate to teach, learn and administer the school.

The Amul cooperative in India posits a model for cooperatives in the Dairy sector.

The then Prime Minister of India, Lal Bahadur Shastri decided that the same approach should become the basis of a National Dairy Development policy. He understood that the success of Amul could be attributed to four important factors. The farmers owned the dairy, their elected representatives managed the village societies and the district union,  they employed professionals to operate the dairy and manage its business. Most importantly, the co-operatives were sensitive to the needs of farmers and responsive to their demands.

In Education, this is not new (Avalon, SUPAR, Woodland Park). In Can Teachers Run Their Own Schools, Charles Kerchener talks about how such schools lack closed structures, promote open-ness and put greater responsibility on students to manage their own learning.

Advisor Kevin Ward, writes that students who come from a traditional school think, “that an open environment is
the equivalent of an unsupervised study hall and act accordingly. They wait for bells and whistles and detentions and plenty of assignments.” “Parents may expect to see immediate success,” but “learning to become an independent learner takes not only time but a good measure of failure.” These students become successful over time, Ward asserts, because students create their own rules. That struggle can take a long time, sometimes two years before a student understands that success is primarily a function of what they put into it as opposed to how well they play by someone’s rules. Contrast this with scripted teaching, frequent teacher-led drills,
and frequent testing that characterizes some charter schools recognized as successful.

…But regardless of the hours put in, students must design projects that meet all the state standards.

…The credit system—perhaps the most enduring structure of American high schools—is relegated to a bookkeeping function

It is interesting how these cooperatives are organized and how do different stakeholders react to shared leadership and open ecosystems. It is important to note that the exact shape and form for these cooperatives is not something that is designed. Rather it is emergent, based on the dynamics of the people, context and tools.

In India, I have yet to come across a similar vision. Doubtless, there exists someone doing it, but it is an idea not yet discussed or explored in policy or other academic circles, at least from what I know.

However, there is merit in discussing this model if it leads to increased stakeholder trust & respect, higher quality learning, diversity and autonomy. What if there were a significant proportion of cooperative schools in India catering to local needs, responsive to local community, and creating environments where students could really take responsibility for their own learning? Such cooperatives could be served by other cooperatives as well – for needs ranging from administrative/professional services to even needs such as teacher education and leadership development.

Can such a future be?

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#rhizo15 Week Two – Counting networks

A rather belated post on #rhizo15 week 2! How do we count or measure learning in our networks or learning rhizomatically? How do we begin to “grade Dave”?

“Counting” evolution of our learning networks is very important. How does a network or community form? When does it acquire critical “mass” of conversation? How does it sustain? And when does it wither away and perhaps die, only to come alive again in the future, like a raw nerve left exposed?

The months before CCK08, then during CCK08, and Change11 and many of the early cMOOCs afforded great opportunities to discuss a multitude of ideas.

I think Stephen sparked it off by talking about Learning 2.0 in an early article. Then came a series of posts around how I viewed collaboration and evolution in networked learning (starting here). Essentially power laws were well in evidence when we looked at conversations – a small number of conversations were held together by many people and these threads were reasonably long (if I remember correctly, this was the pre-‘like’ era), while a majority of conversations were ad-hoc and short lived.

The pattern was not unlike what you would expect on the Internet prompting discussions on the long tail or that the world wasn’t flat, it was rather spiky. It also was scale-free in the sense that it could observed in small classrooms as well as the rather large learning networks of these cMOOCs.

This pattern also prompted me to think that the goal of such educational networks should be to flatten the power law, leading to a more participatory, equitable and democratic system rather than the ‘rich get richer’ bias that we have now (and Stephen writes eloquently about this, especially towards the end of that post) in his recent dialogues with George when he talks about the University system).

Which is why counting is really an important subject. We cannot continue to count the way we have been counting. But we cannot change unless we also redefine what we are counting and how we are counting it. In fact, for cMOOCs to be counted as a credible alternative (and not just a supplement like the xMOOCs), we have to devise a friendly and intuitive mechanism for counting learning in these networks.

This type of counting is necessary for people to be able to share a new common vocabulary for representing and differentiating levels of competence or progress. Unless this new vocabulary emerges, we will not have a way to transact within it, to generate economic and social choices of human capital using it and to create policy around it. It will also be difficult to get any adoption at scale.

This, in my opinion, has been the biggest block to making cMOOCs mainstream as well as the biggest reason that xMOOCs have been credible. xMOOCs have taken the same counting terms from the traditional system which is widely understood – institutional brand, expert professors, certificates and degrees, price, blended learning – which makes them intelligible to the world. cMOOCs don’t yet have a vocabulary to do that.

It is not just the vocabulary though. The vocabulary will only emerge through research and compelling evidence. It will need new tools and techniques for measurement. It will need to be able to fit in the modern world and the needs of the people. If we do not evolve such measures, cMOOCs will be marginalized as hype.

The need of the hour is for such learning networks to analyze what constitutes learning in the network and how to count it. It is easy to say that these learning networks are only suitable for certain domains or for certain types of people. But it is more difficult to believe they are a credible alternative to traditional education systems without the accompanying quantifying justifications that make the educational, economic and social value intelligible and visible to everyone.

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Is the classroom a machine?

In a Big Think article, Why Technology Won’t Save an Inefficient Education System, with Dr. Madhav Chavan, and in several other similarly argued contributions, particularly like the ones from Sir Ken Robinson (read a critique here) or Sugata Mitra.

Education over that past 200 years has been fashioned like an assembly line. Children get placed on a conveyor belt that carries them from grade level to grade level. At each stop on the way they are receive the same knowledge as everyone else. Rather than become intuitive problem-solvers, students are expected to simply absorb the facts provided to them.

The argument that the educational system is a machine built for another age implies that the classroom is itself a machine and the teacher an automaton carrying out procedures that fill student brains with knowledge.

I had a group of educators look at me with alarm and disapproval the other day when I dared to suggest that the classroom was anything like a machine. For them, a classroom was an area where each student is different, has different learning styles and demands, and where they work hard to meet the demands of the curriculum (not enough time allocated to complete the syllabus). Challenges faced in each classroom were unique, although some best practices could be arrived at through experience. Similarly no classroom is the same as any other one in terms of its constituents, its infrastructure, its language and so on. The sheer diversity at the classroom level defies machinistic interpretations.

If the classroom is not a machine, the school as a factory analogy should break down here. Why? Because the classroom is the fundamental unit of the assembly process of schooling. And if that is not a machine, then school likely is not.

Similarly, if the counter to everyone being a dumb receptacle for knowledge, is that everyone becomes an “intuitive problem-solver”, we are talking about another kind of deterministic and linear process, another kind of factory that produces a different kind of student. This was exactly what 21st century skills framework in the USA or our Indian Continuous and Comprehensive Evaluation (CCE) system has turned out to be – an addition to the curriculum that tries to generically create certain skills and orientation in students, commonly, across the board.

The point to be understood is that we are still thinking deterministically. In the article, Chavan talks about employing technology in an appropriate manner – not as subservient to the linearized school system, but as a tool to collaborate in order to solve problems. Technology enables a non-linear curriculum, emphasizing problem-solving over rote memorization, Chavan says, but impossible to implement under the traditional education system.

I think he has got it mixed up. Firstly, there is nothing intrinsic to technology that promotes any one way or form of learning over another. Secondly technology itself is not monolithic. Thirdly technology is not all pervasive enough to be a systemic component of learning. Fourthly, there is an implicit assumption that we want everyone to be great at problem solving and that there is this one giant universal conception of problem solving, irrespective of domain. Fifthly, non-linearity is a rich feature of existing classrooms, with or without the intervention of technology, in the sense that the classroom is a complex organism.

I think what they all mean to say, is that the traditional system suffers from certain constraints and obsolete practices that are making it very difficult to “enforce” alternate practices and conceptions. Let us look at some of the real constraints – the underlying causes.

Teachers are still learning the way they teach – To innovate the existing paradigm from the inside, teachers must start learning differently. If teachers start learning and using technology-enabled learning methods on their own, it will be a matter of culture for them to start using them in the classroom.

Teachers need to learn – Largely, teachers are like any other adult, and their motivation and ability to learn are immensely important to address. Mechanisms that reward professional and personal learning are largely absent in our system, and for the teachers in the public system, not integrated with career progression and salary increments.

Syllabi are too extensive – Syllabi are following their own inflationary trends. As the volume of knowledge has grown, topics that were earlier taught in higher classes, have been added to the load of the lower classes. The density and complexity of content to be taught/learned has increased significantly. The duration of time remaining the same, teachers have increasingly lesser time to focus on teaching core concepts. As one teacher explained in an alternate manner, “the syllabus is alright, it is just that the system that enforces an end date to the syllabus is wrong!”.

Technology is not ubiquitous – the availability of technology (and electrical power) itself is a core problem. Technology for computation, for storage, for protection against virus attacks, for connectivity and Internet access, for mobility – all these are real challenges in schools (and at home) today. Over time, these will hopefully get addressed by policy thrusts and reducing costs.

Constraints of the system – everything has to be taught in school, there are rigid enrolment schedules, each grade/class is divided into isolated and insular groups or sections in some arbitrary manner creating limitations on collaboration and sharing of knowledge – and many other structural components of the system. In fact, these constraints are the ones that are closer to the industrial age-factory analogy in the sense that they are the pillars of educational management in schools.

For example, putting children into groups and assigning them teachers is an operational decision – one that promotes manageability of the education process primarily. Many people say it is also logical to keep class sizes low to promote greater collaboration (and perhaps, control) and ability for teachers to address individual learning styles. But I believe that the two are different problems – there are many ways to adapt, blend or flip learning emerging now that need not necessarily force us to enforce these structures and ratios.

In summary, I think it is perhaps wrong and naive to treat classrooms as machines and teachers as automatons. Classrooms are complex organisms and don’t easily fall into the determinism of the factory analogy. However, classrooms and teachers operate under a system that tries to enforce determinism and linearity through some of the constraints discussed above.

If we want to change as a system, we need to extend, enhance and celebrate the complexity in education.

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#MOOConMOOCs – Sir John Daniel on MOOCs

The interesting MOOC on MOOCs conducted by Dr. T V Prabhakar from IIT Kanpur and Dr V Balaji from Commonwealth of Learning is in week 3. The theme itself is reminiscent of the CCK MOOCs, which did a deep dive into the Connectivist origins of the original MOOCs. It is timely also because India is really on the verge of something special in this area.

Sir John Daniel, one of the experts in Open and Distance Learning, has the following points to make in his video lecture contributed specially for the course.

• Open and Distance and Online learning did not start with MOOCs or even the Internet.
• Putting courses online does not automatically improve their quality.
• MOOCs are a good example of how computers and networks have increased the power and possibilities of ODL but they lack some of the vital ingredients of a good learning system. Many do not include Holmberg’s “guided didactic conversations” between learners and teachers and most do not include student assessment and certification.
• Everything depends on the design of the teaching learning system around the students’ needs.That must be the next step in  the development of MOOCs.
• In most cases, MOOCs are still simply information distribution systems
• Why have MOOCs been so slow in tackling the challenges of interaction and assessment? Because early 2012 MOOCs were by exclusive universities.

In his 2012 article, Making Sense of MOOCs – Musings in a Maze of Myth, Paradox and Possibility, Sir John Daniel makes some important points:

We also agree with Bates that current xMOOCs pedagogy is pretty old hat but this will now change fast. Even if Coursera gave its partner universities great freedom in course formats in order to sugar the pill of signing the contract, this will quickly produce a great diversity of approaches and much healthy experimentation.

Placing their xMOOCs in the public domain for a worldwide audience will oblige institutions to do more than pay lip service to importance of teaching and put it at the core their missions. This is the real revolution of MOOCs.

In a more recent article for the Montreal Digital Conference to be held next month, Are MOOCs the long-awaited technological revolution in higher education?, Sir John Daniel makes some important points:

• It is unlikely that MOOCs shall be considered a revolution in Higher Education unless they are also able to perform the core functions of that system – “the authority to award degrees, diplomas and qualifications”.
• Quoting Laurillard who questions whether MOOCs are solving global education problems like access to universities, spiraling student debt and low graduate pay, he presents MOOCs as perhaps being more useful in professional and vocational development.
• The viability of building and maintaining MOOCs for universities are also called into question. They do not represent a significant return on investment (like the UKOU’s tracking of students who enrolled revealed that 1500 students had prior contact with its free media implying an 8% return on investment in free media) if considered for student recruitment, nor are they likely to make as much money in services like proctoring and assessments as compared to private operators. He sees certification and employee recruitment as the most promising end-uses of MOOCs.

In talking about the legacy of MOOCs, he writes:

This transformation of the methods of teaching and learning will be the primary legacy of MOOCs. It will not be a revolution but it will have a long-term impact on the way higher education operates, much like the important evolutionary stimuli in the earlier history of universities that we examined earlier.

Talking about OERs, he states:

The creation and use of OER developed steadily, but without fanfare, for the next decade. OER were the long fuse that detonated the MOOCs explosion.

On why MOOCs will not be revolutionary for Higher Education,

MOOCs are not revolutionary, both because higher education develops by evolution and also because MOOCs mostly do not lead to formal qualifications. MOOCs are, however, the harbingers of an important transformation that will lead to much greater use of online technologies in teaching, research and academic service.

Not surprisingly, he concludes:

Quality and the quality assurance of ‘post-traditional’ higher education, like the certification of its outcomes, is one of the greater challenges of these new forms of teaching and learning...Our first conclusion is that we should not await a revolution but rather expect digital innovations to transform practice in an incremental manner...Second, the present disruption being caused by digital technologies is a constructive process. We shall see a flurry of evolutionary change as institutions adapt to the new niches that innovations are creating. Third, it is important to let experimentation continue so that the viability of various models for using technology in teaching, learning, assessment and certification can be tested. This is why it was dangerous to present MOOCs as the contemporary revolution in higher education. Fourth and finally, this exciting phase of evolution poses a special challenge for quality assurance, which is caught on the horns of a dilemma.

Daniel is trying to situate MOOCs (specifically xMOOCs) in the Higher Education context, terming them an evolution and not a revolution, experiments that need far more innovation, currently unable to meet global challenges like student debt, unable to perform core functions such as awarding degrees and a logical evolution of the open and distance learning, OER, digital innovations and online learning paradigm. I think Daniel is saying that the incremental innovations in teaching and learning of the xMOOCs will bring about the real revolution over a period of time.

There is also a fleeting aspiration in what he writes:

In the long run heutagogy and cMOOCs may have a greater impact on the evolution of teaching and learning in higher education in an information age than the more common xMOOCs, some of which learners can find trivial rather than confusing.

and from the Musings article:

We quote Illich to emphasise that the xMOOCs attracting media attention today, which are ‘at the intersection of Wall Street and Silicon Valley’ (Caulfield, 2012), appear to have scant relation to those pioneering (Ed: cMOOC) approaches.

As George Siemens writes while distinguishing between x- and c-MOOCs in What is the theory that underpins our MOOCs?:

As stated above, there is overlap between our model at that of Coursera/EDx. However, Coursera/EDx emulates the existing education system, choosing instead to transfer it online rather than transform it online.

Clearly, xMOOCs are an extension geared for the traditional system of education, where at University or online, open and distance. By his own admission, cMOOCs are pioneering approaches that may have a greater impact on teaching and learning in the long run.

The contention lies in whether Daniel thinks that the xMOOCs and cMOOCs are milestones on some kind of a continuum of evolution of higher education, or whether they are, as I firmly believe, two completely different systems altogether. In my opinion, we could better call the xMOOCs something else so that we are able to focus on the potential of cMOOCs in a better way – perhaps call them XBTs or eXtended-Web Based Training, just like the earlier generations were called CBT and WBT.

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Faculty shortage or learner shortage?

People keep on going on about there being so much shortage of good quality faculty. That, they bemoan, is the most important factor behind the problems that we face in K12 or Higher Ed today. It is definitely true to an extent.

I believe the bigger challenge is to find learners. Not students. But learners. Or capable students who take greater responsibility, initiative and interest in their own education as well as the education of their peers.

If we flip the problem, we can perhaps leverage the scale of learners to overcome most of the problems in education. To do this we have to break from the belief that students have to be led. They don’t. They need to be helped to become more capable of learning in an environment mediated by social and technological networks.

This can reshape how we think about teaching and learning. Teachers then need to make sure that students become more capable (instead of becoming more knowledgeable) and that they have help and facilitation when needed. Students have to acquire critical literacies (and heutagogical capabilities) to transform into Learners. The Government needs to reshape the ability of these new generation of capable learners to acquire credentials that can be interpreted (and later perhaps even replace) at par or higher (or differently) than existing credentials. Our institutions and employers need to reshape structures and practices to allow all this wonderful learning led by the ones that are most impacted by it.

This is why, in the FICCI Vision Paper on MOOCs in Higher Education that I co-wrote, my vision for MOOCs (and in general the educational system) was:

Learning through Massive, Open and Online courses (MOOCs) will enable all Indians who want to learn, earn, teach or innovate, the capability to realize their true potential and transform our country.

The vision talks about building capability, not creating trained engineers or research scientists. Replace “MOOCs” with “our Educational System” and the vision would hold, really.

Are we really chasing the wrong problems?

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On Teacher’s Day

There is a teacher in everyone of us. It is useful to acknowledge that a whole lot of things are learnt without someone actually teaching us, and that perhaps someone is right now learning from us without our even knowing it. On the Internet, this is possible at a very large scale. We learn from other people’s review of the computers we buy or the places we visit. We learn to dress by looking at what others wear and talk as we hear others speak. We learn from reading a blog post or the fact that a guru likes a particular URL or that an expert just followed an innovative startup’s twitter handle.

So when practicing teachers and real experts, who really do all of this teaching and coaching professionally, start making their actions, their learning, their idiosyncrasies public, a whole lot of people will end up learning even if they are not in their class. Perhaps their class will also learn much more if they share the guru’s network, the guru’s learning trails across the World Wide Web.

As teachers, it is really about how we learn and how we share how and what we learn. It is not learning how to use technology (which is an important enabler, but not an end in itself), but how to embrace a culture of open-ness, sharing and a much heightened consciousness that we are professional performers of a learning process; that as teachers we are actually enacting the role of expert learners.

For that, we have to re-envision the way we learn. We are a product of much the same system that we subject our children to. We bind our students by its same constraints. We are steeped in the routines that we have perfected in years we have taught the same curriculum again, again and again. We cannot change ourselves by thinking in the same ways the system has taught us. We must re-envision our own futures, standing outside the systems of today.

Why it is so phenomenally important to re-learn how to learn in today’s networked environments? Its possible because, invariant to scale, the network has opened up hitherto unknown opportunities to teach and learn. Not that you can now learn something that was previously hidden from you, but that you can now learn and teach in ways that may be much more than the classroom we are so used to. In fact the classroom analogy does not even exist in the networked environment (the closest it gets is “clusters” or “swarms”) – the network is not a class.

Since networks are not classes, you cannot apply traditional teaching-learning techniques to it (or atleast not as-is). So an entire paradigm becomes near-obsolete when one thinks of networked learning. Which is not what the xMOOCs would have you to believe, but that is entirely their loss.

If you can think network, you can break away from the traditional mode. It is what we must do. Case in point. If there is no class, who are you teaching? Answer: You are teaching a cluster of nodes (students) bound to you in some manner (through your institution perhaps), but they are really part of many different networks as well. By connecting to those students and promoting transactions between them, helping them add new connections to their network, and leveraging their existing networks, you will build upon a fabric of learning, much like a weaver or an Atelier. You will help them break away from the monotone of traditional systems, help them celebrate chaos and let them build their capability to learn.

When you become that networked teacher, you will contribute to a scale of learning that will be unbelievable. What you will do within your own small networks, may become amplified or contribute to global knowledge about learning and teaching. Just the sheer scale of your teaching and learning, your networks, the types of interactions, will fast transcend the power of any certificate or degree the traditional system may have to offer.

The revolution is here. It is you. Seize the day.

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The hard problems in eLearning

There are some key challenges that we are facing in eLearning today. And I am beginning to think that these are pretty much invariant to scale. I am beginning to think that perhaps many of them happen at smaller scale in traditional face-to-face education. Here is an indicative list.

• High dropout or low completion rates
• Low engagement and retention (motivation)
• Lack of data driven analytics cramps scalability
• Low use of collaboration/networked learning tools & communities
• Lurking as a legitimate activity
• In courses that need them, lack of physical F2F & LAB support
• Increased demand on the student’s capability for self-directed learning
• Need sophisticated auto-grading (or scalable high quality peer review) systems for large scale assessments
• Video lecture fatigue
• Lack of interoperability with traditional institutions (incl. curricular)
• Availability of Localized materials
• Access to power, infrastructure and connectivity
• Credibility / value perception of learning for employers or for credit transfers by traditional institutions

Some of these are definitely challenges that would constrain any system. But perhaps the real challenges lie elsewhere. For example, I am getting convinced that more than anything else, the capability & motivation of the learner to learn, is the most limiting factor.

We see a lot of power laws in the real world of learning – where a few students participate heavily and the largest number contribute to the long tail. Ideally, an efficient and high quality system would be one where the graphs are uniformly flatter indicating wholesome participation in the process of learning. I would think that not much changes at lower scale or with change of modality to traditional classroom scenarios, and that power laws are in fact observable in these scenarios as well.

The aim of most educational systems is to develop students who are prepared for the life to come, who can contribute to  the world as responsible citizens, who are successful in leveraging knowledge and reason to attain their goals and who learn how to learn. I think the last part is really significant – in fact I would say the most significant part.

In thinking about how people can learn to learn, it is obvious that there be a multiplicity of options on how to learn, rather than just any one way of learning. Our education systems have so far taught just the one way to learn, but there are indeed other ways to learn that may or may not be consonant with the traditional approach.

What are some of these paradigms? I think the Connectivist approach crystallizes what learning really means in a digital age. It is sufficiently “alternative” as a paradigm and needs to be explored. The MOOC is perhaps just one instance of Connectivist environments. Other online environments may exist where massive does not necessarily equate to number of learners, and open doesn’t necessarily equate to “barrier-less” and where we let go of the “course” confines.

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MOOCs are ecologies not episodes

There are two ways one could think of the life-cycle of a MOOC. MOOCs could be thought of as one-time and episodic. They could also be thought of as ecologies, sites or environments for continual learning (for example, a series of MOOCs on the same topics, such as CCK), not use-once-and-throw episodes of learning. I prefer the latter, although some may say the MOOC itself may not be likened to an ecology.

I like the idea of MOOCs as ecologies because communities and networks get created at the site of a MOOC and their value extends beyond the lifetime of a single occurrence of the MOOC. When MOOCs are run as a series of continuously or discretely evolving episodes, they act to extend these communities and networks, each addition bringing fresh insights and diverse experiences into the mix.

This extension is one of the things that really bring the distinction between MOOCs and the traditional courses to the forefront. MOOCs leave a trail of learning experiences, of conversations, that are visible to learners that participate in each succeeding episode. In traditional settings, this knowledge is stored and refined by teachers only who use it to make their teaching more effective over time. However, these are distilled insights, not visible to the learner.

Why I also like thinking of MOOCs as ecologies is that they are shaped by the behavior of agents within them. The agents (instructors, students, administrators, marketing agencies) actively engage with each other. If they collectively succeed in building engagement and value, the ecology thrives. If they are not, we see more skewed participation rates, and the ecology disintegrates quickly.

MOOCs as ecologies also imply that students can remain connected to every episode. So they learn incrementally with every episode they participate in. This has not been addressed clearly and explicitly by MOOCs as yet. In many ways, students who have participated in one or more episodes learn how to stay abreast of the developments in the field of study through their ever-expanding network presence.

Within the MOOC ecology, focus shifts from the content and instructor to the degrees of interconnectedness and interaction in the networks that constitute the MOOC. Conversations become the key to successful learning. Modeling learner interactions and measuring efficiencies at learner, network and MOOC levels becomes very important to gauge the state of the ecology. Each MOOC series contributes, in a dynamic manner, to the understanding of these group dynamics and efficiencies.

For MOOC designers, this should become an important component of your design. Thinking of MOOCs as ecologies allows you to focus on the learning experience and how you can garner insights into how participants want to engage, over successive episodes of learning.

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The Outcomes of our Educational Systems

Does a particular type of education system tend to produce the same outcome irrespective of the underlying environment?

Or is it that the underlying social, economic and political environment will cause pretty much any educational system to tend to produce the same outcomes?

Or is it that the outcomes emerge as a result of the interplay between the educational system and the components of the ecosystem it lives in?

The reason I am asking is because everywhere I look (at least in democratic societies), the problems of education are pretty much the same, although the scale does vary. I hear people across school, university, professional and vocational education mulling over the same problems with as much inertia or angst, in India or in the UK or the USA or Australia or elsewhere. In the case of democratic, market driven countries, there may be a stronger set of patterns as well (as the case may be for authoritarian regimes or other sociopolitical structures).

Common refrains include ones such as teachers are not trained enough, children are not getting 21st century skills developed in them, employers don’t feel happy with the levels of employability of students that graduate, not enough e-Resources are available, there is an issue getting learning to remote and economically weaker sections of society, and policy makers are slow and bureaucratic. And then there are people who proclaim variously that the education system is broken, or that it is obsolete and cannot be “fixed”.

If it is indeed true that educational systems  are invariant to the underlying environment, then there are obvious design faults, that when rectified should cause the systems to improve dramatically. Perhaps the current educational systems may be replaced by new designs instead of being redesigned or “fixed”. The aim then becomes to understand the elements of design of the educational system and overlay them with the current and estimated future contexts, to arrive at new constellations of those design elements.

If the conclusion is the reverse, that educational systems don’t have much to do with outcomes, rather the outcomes are really driven by the underlying ecosystem, then perhaps the answer lies in reforming or redesigning other structures that provide inputs or receive outcomes and outputs from the educational system.

The possibility that outcomes are emergent (i.e. they emerge out of the interplay between the networks of our education system with the rest of the socioeconomic fabric) exists. People will say that the educational system shapes and is shaped by the underlying ecosystem in which it operates. But that does not explain commonality of outcomes observed globally.

I have also started feeling that traditional educational systems are far more chaotic than Connectivists would like to believe. As an example, a degree is given the same level of recognition in most countries, however the conditions of obtaining that degree, whether it is the curriculum, the quality of teachers, the infrastructure or any other design element, vary hugely from University to University. I did this exercise recently when I tried to compare the same named courses across multiple Indian and Foreign universities, and could not find more than a 20-30% similarity in most cases between the syllabus and teaching method of one university versus that of the other.I don’t think two universities would really agree on what (say) a Bachelor’s Degree in Economics should really contain, but they will still award the same degree! The traditional systems seem very chaotic, but are also very highly constrained (duration, method, engagement, assessment…) and designed towards very fixed goals – like closed loop systems – they do not present much opportunity for non-linearity.

So it is really an interesting question to try to answer, at least for those who are looking to engineer the next generation education system(s).

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MOOCs are not books

A startling post by Bernard Fryshman – Books Are MOOCs, Too, leaves me with conflicting thoughts. If he is talking about xMOOCs, I could perhaps agree to a level. If he is talking about cMOOCs, I couldn’t disagree more!

Bernard makes the points that books are mobile, ubiquitous, accessible, excellent supplementary material for your degree preparation, comprehensive and “massive”. He likens the MOOC hype to the hype that surrounded television based education. He believes that “reading a book requires much more active involvement than watching a MOOC online” and that “(T)eachers find it easier to assign a specific homework assignment in a book than a “viewing” in a MOOC”. Among other insights is his insight that books have the advantage of privacy and a serendipity that is “unlikely in a MOOC” and the prediction that “it is hard to envision more than 5 percent of the 20 million postsecondary students in the US drifting over to MOOCs”.

I guess books have a massive audience, are available online, are (sometimes) open to those who can afford them or if they are free, and they (especially textbooks) are built around the course. Perhaps Bernard’s conception of the BOOK is that of being Best Oracles Of Knowledge, that if consumed well, should predictably result in knowledge replication.

Books and their contents, whether offline or online, whether backed by collaboration or not, whether available openly or not, are simply one element of any learning experience – they are the compiled thoughts of the authors’ state of knowledge that others can benefit from. Textbooks lend themselves to supporting degree preparation since they are specifically written for that context.

However, to liken them to MOOCs on the basis of these, dilutes the essence of what the online learning world has been talking about for the past few decades.

The xMOOCs can argue that MOOCs can extend the textbook experience by bringing in online collaboration, crowd performance reporting, connect with the instructor and engaging multimedia content apart from other online affordances. But they can only do just that – since their current format is merely an extension of early approaches to open courseware with the addition of these online social elements.

The concept of online (free or paid) multimedia instruction from the experts is hardly new or revolutionary, but the hype machines have been active for the xMOOCs. It is a little depressing that they picked up the MOOC moniker, the result of painstaking work by George, Stephen and Dave, put brand and dollars behind it, and got lucky. It seems that we now have nonsensical variants like SPOCs (Small Private Online Courses). Tony Bates makes a huge indictment of the the xMOOCs when he states:

In my view, MIT will struggle to make an impact on educational research if it continues to ignore the potential contribution of educators. It is as if researchers such as Piaget, Bruner, Vigotsky, Carl Rogers, Gagné, and many later researchers had never existed. Can you imagine anyone trying to develop a new form of transportation while deliberately ignoring  Newtonian mechanics? Yet this is what MIT is doing in its educational research.

cMOOCs are incomparable to textbooks, or to xMOOCs, or for that matter to courses in a traditional context. They are a different paradigm altogether that stands outside the conventional lens – I would go so far as to state that the xMOOCs are literally inside the box of traditional education, while cMOOCs stand outside the box – that cannot be viewed by the lens of what we traditionally define as the formal learning or university experience.

So when it comes to textbooks and the cMOOCs, Bernard’s analysis falls flat. Textbooks and cMOOCs are simply not comparable.

In the cMOOCs, any one resource is not as important as the connection making process itself – the sense-making and way-finding is the core of the learning experience. Navigating the “conversation”, “context” and the “network” in a cMOOC and deriving learning therein, are perhaps the most important parts in a cMOOC.

Learning to define and set your own plateaus of competencies, learning to be instead of learning to do or know, learning to navigate the over abundant flow of digital information, learning to grow your network and make it richer all the time – these are the critical literacies of the cMOOC world.

Textbooks may or may not be part of the design of a cMOOC – that is largely irrelevant. What is important is designing a cMOOC environment so that it is suitably complex and adaptive.

The cMOOC starts not from the definition of a syllabus and design of the videos, but from making available the teacher’s network – the continuously changing and adaptive nature of her learning. Within that, she decides to give focus to a sub-network that she wants to engage learners on, with the expectation that her learners will usefully (to them) conjoin their network to hers, resulting in far richer learning for both.

The cMOOC starts from a technology base that is geared to expose that network of people, resources and concepts, for extension through reflection and practice. Exposition is non-existent, the best practice is to model and demonstrate your learning processes to your students.

The cMOOC starts from an understanding that diversity and autonomy in the network is very important. In that sense, and this is especially tough for critics of the format, it is not controlled or predictable. However, I foresee that soon we will have ways to understand how such complex ecosystems can be designed for maximal learning effectiveness.

Which is another point for cMOOCs – they are nascent and evolutionary as of now. They are directional and aspirational, and not transactional in the traditional sense. Does that make them less useful or applicable? Not really, but you need to know the difference in approach to be able to use them successfully, as George, Stephen and Dave have repeatedly demonstrated, whether with CCK or Critical Literacies or EdFutures.

Let us face it. We cannot bemoan the fact that the education system is broken, while continuing to find ways to reform it. We must look at alternatives and not disparage those alternatives because either we do not understand them or we lack the patience and conviction to fix the issues in education.

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Offline Connectivism

In 2008, when discussing the critical role of technology in the existence of a Connectivist learning environment, Stephen commented:

Take the steam engine, for example. It works through a process of burning coal to heat water, which turns to steam, which it then fed through a turbine or engine in order to produce power.

You need quite a but of technological infrastructure to build the engines, and you need coal to burn. Without the technology and the coal, you don’t get the benefits of the steam engine.

Does this mean that the principles behind the steam engine are not generalizable? Of course not. The *principles* apply to everybody, whether or not they have a steam engine.

It’s the same thing with connectivism. The principles apply, even to people who do not have the technology to easily observe them in action.

Again, at EDGEX in 2012 (at about 28 minutes into the discussion), George Siemens asserted that without technology, a lot of the abundance of knowledge, which is one of the fundamental reasons for Connectivism (and that itself requires more technology to interpret and access), would not be exposed to a large number of people. Stephen Downes made the point that networks (that have existed even without technology) are the underpinnings of a Connectivist environment and that technology facilitates the making of connections (for example, the Six Degrees experiment).

This is important for India, and for others at our level of development. The technology required to make globally diverse connections simply does not exist for a large number of people. A large number of people simply are not overloaded by the abundance of information, most do not even know that there is more to knowledge than the community or place they live in.

At low levels of development, perhaps the small local network is all that exists, constrained by things such as customs/traditions, economic & social power and access to educational opportunities. This is also where the bulk of the population is in countries such as India and large parts of Africa. The conditions for access to technology (computing, internet) are yet to be established in these areas and where they are available, reliability and sufficiency is often a constraint (what do you do if the school does not even have power).

What then, are the ways in which Connectivist learning environments could be designed for this audience without an initial reliance on computing and Internet technology (perhaps including even power)? The most pronounced impact would be speed and immediacy.

Let us look at the factors influencing network formation.

Local Infrastructure & Economic Development levels: Safe assumptions about available local infrastructure could be that there is a way to communicate through telephone (more or less) and postal networks, that power is unreliable and that the Internet availability is meagre. This is especially important for remote areas. East and North-east have the lowest tele-density and just 1% of rural households have a computer with an Internet connection (8% of urban households) [Census 2011 report here]. The report also states that “(o)ne-sixth of the country, or 200 million Indians, don’t possess any of the most basic assets like a transistor or TV, phone, vehicle of any kind or a computer.”

Society, Religion & Culture: Networks are influenced by culture. Somewhere there must be an understanding of local culture and its influence on learning networks. Traditions apply barriers to networks (social constraints) that impacts the ability of the network to grow and diversify. Community bonding, existence of sub-communities and influence centers (including religious) are all important factors.

Language: Language homogenizes and localizes. This has a direct influence (especially in India which is a single country with many languages) on how networks are able to grow.

Population Density: This is an important one. Census Data shows a remarkable skew across states (an average of 382 people per square kilometre, half of Indian states below that with Arunachal Pradesh at as low as 17 and Delhi/NCR as high as 11,297!). This is critical because high density areas throw up many more opportunities (sparks) for networks (fire) creation and growth.

Interlinkages with other communities: For ideas to spread outside the local community, we must look at the transaction points of this community with the external communities. This could be commercial trade, medical & other services or unifying through administrative departments.

Out of these (and many possible others that influence network formation and growth), Connectivist learning environments would focus on ones that they can influence in some way. For example, in an offline scenario, can postcards carrying a question to an expert outside local boundaries be an admissible innovation? We also need to look at mechanisms underlying complex systems to see which interventionist approaches will work better. More on this in subsequent posts.

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Confused MOOCThink

I came across an article by the progenitors of #EDCMOOC on their initial thinking around MOOC pedagogy (MOOC pedagogy: the challenges of developing for Coursera). Riding on the Coursera engagement with the University of Edinburgh, the team designing the eLearning and Digital Cultures MOOC on the Coursera platform (that I missed enrolling for, though) was seeking to engage with the medium and pedagogy, planning and development and the wider implications for the practice of and research in eLearning and Higher Education.

The article makes a promising start by articulating the “digital mimicry” of the xMOOC platforms by calling out the fact that their models are digital extensions of the conservative education system. The authors also demonstrate their understanding that the MOOC innovation as one that questions and loosens the traditional notions such as institutional control, learning outcomes and assessment criteria.

They do acknowledge the precedents set by the cMOOCs, but dismiss them as being “populated by committed e-learning enthusiasts and remain untested as vehicles for delivering alternative, less ‘reflexive’ subject matter”, “pedagogically interesting, may not fit so well across other disciplines…radical fringes of what the Higher Education sector might be prepared to more fully endorse”.

Their focus is to preserve the “construction of the teacher that has an immediacy that can succeed at scale”, with the belief that the teacher’s role is somewhere in between “over-celebratory fetishizing of the teacher” and “(writing) the teacher out of the equation altogether”. They don’t subscribe to the hype that MOOCs (and the Open Education movement) will achieve grand visions of democratizing education or freeing of the world’s knowledge, but do believe that the MOOCs have some merit in terms of scale, diversity, experimentation & research, and augmentation to physical offerings of higher education institutions.

There intent is to see how the MOOC can operate in conjunction with traditional practices. Essentially, they base their interest on:

Online education is a trend-ridden field, and MOOCs might be seen as just another – rather high-profile – piece of ed-tech du jour. However, in their sheer scale, in the rapidity of their rise and in the profound issues they appear to be raising regarding the purposes of higher education and the future of the university, they are clearly something genuinely new, something more than simply modish. For this reason, they are surely worth serious engagement on the part of anyone interested in the digital futures of educational change.

IMHO, this is a very cavalier approach to think about MOOC pedagogy and I am sure the authors will want to defend their approach based on the learning they have had from actually putting this into practice.

Why do I say this? At the outset, you cannot think of cMOOCs and Connectivism from within the system – they are a disruption – xMOOCs being the (rather limited) innovation. cMOOCs questioned the existing paradigm, demonstrated an alternative (raised many questions that are still unsolved like, for example, assessments in a cMOOC environment) and laid a strong foundation for thinking about the disruption through the theory of Connectivism.

It is not enough to state they cannot fulfill grand visions of democratizing education or cannot work in less-reflexive settings. There must be an effort to quantify the “why” behind these assertions. There must be an awareness that networks that are democratic do not exhibit power laws, rather they are horizontal line graphs that require certain critical literacies (not only those found in “elearning enthusiasts” – dislike being called that).

There must also be a concerted effort to understand that the alternative to instructor-mediated “contact and dialogue” at small scale, towards preserving the quality of these interactions at a much larger scale, must have necessarily to leverage the power of the network (witness Alec Couros’s experiment to call for external mentors online for his physical class) and does not exist in the spectrum between “no-teacher” and “over-fetished teacher”, but rather in different conceptions of what a teacher can be (Atelier, Weaver and so many others that were discussed in CCK08).

It is also important not to bypass the role of technology in unearthing the progress, direction and quality of learning and acting as tools for the network itself to evolve and progress. Therefore, discussions around Learning Analytics, Complexity, Network evolution & collaboration, design of emergent environments for learning and new ways of implicit and explicit assessments must foreground any new design of a MOOC or any conversation around MOOC Pedagogy (if that is the right term – heutagogy was considered as more appropriate in some conversations).

What would count is if the authors directed their design efforts towards exploring the new paradigm from a new paradigm perspective, rather than force-fitting it to existing notions of what they think works and what does not. Their kind of MOOCThink confuses and perplexes me.

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MOOCology

The discussion on what is a MOOC or how do we classify MOOCs is gaining momentum. First we had George explaining the difference by saying that there are xMOOCs and cMOOCs. Now Lisa Lane has come with a different taxonomy (network/task/content based) with some interesting distinctions. Dominic came up his own understanding of the “features” of a MOOC. See also Gordon Lockhart’s Super-MOOC, A MOOC by Another Name and a brilliant post by Doug Holton, where he makes many insightful remarks including what could be necessary and sufficient conditions for learning to occur or to be “caused” (don’t particularly like that last word).

Taking Doug’s cue, we should perhaps be talking of massive in the sense of the quantum of connected-ness or connection-richness, or in terms of the widespread nature of the learning need or motivation, rather than looking at it from the point of view of number of learner enrolments.

That said, I would reiterate that we are comparing apples with oranges, and despite the “mania”, there is no reason why we should be forced to compare these different initiatives in the first place. MOOCs (cMOOCs) will have a plethora of possible implementation strategies and techniques. For example, I love what the folks at the Mechanical MOOC are doing (Audrey covered them here).

In my opinion, it makes more sense to focus on the platform rather than the tool, the rubric rather than the assessment and the DNA rather than the you or me.

A video, by Prof. John Holland (University of Michigan) speaking on Modelling Complex Adaptive Systems, is a must view (rather long, but worth it) for a large number of reasons. I find this CAS video (and generally the complex systems area) appealing because it makes more sense to me than engineered closed systems like we have in education today.

I am intrigued by the emphasis in the talk of building blocks, signals, interactions and boundaries within an overall approach of risk taking innovation. I think that fundamentally describes the platform I am referring to. Let us look at that process.

When a learner first starts out, certain pre-conditions exist. These pre-conditions are what makes a person a learner – whether it be out of curiosity, awareness, context, a need and/or some other kind of motivation trigger. At this point, the learner understands little of the network of knowledge, and perhaps may also have a sense or purpose or general idea of outcomes from the forthcoming experience. The platform will have to recognize this initial state.

Next comes a series of interactions in and with the network. This is where the accessibility, quality and depth of the network (in terms of coverage, accuracy, engagement, open-ness) and the contained boundaries play a big role in facilitating or obstructing discovery, experimentation and conjecture – viz. sense-making.

The network really is two things – one, an explicitly curated or visible set of people, content and tools, and two, a vast hidden implicit network intimately connected with the first but not explicitly visible at first.

Interaction in the network will be governed by signals – actions by the learner, actions by others and changes in the network itself as it evolves and adapts. The learner will interact to implicitly or explicitly “produce” or “engineer” make visible or personal, a set of connected nodes in the network (which shall be her curation arising out of her discovery, experimentation and conjecture).

The visible and invisble impact of her sense-making and of others will generate fresh signals in a non-linear manner. Over time, some of the network constellations will get broken to form new bonds (or connections) as the process will be usually far from equilibrium. Visible parts will become a part of the network thus changing the network maps of sense-making of others and in turn generating new innovations and experimentation.

Again over time, feedback from these interactions or signals will reinforce collections or patterns of these nodes of sense-making and new building blocks of comprehension and sense making will emerge. This is turn will affect boundaries of interaction and reduce impedance caused by them, so that new constellations are created.

The platform will have to recognize this elaborate dance of sense-making, the signals, interactions, boundaries and complex adaptation. It will have to provide for this complexity and it will need to allow for contextual influence to align towards certain constellations (and it will do so in many ways, giving us the agency). 

The platform will have to recognize and help resolve multiple trails that coalesce into a conception, parallelisms or multiple patterns of building blocks that converge into a model (a thought, an idea). And the system will have to recognize transition or inflection points, when existing models are questioned and new trains of thoughts emerge, just like in this post.

The platform has to provide for this emergence, chaos, self-organization and adaptation. Something that is spectacularly different from what Khan Academy or Coursera or other non-MOOCs are attempting to do. And in doing so, it will forge a new understanding of what an educational system ought to be.

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MOOC Dropouts

Audrey is grumpy and unhappy about the massive dropout rate vs. the hype of the open courses. She writes:

I’m starting to get more than a little grumpy about MOOCs, what with all the hype about the revolutionary disruptions and game-changing tsunamis. I’m tired of the mainstream media punditry and their predictions that Stanford University’s experiments with online education (and by extension now Coursera and Udacity) will change everything; I’m tired of Silicon Valley’s exuberance that this could mark the end-of-the-(academic)-world-as-we-know-it – a future that its press, its investors, and its entrepreneurs are all invested (sometimes literally) in being both high tech and highly lucrative.

And she goes on to say:

While aspiring to learn is, indeed, worth celebrating, I can’t imagine anyone seriously argue that aspiring to learn is sufficient. Yet The Atlantic suggests the low success rates are “a sign of the system’s efficiency.”
 
And perhaps as these MOOCs are all just experiments – hyped experiments, but experiments nonetheless – we can shrug and say it’s great folks want to learn and, alas, it’s a pity when they don’t. Perhaps. But when we praise the failure to complete a class (a failure to learn) as “efficiency” and simply stop there, then I’m not sure what we’re building with MOOCs even rises to the level of what Dean Dad calls a “useful extra.” I’m not sure we can even know that it’s useful at all.

This is symptomatic of the adaptation the MOOC idea has gone through. Where many people are amazed (including George who says “I can’t recall a time when universities at one moment have responded en masse as aggressively and as collaboratively” ) at the response in  the past few months, and others like Audrey mix scepticism with an open-ness to engage with the medium, I want to take a step back and talk about some of the major learning from the MOOCs starting 2008.

For me, and many others in CCK, the question of comparisons between existing systems and the MOOC model did not really exist – it was like comparing apples to oranges. There isn’t anything like the existing system (no vocabulary) that exists in a MOOC (except for the name, which has “course” in it).

We were witnessing the emergence of a new way of thinking about teaching and learning. New catchphrases – “Learning is the process of making connections”, “Knowledge is the network”, “to teach is to model and demonstrate, to learn is to practice and reflect” – emerged out of these original MOOCs.

The MOOCs taught me to appreciate emergence, complexity, self-organization and chaos in my learning, both at an individual level and at a group level. Perhaps the most difficult for me to “learn” was the absence of determinism in learning, except that negotiated during the process.

Learning then became something more than the sum of its parts. I have not seen a connectivist implementation of a learning experience that can stand against the traditional LMS and social collaboration add-ons (although George has been working on such an initiative) based learning experience, which focus on the parts rather than the whole. And there exists no pedagogical or andragogical recipe for a MOOC the way Coursera and others may want to advertise.

The vocabulary elements that indicate accomplishment and learning have not been been conceptualized for MOOCs. That is an important thing to remember (and Stephen could have something with his chess game analogy). Neither, more than conceptually, have we talked of the notion of competency. We are at a state of the art in Connectivism today that, in my opinion, defies implementation to any significant degree, for if we had, Audrey would be less grumpy.

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My life is a MOOC

I have been meaning to catch up with the interesting discussion happening around MOOCs. I believe that there will be and should be plurality of approaches and intentions – they are the inevitable accompaniment to change itself. The top tensions in the conversation are:

• How do MOOCs compare with other initiatives like the Stanford AI? Should they be compared at all? How is the MOOC experience different from the others in both design and execution?
• Should MOOCs be seen as disruptive and liberating futures of education, or as incremental improvements to existing educational systems? Should they be posted at all as alternatives to degree or continuing education programs?
• What skills do learners require to navigate these new learning environments? Does it require that they be motivated, socially enabled and have certain Critical Literacies? Should we worry about motivation or presume it? Is learning an art that can be acquired through reflection and practice or is it a science that can/should be rigorously taught?
• Is there intentionality in the design/conception of a MOOC? Should we be moving away from the assumption that MOOCs exist to teach something (as opposed to arguing whether learners can chase their own goals)? If so, how is it different from the way things are today on the Internet and with social media?
• Are theories other than Connectivism able to explain these phenomena accurately? Can/should existing theories be reframed effectively for these types of experiences? Is the Connectivist mode, just as for other theories, like the principles behind the steam engine – evidenced anywhere, anytime?
• What are the benefits that can be derived from such open systems? Are these benefits comparable to the perceived benefits from traditional closed, semi-open systems?

George indicates that this is a process of experimentation, rather than a prescription yet. But not necessarily one that should or does preclude entrepreneurs from adopting it or universities using and promoting their brand to differentiate themselves with. Stephen indicates that we would be better off thinking afresh, rather than treating them as another way of doing the same thing. Dave indicates how the Cynefin framework and the Rhizomatic learning approach can be interpreted in the context of what a MOOC can help one achieve.

The goals of education are variously defined to include a humane & progressive society, inclusive & equitable development, growth & innovation and a host of other goals that arise from awakened and aware individuals. The goals of training are to ensure repeatability in performance and the ability to handle emergent situations.

Theory and Practice are clearly differentiated by challenges of scale, diversity, infrastructure and operations. While Theory may predicate how things should be, Practice dictates what things are – and there are substantial gaps between the two that cannot be resolved by changes in Theory or Practice alone. This is true, not just in Education.

Thus while theories may suggest that Connectivism or Cognitive Apprenticeship or any other theory be the best way for someone to learn, the practice may leave much to be desired. In fact, trying to systematize any theory/philosophy at scale has always been a challenge. This is the core problem that faces us today, so much so, that we have questioned repeatedly the industrial nature of the education system. Of course, there will always be much to be said and debated about one theory over the other.

Which is why it makes sense to experiment with another paradigm which is closer to the way things are and much more in tune with what our goals from Education and Training are. Such a paradigm embraces complexity, questions the existing design and intentionality, while at the same time attempts to meet the same overarching goals. It is necessarily incomparable and requires a new acceptance from people willing to experiment, to craft it into Practice.

The new paradigm is at once more scalable, more respectful of diversity & personal needs, more inclusive & progressive, and most importantly, addresses just those issues that are really crippling the existing paradigm.

In Practice, there is still a long way to go to see how that acceptance can occur in an emergent manner. There are questions around the temporality of learning for specific needs, the need to assess (internal or external) learning for performative reasons, the assurance of learning in such environments, the use of technology, heutagogical considerations and many other important areas. These cannot be answered by rebuttal, but by cooperation. And it must be done by mechanisms that respect complexity and open-ness.

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The Informal Educators: Steve Jobs and Jagjit Singh

Steve Jobs, S.J. and Jagjit Singh J.S. SJ and JS. Full Circle. Closed Loop. Rest in peace.

While SJ epitomised creativity and innovation in technology, JS did the same with Music. While SJ brought personal computing on its own, JS brought life to the dying art of the ghazal. Two people who were never formal teachers. Nonetheless, what we learnt from them is priceless and will continue to inspire us and future generations to come. And they were connected too. The ghazals that JS sang adorn many an iPhone or iPAD.

Since I am irreversibly Connectivist, I can’t help thinking that they were informal educators, teachers who taught without teaching, motivated with their words and actions, who could not be formal educators because perhaps the world was too big to fit in their class, and from who generations will continue to learn.

And there are many like them. Some resting in peace, some visibly our guides and some hidden somewhere off our networks. The skill we must imbibe is how to connect with them, learn from them, despite them not teaching us in an explicit classroom. The world then becomes our classroom, substituting formal teaching with guided collaboration and self-service. That learning is different from time bound, formally assessed mechanisms in ways that are fundamentally incomparable. It is chaotic, non-deterministic and complex and led by our own desires and skills.

The puzzle is in figuring if this is a new kind of education system. Not system, in the traditional closed loop sense, but a complex, distributed one with many cores – many distributed and disaggregated centres of learning and assessment. The puzzle is in the emergence not the making, because it can’t really be “made”. The puzzle is whether it will result in superior outcomes – better citizens, more informed decision makers, more democratic nations and more competent professionals.

It is a puzzle I love and hate to think and talk about. Hate because it involves letting go of structure, intermediation and control. Love because it is free and open, and perhaps has the best chance of helping our children emerge from the abyss of learning they are in today. It needs more people to experiment, play in local contexts, stay globally connected to an ever-expanding network of practice. It is a movement rather than a policy decision, a personal decision to play ball, rather than an imposed directive, an urge to change rather than a push to reform.

SJ and JS. Full circle. Rest in peace.

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Epistemic Games

Clark Quinn pointed me to the work of David Williamson Shaffer and the work around Epistemic Games, the site provocatively taglined Building the Future of Education. Defined:

Epistemic games are computer games that can help players learn to think like engineers, urban planners, journalists, lawyers, and other innovative professionals, giving them the tools they need for a changing world. In epistemic games, players see what it is like to live in the world of adults. They learn ways of thinking that matter in the digital age, and have a chance to imagine the kind of person they might someday become.

David has an interesting presentation from the Design Education Seminar in Paris, France (June 2011) [slides, video, interview]. The first point he makes is about the Epistemic Frame. The Epistemic Frame comprises of:

• Identity (the who)
• Skills (the how)
• Knowledge (the what)
• Values (the why)

(italics added)

He also illustrates an important aspect of games – games as cultures and as environments for growth of innovation cultures. He also connects two “theories” – learning by knowing and learning by connecting.

It is an interesting level of detail for the commonly used word immersion. There is an epistemological and ontological base that designers can use to inform the design of the games they invent. Against the backdrop of the two theories and the epistemic frame, game design becomes a tool for mapping inter-relationships within the epistemic frame – literally describing a state of competence through conversation, game-play and learning. The epistemic frame poses the Values dimension, to me a critical aspect of immersion. In doing so, it focuses on a culture of thinking and innovation that is overwhelmingly important today.

In Use of a professional practice simulation in a first year Introduction to Engineering course, the authors state:

Importantly, engineering knowledge and skills are not required to complete the two design-build-test cycles in the simulation; instead the emphasis is on managing conflicting client requirements, making trade-offs in selecting a final design and justifying design choices….Prior work has also shown that epistemic games—learning environments where students gameplay to develop the epistemic frame of a profession—increase students’ understanding of and interest in the profession.

They explain the methodology behind the game, called Nephrotex, and include a blend of virtual with physical mentoring – something that they believe is critical to the simulation process. It also is a practitioner experience, giving what students will face in real life. In Collaborating in a Virtual Engineering Internship, the authors state that:

epistemic games are designed based on the epistemic frame hypothesis, a theory of learning that analyzes thinking in terms of connections among frame elements: skills, knowledge, values, and justification or decision-making (otherwise known as epistemology) of a STEM profession.

…Nephrotex is grounded in the epistemic frame hypothesis, which suggests that any professional community has a culture (Rohde & Shaffer, 2004; Shaffer, 2004a, 2005, 2006) and that culture has a grammar: a structure composed of skills (the things that members of the community do), knowledge (the understandings that members of the community share), values (the beliefs that members of the community hold), identity (the way that members of the community see themselves), and epistemology (the warrants that justify actions or claims as legitimate within the community). This collection of skills, knowledge, values, identity, and epistemology forms the epistemic frame of the community. The epistemic frame hypothesis suggests that (a) an epistemic frame binds together the skills, knowledge, values, identity, and epistemology that an individual takes on as a member of a community of practice; (b) such a frame is internalized through the training and induction processes by which an individual becomes a member of the community; and (c) once internalized, the epistemic frame of a community is used when an individual approaches a situation from the point of view (or in the role) of a member of the community (Shaffer, 2004a, 2005).

…Put in more concrete terms, engineers act like engineers, identify themselves as engineers, are interested in engineering, and know about physics, electricity, mechanics, chemistry, and other technical fields. These skills, affiliations, habits, and understandings are made possible by looking at the world in a particular way: by thinking like an engineer. The same is true for biologists but for different ways of thinking—and for mathematicians, computer scientists, science journalists, and so on, each with a different epistemic frame.

In David Hatfield’s dissertation, The right kind of telling: an analysis of feedback and learning in a journalism epistemic game, he states:

Epistemic frame theory (Shaffer, 2006, 2007) argues that expertise, such as the kind involved in complex thinking and problem solving, fundamentally involves diverse and dynamic connections between different forms of knowing (Broudy, 1977) and acting, guided by the norms and principles of a particular community….More than simply a collection of different elements, though, epistemic frame theory focuses on the ways in which specific frame elements are used together during complex thinking and problem solving (Shaffer, 2010).

The Critical Literacies MOOC focussed on just this kind of research a year ago from the point of analysis of thinking. Where it starts getting really interesting is here:

Epistemic frame theory thus argues that expertise can be modeled as a network of connections between specific understandings, techniques, values, identities and epistemologies, all of which are articulated through discourse. Assessing the development of such expertise, however, is a significant challenge.

I would add that fidelity of the simulation environment (level of immersion) becomes a significant challenge because it is itself a dynamic network of object and non-object states. In a lot of situations, as in regular eLearning, the struggle is between fidelity and scale (time to develop, cost, effort, complexity). At low scales, all experiences can have a high level of fidelity designed (witness the physical blend in Nephrotex). This can invert very quickly as we add additional variables and behaviors in the mix.

Be that as it may, this work is very useful because it leads us to the next question – how can these elements and their relationships be modeled to increase fidelity while at the same time lessen the impact of the scale of the challenge. Treating the elements of the epistemic frame as categories or clusters of child elements and then building networked relationships and “knowledge” out of these connections, is one part; modeling the dynamism is the much larger other.

In part (see Connectivist Simulations), I have always likened this to the challenge of sense-making and wayfinding in learning and knowledge (networks)  in Connectivism.

But what really got me excited is the possibility that all these ideas could probably merge if we started looking at simulations on a wider scale – connective simulations that could provide a way to abstract from the richness and complexity of our learning  process in a meaningful manner – allowing us to not only gain better insight about learning, but also to be able to guide our efforts to architect/enable observation based assessments.

The challenge, in my opinion, is also to prove that the new forms of assessment are scalable and accurate. That is, a large number of people can reliably be observed (or can demonstrate) “being” or “doing” in a manner that is reliable, accurate and consistent. The accuracy problem is important because simulations can only do so much in abstracting from a complex real-world.

If we had that method, and it was proved superior to traditional methods, then we would have buy-in. After all, the problem confronting us at this moment really is that we still end up trying to observe and assess people’s performance afresh whenever they start on a job, despite qualifications and proof from reliable assessments.

I just came across a load of search links to Connectionist Simulations, which is where all this is ultimately headed and should, at some point, capture my undivided attention. But this is wonderful work and I will follow it closely.

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Learning Histories

What happens to learning histories? Traditionally, in the school or college system, we treat textbooks and references built by experts as the starting point of our education. Students are encouraged to discover through the texts and teacher led activities. However, from one group of students to the other, from one year to the other, it is an ab-initio start. The only continuity is possibly provided by the teacher, who takes to her class the knowledge of any prior learning histories.

The traditional system has a short memory. Histories of student conversations, their trials and tribulations as they navigated unfamiliar terrain, are transmogrified into common mistakes pointed out by the teacher, FAQs built by experts and so on – themselves shortcuts to navigate the longer path taken by the experts to arrive at their conception of the domain. In the process, experts make some reasoned choices about what to leave out. It is important to learn and apply the Pythagorous theorem in a secular manner – never relating to Pythagorous himself or the cultural, social and political context in which he invented the theorem.

These choices are made for the learner. And in this manner, she is condemned to not “know” many learning histories. And therefore, not be able to construct many new forms of learning or adapt histories into new futures. This is typical of a system where temporality is key – competence is generated (or not) out of a structured time-space of an institution.

However, this is simply not the way competence is employed and grown at work or in life. Knowledge management is key to successful enterprises and initiatives, where processes become as important as competence. A hallmark of this competence is that it is based on non-linearity of paths taken to perform based on extensive networks of resources available for self-use.

The core issue is that our systems need several proofs of competence as entry criteria to a variety of different spaces. And they need these proofs to be socially acknowledged, presumably because they shift the burden of proving them to experts. As it happens, the provers and the system are often at odds with each other because they believe in different notions of competence and how to engender it.

Scale entrenches these vulnerable and shifting contracts deeper. With scale (numbers, diversity, globalization, technology), it becomes even more difficult to remember or place learning histories within the context of engendering competence. Someone I know told me about how one of his unofficial mentors spent forty years of his life sifting through Ramanujan’s discoveries, trying to decipher how exactly Ramanujan made his phenomenal discoveries – an anachronistic, obscure but inspiring endeavor in these times.

Learning histories are important. They are important for us to spark innovation, to facilitate the next Ramanujan in his discoveries, to place our learning in local and global contexts within which we exist today. And possibly the way we need to retain these learning histories to record the conversations, curate them, enable connections to them, and celebrate the paths that learners before us took to both fail and succeed. And hope that these inform and help develop new ways of addressing our problems today and for the future.

 

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MOOC, DIY-U and Edupunk

I was reading with interest Stephen Downes’ critique of Anya Kamenetz’s approach in her book DIY-U. I am reading Anya’s book, but could not help writing this post, even though that exercise is incomplete, so I beg your indulgence.

The point Stephen is making is definitely not just academic. The term DIY (do-it-yourself) affords primacy to the individual and is application based. Over time sites like eHow and companies like Home Depot, realizing different needs (cost saving, interests, job compulsions), put together a set of material (books, online guides, community trouble-shooting and advice etc.) to put structure to “learning” specific things with the objective of being able to apply them in a specific context.

This took the form of learning packages, not unlike our monogamous WBTs (web based training) formats. Now these are being extended by the affordances of the networked digital economy like open access, social search, social networking and location awareness. This is very akin to the way our LMSs have evolved. They started with learning packages (which evolved into standards based packaging like SCORM), and then as the network surfaced, they added the “social” to it and called them the next version / next generation social collaborative learning management systems. That is also why these vendors cannot seem to position the Edupunk version as the alternative and have ended up creating a “me-too” add-on feature set for “informal learning”.

There is a deeper malaise, one that Stephen also points to. We are thinking inside the box (very un-Edupunk), when we do try to map an existing system with a new alternative way of doing things keeping the existing system as the base reference. Edupunks (I am hoping) will not look at taking the affordances of an educational system and propose an alterative that will map to its “benefits” or affordances. Rather, they will stand outside the box and raise questions about whether the box really is what we need (why not look at the sphere next to it or why look at all at a closed bounded object). This is similar to combating the oft-heard argument or stance – “technology cannot replace the classroom”. Stephen is right to remark – “It’s establishment thinking combined with a good dose of offloading costs.”

A direct consequence of thinking like that is the “objectification” of learning and the learning process. The approach is to “objectify” or treat learning as a structured process with pre-identified participants, an approach which tries to build a marketplace and commodifies learning. Teachstreet, for example, has the tag line – “Learn Something New” – exhorting us to “find great classes and courses”. Similar to how Anya talks about “content and skills”.

The MOOC Edupunks have demonstrated the way to think outside the box – of becoming rather than doing or getting, of being able to measure your performance. And in doing so, they have exposed core principles of how learning happens (at least their perspective). There is great learning happening as well, as the MOOCs & accompanying deliberations evolve. No one claims to have the final recipe (maybe because none is needed or even possible), which is also why DIY is perhaps a bit presumptuous. But the focus on thinking outside the box rather than inside it is the biggest contribution being made to start with.

What is required is greater investigation into “design” of connected environments, into techniques/patterns that underlie the conversation itself, into technologies and designs that support these connections – in a way that does not translate into “design” of learning, like in the traditional system.

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Learning Styles and Learning

When I was building up the story for LearnOS, in my mind I had a mathematical model for how a complex of factors, assessed through various instruments (psychometric, inventories, observable analytics), could result in heuristics not only for content presentation, but also for collaboration, tools usage and learning process design. A Learning Weights Matrix mapped elements of the learning experience to learner, learning, media and organization indicators to arrive at an indication of design or experience. I tried this with research aimed at evaluating two courses offered by the British Council in New Delhi and got some interesting results.

However, my thinking has changed past that phase, based on a few key considerations.

This is not a machine. There isn’t a definitive set of factors I could use, there is probably not a definitive way of measuring and categorizing profiles and perhaps not a definitive way of mapping enumerated elements of the learning experience to profile information. I am not saying it may not be accurate, or adaptively so, useful, but that it is misdirected. It depends on thinking of students and teachers as finitely defined entities on a production line, programmable and predictable in the face of input.

We are trying to extrapolate from small instances to large scale systems using technology. That is not correct. eLearning as such does not scale well. The quality breaks with scale of any sort. Scale must leverage scale – have a large number of small learning clusters/networks rather than a small number of very large paradigms.

Research, especially around Connectionism (and more specifically Connectivism) indicates that we would be better off looking at focusing on capabilities/literacies rather than on learning styles, on networked behavior rather than individual unrelated atomic conceptions.  Competency frameworks, career progression, and talent management as a whole, need to be re-evaluated in this context

How this emergent ecology will result in competencies bookmarked to real life skills is not altogether unknown. But it still requires structure and method that practitioners, who are currently trying to fit these new ideas inside dominant frames of reference (inside the box), can leverage. It has the promise to scale, much beyond the confines of current eLearning.

These thoughts pretty much redefine the state of art from when I wrote the initial draft for LearnOS and bear on me to remember that technology cannot play God, as someone in a recent conversation, tried to impress upon me.

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Learning and Chaos

Found an interesting article after talking with an expert in Chaos theory. JoAnn discusses possible impacts of Chaos theory on classroom learning using systems, initial effects, bifurcations and fractals. She also explores existing theory in relation to chaotic systems for learning.

Essentially, the point that needs to be explored is whether learning is linear, deterministic and predictable or is it inherently non-linear, dynamic and unpredictable. Chaotic systems may appear random and dynamically changing, but still exhibit an underlying pattern or order.

With such a myriad of factors at all levels (content, teacher, student, learning environment) that affect the teaching-learning process, it is a little wondrous to assume that learning is determinate. For example, as JoAnn points out, prior knowledge has an acknowledged role in what we learn. From the point of view of Chaos theory, small changes in initial conditions may cause very large changes in individual learning or performance.

George Siemens brings more in through adding theories of complexity, chaos and emergence into understanding learning. George appeals to “deterministic unpredictability” of the learning process as reason enough for us to consider the impact of these three theories in our own think about learning. More links here.

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Centenary Post

For my hundredth post, I would like to focus on a few key questions that attack various aspects of what I have experienced and learnt in the past two years. These questions are extremely important for me to attempt to answer and I hopefully will, atleast in part, as I go on. The questions may seem disjointed, but perhaps have a common set of answers.

The first, and overarching, question is:

Are there (or what could be) education systems that have (or would) worked outside the box (in contrast to what exists today) and have proved their reliability and validity in the context of today’s and future needs?

This is important to me because I need to understand if we can really envisage an alternate system of education – one more geared towards achieving a vision of a just, inclusive and humane society – than the one we have now. Not that an educational system is solely responsible for all that is wrong today, but in the sense that the educational system is an important enough component of achieving that vision.

There are many strands of thought that connect to this question, not the least being whether this disruptive change is at all required, but it is a question worthy of building an informed belief around. I would further acknowledge that perhaps this change could happen in a way that replaces a portion of the existing system.

The second question relates to the qualifications of a teacher in higher education in India. 

Do undergraduate and post-graduate teachers need a qualifying degree/diploma in educational theory, instructional design/methods and learning technology with a model of internship before they start teaching?

As I have noted before, this question puzzles me no end. I can’t understand why this is not a pre-requisite already (rather than a possible refresher down the line). School teachers require certification, but others do not? It is a different matter that existing certifications in India may perhaps need to be effectively revamped to meet today’s and future requirements.

But I think the answer to this question may have huge implications for achieving the overall vision of any educational system. In particular, it may help bring disruptive change that partially replaces the dominant paradigm.

The third question relates to the role of assessments in an increasingly collaborative world.

How does one assess learning based on principles of collaboration, free thinking and reflection?

What happens when we remove the boundaries of formal curricula, competency models and organizational metrics? This is an important gap, I believe, in connectivist thinking. I am particularly interested in this because the traditional model has an answer that can be tied directly to economic models, social aspirations, development and growth paradigms.

To build an alternative, intelligible and acceptable bridge to other parts/components of our world, we will need to answer this question. Lots of these other systems depend upon the ability of an educational system to provide these assessments to be efficient and effective.

And finally, the question:

What will it take for the change to happen?

I believe that a change is needed and that it should be disruptive change. The change has to be wrenched out and has to stand tall. What will  the drivers be? I think we need to look outside the educational system in order to assess these drivers. 

Perhaps we need to ask ourselves what the political system needs, what the justice system needs, what the economic system needs, as inputs that will help reshape their own destinies in the quest for a just, inclusive and humane society.

These are all overall questions that impact my thinking at this point. As is the fact with questions, I am sure many would share them with me. If anyone has what they think could be answers, I would greatly appreciate your stopping by!

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3 Idiots: Educational Pedagogy or Fantasy

In case you didn’t know, 3 Idiots is now a record-breaking Hindi movie, that explores and exposes the educational system. As of the time of this post, it has been released worldwide and is the highest grosser in Indian cinema history (about US$68mn in 19 days and also made 43 million pounds worldwide to date).

The movie is based in a “traditional” academic setting in an engineering college, reputed for its excellence and for its no-holds-barred-excellence-is-the-most-important thing principal. The story revolves around 3 students who get to live together in the college hostel and become lasting friends. The story tries to bring to the front the problems created by a severe focus on grades and book knowledge and essentially laments the restriction of freedom of thought and reflection that has become a hallmark of the educational system. The term “idiot” is used to refer to not someone stupid but to an irrepressible free thinker who follows his heart.

It has caught the imagination of an entire nation of learners. And that fact bears important testimony to the popular perception that the academic system discourages free thinking, diversity of opinion, creativity and innovation because of it’s over emphasis on grades, bookish knowledge, competitive spirit and teacher-centricity.

The main “idiot”, played by Aamir Khan, is, in my opinion, the only idiot in the film. Born to the assistant of a rich man, he proxies all the way through engineering college for the rich man’s son. As a result, he gets to go where his interests take him, to whichever subject and teacher that excite his imagination. He is naturally inclined to be curious, his questioning ways earning him the ire of his teachers and the ridicule of his peers. But he is brilliant and ultimately emerges as a scientist with a large number of important patents to his name.

Aamir believes in free thinking, of questioning the dominant paradigm. Ultimately he converts the principal of the engineering college, who is fanatically entrenched in the “traditional” mindset, to seeing things in a different light. The movie ends with shots of Aamir in a “school” in Ladakh doing what he believes – teaching kids to let their imagination, innovation and creativity take over.

But there is a bit of demagoguery here, with no clear indication that the ideas are as revolutionary as they seem. For example, a point of discussion should be what is exactly being proposed. The movie is not clear on what or how this pedagogy and system really to be made possible. If it is argued that ultimately it is a movie and not a research project, I would argue that it is not a trifling matter given the reach and success of the movie and its ability to shape popular perception.

The applicability of these ideas and their sudden, almost inexplicable shift from a higher education setting to a school, is a little puzzling too. There is no evidence of Aamir’s school principal having the same endgame delirium as was the case with Boman Irani, who played the engineering college principal. The dynamics are very different between the two scenarios. 

Also, there is little evidence that creativity, innovation and imagination does not at all exist in the traditional system -sometimes teacher-heroes led and sometimes with an organizational focus. It then begs the question – are we talking of a change from inside the box or are we talking about something revolutionary that is at odds with tradition. I don’t see that debate happening around me. Most of the debate seems to be around how the movie has borrowed more from Chetan Bhagat’s Five Point Someone than anything else.

Conflicting verdict at the end for me, though. It leaves me wanting for more because it was hugely entertaining. And a trifle irritable because perhaps the matter should not be trifled with.

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Networked Learning Environments

So are LMSs now part of a technology trend that is headed south? Will incorporation of Web 2.0 features make them more enticing? Will learning really become more effective if Web 2.0 happens to these LMSs? Will they start working on a networked learning SCORM advanced API soon, maybe by defining standard runtime Web 2.0 interactions with services such as Facebook and Twitter? Do we bid adieu to learning objects?

These are uncomfortable questions that must be asked. Scholar360 attempts to be one effort to move away from LMSs as we traditionally know them by keeping the social network at the core.

Let us try and visualize what would really happen if the network really was the core and learning, the process of making connections.

Firstly, the definition of what constitutes content would change. It would become highly personal. This is because it would be pieced together from every learner’s perspective from the content already available to her.

Secondly, content would generally come from connections, which is to say that each learner would share her raw or synthesised perspective with her network and those who have access to that network will learn through evaluating the content and perhaps engaging in discussion. Perhaps rather than a learning object with pre-filled content, it would become a network map of ideas and concepts peppered with individual insights. So a “course” written by an “expert” would become a “network of ideas” weaved together by a “weaver”.

Not only would it be personal, but it would also be dynamic with very little control by the “weaver” in determining the boundary or tone of the ideas, once it is “out there”.

So a new learner who “enrols in the course” (read, “decides to learn”) would, around the broad parameters of the learning experience, start building certain types of awareness.

The first awareness would be of the mass of ideas. The second would be of the people. The third would be of the technology that enables her to navigate between people and ideas. The fourth would be a growing awareness of the learning process itself.

This awareness would continue to grow through the “course”. The process of learning as mandated by the “weaver” would be a responsible contract between the learner and the “weaver”, as would be unwritten rules of conduct in collaboration and communication in the network. Certain technological  peculiarities may also need to be learnt or adapted to.

Imagine walking down a road all times of a day and night over many different seasons. Imagine watching a kaliedoscope of people, houses, shops, all change over time. Imagine recognizing something new in the landscape that has changed since you were last there. That is how the network of ideas that the learner creates will change in response to the evolution of the learning experience that is being woven as the “course” progresses.

The weaver’s job will be to acclimatise the learner to the changing landscape, provide an understanding of the environment through initial idea networks and through an empowerment in terms of tools, technologies, processes and social conduct perhaps. It will be the learner’s job to practice and reflect.

The job of technology then transcends the social network provision or the provision of Web 2.0 tools such as blogs and wikis. Technology should now be harnessed “network” each dimension of the learning experience, to help the network really become the core.

For the weaver, technology should provide a way to negotiate the changing nature of interaction/collaboration, of the explosive network of ideas that she set the seed for, of the mechanisms for maximum impact of these ideas on learners. Not only that, it must allow for her the ability to derive a measure of her effort.

For her, the “weaver”, the experience will repeat multiple times. But each time, her network is enriched by the thought processes of her learners – past and present, so that it is never the same experience.

Technology’s greatest challenge will be this immersion into the network, both visually and conceptually. It will not be simple. Atleast not as simple as pushing Web 2.0 collaboration over a social network or inserting a social network (and tools) into a course.

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Network based Training (NBTs)

I have written earlier about what I am proposing as the evolution from the CBT and WBT – the NBT or Network based training, for some time now. NBTs provide a framework for organizations who want to adopt Web 2.0 and networked learning (the connectivism way) in their systems. The main components of the NBT would be both learning process and tool based.

The NBT consists of the following components:

• a learning process that emphasizes learner participation prior to the course in setting up goals and sequences
• definition of agreed upon sequence of focus areas and learning events based on a temporal sequence
• agreed upon rules/structures of participation with weakly or strongly defined compliance
• defined initial roles for participant and educator (and others) that is consonant with a networked learning strategy
• initially defined ecology of 2.0 tools (blog, wiki, discussion forum, live conference events, other collaboration techniques etc) to be enmeshed in the course
• choosing appropriate collaboration techniques e.g. Delphi, shared maps,
• if required, avenues for structured peer review (could have multiple levels) and group work; if so required an expert review
• resource repository that captures suggested content for review and discussion; could include documents or web collaboration resources
• collaboration using techniques specifically suited for the context of the course; e.g. grouped concept maps if a goal is to create a resource base
• policy for sharing; e.g. if sharing with a wider audience is agreed upon, some way of sharing blog posts, discussions with personal blogs or social network could be explored
• statistics for the facilitator role to judge quantitatively and tools for analysis based on qualitative criteria
• setting up of a default network for the participants of the course (as more people join, a historian role is defined that brings them up to speed using a special mechanism for navigating the content, maybe through learner contributed summaries or commentaries)
• post assessment of learning experiences to evolve the learning ecology
• some way of integrating and reporting on the experience in both directions – organizational and personal learning environments
• norming of the participants on how to use; overcoming barriers to use

These would define an ecology within which much learning could happen. One possible view is that each NBT could become a “slice” of learning that could be linked to the PLE. Several such slices could be linked and could potentially inter-mesh to allow cross-disciplinary or cross-network linkages to promote diversity.

Obviously, from a technology point of view, one could go in two directions. One, allow loosely coupled 2.0 service integration. Two, create generic tools to store localized data and build bridges so that this information can be ported to available 2.0 services. The first allows for easy extensibility when a new 2.0 service or app comes along. The second encourages careful selection of appropriate learning tools (not just mash up anything with anything irrespective of the impact on learning – if something is indeed effective, one would rather build it in to the system in a generic fashion, giving far more control).

From a learning process orientation, specifically a connectivist orientation, it will be necessary to position the NBT somewhere along the range between individuals and groups, connectives and collectives, in an attempt to engender the greatest possibilities for leveraging the power of networked learning, collaboration and innovation. The prime challenges and constraints will lie in shaping policy, between open-ness and protection of IP for instance.

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Connectivism and social action

In the wake of the Mumbai terror attacks, I have witnessed in graphic detail the many aspects of socio-political crisis. On one hand, there is the actual terror and consequent military action. On the other is the political shakeout because of mass opinion that reflected in the local elections and change of power positions in the state.

There is also the role of the media as an agent provocateur, irresponsible in its behaviour and indicative of the explicit power mass media has in shaping opinions. In fact the media took upon itself (through its famous media icons), to show their bias and partisan nature, a shocking revelation of the lack of maturity. For example, when the Muslim groups in India expressed their shock and anger at the terror attacks, one media channel anchor said it was a “welcome change”, not understanding that the channel was not a medium to voice her personal bias.

What did the people do? A famous ex-actress, and there were more of these who were interviewed rather than thought and opinion leaders (of those leaders that were interviewed, it wasn’t a dialogue but more a diatribe anyways), stated that taxpayers in Mumbai should not pay taxes next year in protest! That probably is liable to be branded a seditionary comment. Ironically, these people rail against such comments made by people who are really seditionary and communal in nature!

What this all really exposes for me, is the lack of reflection, the lack of serious thinking on serious issues have large geo-political, social, economic and other impacts. Even more the lack of practice, of social action that an individual can contribute to.

For me this reinforces what I am only being able to appreciate in-context now – that our education system needs ecologies where diverse influences are made available – not awareness courses, but strategies for engendering critical thought and refection and avenues for actuating practice through social action.

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CCK08 Week 2

End of week two of the “course” and I think I have come some way. While Week 1 was about Connectivism and the changing face of the web at an introductory level exposing me to some interesting ideas and getting me acclimatised to a massively online course, Week 2 has been the process of getting my hands dirty on some of the basic ideas. You can read my meanderings at the links below on http://learnoscck08.wordpress.com, a blog I specially created for this course, but which I expect shall go far beyond that.

• Patterns
• Rhizomatic Education
• A Global Theory?
• What is Theory?
• Chat Interaction Frequency
• Learning Formations for this course
• What is learning theory?
• Web 2.0 JISC Report CMap

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