Learning theories Part 4: Connectivism
- 1 Theory overview
- 2 Specific contributions
- 3 Networked learning
- 4 Summary
- 5 Criticism
- 6 Important contributors
"Connectivism is a theory describing how learning happens in the digital age. Research in traditional learning theories comes from an era when networking technologies were not yet prominent. How does learning change when knowledge growth is overwhelming and technology replaces many basic tasks we have previously performed?" (Siemans, 2006). Connectivism brings learners to the forefront in locating, presenting, and making sense of relevant knowledge (Darrow, 2009). No longer is structured content at the center of learning, but a resource within a vast array of possible resources.
Connectivism is difficult to describe succinctly, as it emerges from the integration of principles of chaos, complexity, networks, and self-organization – all fields of study that have arisen within the past 25 years, examining various aspects of spontaneous order arising out of random initial conditions. Chaos is the science of surprises, of the nonlinear and the unpredictable. It teaches us to expect the unexpected. Complexity theory is the study of complex systems, and network theory is the study of the interactions between complex systems. Finally, self-organization theory states that large-scale coordination can arise out of local interactions between individuals. From these principles, we see that connectivism is the antithesis of centralized command and control structures we see in most teaching organizations. It is the thesis that knowledge is distributed across a network of connections, that networks have cognitive properties, and that learning consists of the ability to construct and traverse those networks (Downes, 2012). If you're interested, Foton Labs provides quick looks at these theories and more.
Connectivists acknowledge explicitly that their theory, as well as the others, is not universal in its application. It focuses on self-directed and informal learning, on learning with technology and networks, and how to survive and thrive in the knowledge age.
In his initial articulation of the theory, Siemans (2004a) outlined its basic principles:
- Learning and knowledge require a diversity of opinions presented to the whole...and to permit selection of a best approach. First, we are not referring to facts, but the nature of knowing. All knowledge is information, but not all information is knowledge. Our current view of knowledge as static, organized, and defined by experts is being replaced by a more dynamic and multi-faceted view. "The filters, gatekeepers, and organizers are awakening to a sea of change that leaves them adrift, clinging to their old methods of creating, controlling, and distributing knowledge" (Siemans, 2006). In other words, we have moved into an age, brought on by technology and the internet, where knowledge production as well as consumption has become the purview of the many, not just the anointed few. We do not consume knowledge as a passive entity that remains unchanged as it moves through our world and our work. We dance and court the knowledge of others — in ways the original creators may not have intended. We make it ours, and in so doing, diminish the prominence of the originator. "Rather, knowledge comes to us through a network of prejudices, opinions, innervations, presuppositions, and exaggerations, in short through the dense, firmly-founded but by no means uniformly transparent medium of experience" (Adorono, 1984).
- From the connectivist perspective, knowledge possesses two broad characteristics: it describes or explains some part of the world (e.g., how diseases spread), and we can use it in some type of action (e.g., preventing disease). The second characteristic, successfully putting information to use, is the foundational criteria of knowledge rather than its source - university professor, experienced practitioner, armchair philosopher or, ideally, a coming together of all three.
- Learning is a network formation process of connecting specialized information sources, referred to as "nodes" within a network. Beyond formal settings, learning is becoming a process of connecting with people and content in a constant, ongoing, daily activity. As we encounter new resources, we may choose to actively connect with them and contribute our own knowledge and experiences. Learners now move into a variety of different, possibly unrelated fields over the course of their lifetime. Formal education no longer comprises the majority of our learning and informal learning is taking on more significance (perhaps it's always been so). Learning now occurs in a variety of ways – through communities of practice, personal networks, and through completion of work-related tasks. Learning is a continual process, lasting for a lifetime. Learning and work related activities are no longer separate. In many situations, they are the same.
- Knowledge may reside in non-human appliances, and learning is enabled and facilitated by technology. Just as knowledge can reside in books and other written forms, so to can it reside in computers, networks of computers, and the infinite combinations they afford. Just as we draw on the knowledge of other humans, we draw on the knowledge of networks. This phenomenon already has a name - the "Google effect" in which we are using the internet as a personal memory bank (Sparrow et al., 2011, see Item 2 below). According to their research, people are more likely to look for information on the Internet, and they're more likely to remember where they found it rather than the information itself. The type of information people seek is generally outside their expertise and may be needed temporarily. Thus knowledge is not the ultimate concern, but rather it is how to locate that knowledge when it is needed. Knowledge lies in the network – the interconnected networks of friends and colleagues, organizations, fields of study, professional societies, Facebook and YouTube, the internet. Networks contained within networks within networks (Figure 4 below).
|2. Dr. Sparrow discusses the Google effect.|
- Up to now, knowledge, even on the internet, has been originated by humans. This is no longer the case. In the military, artificial intelligence agents, using algorithms, now collect raw data, distinguish patterns, and report them to their human commanders. The same is true for weather forecasting and network traffic. Google has created self-driving cars. Some say we are on the cusp of super-intelligent machines. Thus, the source of knowledge is not of primary concern as long as it meets our definition of knowledge.
- The connections that enable us to learn more are more important than our current state of knowing. “Know where” and “know who” are more important today than knowing what and how. "An information rich world requires the ability to first determine what is important, and then how to stay connected and informed as information changes. Content is dependent on the right conduit for expression and communication (the internet, a book, a text message, an email, a short video clip)" (Siemans, 2006).
- Learning and knowing are constant, ongoing processes (not end states or products). "The idea that there is a body of content to be acquired and remembered is explicitly rejected; to learn in a constructivist sense is to grow and develop, to form a network of connections within oneself and with others" (Downes, 2012). It is a never-ending process. As students are discovering, a college degree is only the beginning of a life-long quest to keep up.
- The ability to see connections and recognize patterns and make sense between fields, ideas, and concepts is the core skill for individuals today. Silos of knowledge are no longer appropriate or useful because new discoveries and knowledge are coming from connections between formerly disconnected fields of study, ideas, and concepts. Behavioral neuroscience (the application of biology principles to human behavior) and informatics (a cross between information science and social science) are prime examples of various sciences coming together to create new fields of research and application. The ability to see and articulate these connections has become an essential skill for learners. Contrasted with constructivism where the individual constructs his or her own meaning, connectivism states that meaning exists externally and it is the learners’ challenge to recognize patterns which have remained hidden, making new meaning by forming connections between multiple disciplines. Learning is a process of connecting and integrating specialized knowledge. A learner can exponentially improve his or her own learning by plugging into existing networks. As with constructivism, students must learn how to evaluate information as to its currency, relevance, authority, accuracy, and purpose.
- Currency is the intent of all connectivist learning activities. When we need to accomplish a task, it is not content in general that we want. We want content that is current, relevant, and contextually appropriate. Knowledge is not static; we don't want outdated content, we want the most up-to-date knowledge we can get. We don't want general knowledge when we need specific information. And we want it in a form (e.g., paper, cell phone, desktop) that best fits the need at this particular time. Connections are what allow us to obtain these resources in the current moment.
- Decision-making is learning. When confronted with a decision or problem, we first need to decide how to approach it. Is the approach applicable to the circumstances? We need to identify alternatives. Have we identified them all? We test the alternatives against certain criteria. Have we selected the most salient criteria? We must select the best alternative and implement it. Was our choice really the best one, and can we successfully implement it? What happens if things change? What about intervening variables? The process requires several instances of learning, including observing the results (i.e., feedback). Choosing what to learn and the meaning of incoming information is seen through the lens of a shifting reality. While there may be a right answer now, it may be wrong tomorrow due to new knowledge and circumstances affecting the decision. "The ability to draw distinctions between important and unimportant information is vital. The ability to recognize when new information alters the landscape based on decisions made yesterday is also critical" (Siemens, 2006).
Connectivism is still quite young and its long-term impact has yet to be seen. Yet, important advancements are already impacting education and training at all levels. Stay tuned for further developments.
The learning organization
An important new contribution of connectivism is its ability to describe the learning organization. If an organization is the sum total of its members’ knowledge and skills, it is only through connectedness that the organization can fully take advantage of them. In the information age, knowledge and information flow is an important element of organizational effectiveness, the equivalent of the oil pipeline in an industrial economy. Information, like electricity, flows from node to node. Click here for an account of organizational learning in a software development environment.
George Siemens and Stephen Downes conducted the first Massive Open Online Course in 2008 with approximately 2,300 participants. All course content was available through live presentations and discussions, RSS feeds and online students could participate through collaborative tools, including blog posts, threaded discussions in Moodle and Second Life meetings. This approach has been labeled cMOOC to distinguish it from the more traditional xMOOC offered by EdEx, Coursera, and other providers. See a fuller discussion of MOOCs in Delivery mode.
"By navigating the content environment, and selecting content that is relevant to your own personal preferences and context, you are creating an individual view or perspective. So you are first creating connections between contents with each other and with your own background and experience. And working with content in a connectivist course does not involve learning or remembering the content. Rather, it is to engage in a process of creation and sharing. Each person in the course, speaking from his or her unique perspective, participates in a conversation that brings these perspectives together" (Downes, 2012). Click here for an account of producing the first MOOC (PDF).
Personal learning network/environment (PLN/PLE)
A personal learning network, or personal learning environment, (Figure 4 below) is the environment we create and use to learn in a constructivist manner. The individual is at the center, connected to all sorts of different resources, social networking, communities, blogs, our own files, books, etc. All kinds of different people, services, and sources. Some make a distinction between the network (the people and relationships) and the environment (the tools and infrastructure). The main thing is that individuals are connected to each other through a variety of technologies. The activities of teaching and learning merge into one and the same activity. We're receiving content, manipulating it, creating it, sending content to others, discussing it, and ultimately personalizing it and using it for our own purposes.
Connections between nodes in an individual's personal learning network can vary in strength. Strength depends upon several factors including an individual's motivation, exposure, emotions, and experience. Individuals with specific learning objectives will be more motivated to make new connections based on the objectives. Exposure relates to repetition as a means to strengthen a connection. The more popular a node, the more other nodes link to it. How individuals feel about their connections plays a part in the value placed on the nodes and how differing perspectives are interpreted. An individual's personal experience helps to define the creation of a network.
The creation of networks allows individuals to stay current despite the rapid pace of knowledge development. Again, the ability to learn becomes more important than what is being learned as content is quick to change. The aim of networked learning is to facilitate the development of deep understanding, complex worldviews and the ability to quickly assimilate and adapt to shifts in the knowledge base.
|3. A Personal Learning Network/Environment (click to enlarge) Credit: Jason Hews|
As previously noted, Stephen Downes (2012) defines constructivist learning as the ability to construct and traverse networks of knowledge. To do this, learners need to understand the properties of networks and how to locate and use knowledge within them. If self-directed learning is the name of the game, what role do instructors and courses have to play? Connectivism suggests that the teaching role is actually an aggregate of many different roles - which need to be disaggregated. They also believe courses can be conducted in a connectivist manner, and that learners can be taught to take learning beyond the online classroom and into the world of networks.
Properties of networks
Networks are characterized by attributes of autonomy, reduced resistance to information flow, ease of connectivity, organic growth, rapid iteration and improvement, as well as ease of scalability (Siemens & Weller, 2011).
- Autonomy: Each node within the network governs itself, accomplishing its purpose. Doing so requires cooperation and an exchange of value.
- Diversity: Nodes possess distinct, unique properties - unique combinations of knowledge, experiences, and perspectives. The greater the variety within a network, the stronger it is. Ambiguity and paradox abounds, creating new possibilities.
- Openness: Membership is fluid; the network is in constant flux due to entering and exiting nodes.
- Interactivity: Communication moves between nodes through multiple routes due to the diversity of the nodes.
Networks that possess these properties are able to develop and grow while those that do not will be impaired in some fashion. Network death occurs when all entities are of the same state, and hence all interaction between them stops due to network stasis.
Nodes are individuals, business units, data bases, computers - anything where knowledge resides. To remain current and effective, member nodes must be active in the network – both contributing and seeking out new information. Nodes are always in competition for connections because links represent survival in an interconnected world, and the placing of value on certain nodes over others is a reality in the human world. We see this especially with corporatized social media sites like Facebook, Twitter, Google+, Tumbler, etc.
Selwyn (2012) convincingly places the role of social media in learning within the connectivist framework. “A major educational implication of social media is the apparently changing nature of learners’ relationships with information and knowledge. Indeed, it could be argued that social media support forms of knowledge consumption and knowledge construction that are very different to the epistemological principles of formal education and individualized instruction.” As George Siemens (2004a) puts it, “learning can therefore be conceived in terms of the ‘capacity to know more’ via social media rather than a reliance on the individual accumulation of prior knowledge in terms of what is currently known.”
| Learning from Network Communication: Community Health
In a study recently published in the journal Psychological Science (Eichstaedt et al., 2015), researchers compared tweets and heart disease at the county level. The study found that language analyses may predict heart disease risk as well or better than traditional epidemiological risk factors.
"Language associated with anger, negative emotions, hostility and disengagement within a community was associated with increased rates of heart disease," explains lead author Johannes Eichstaedt, "Language expressing positive emotions and engagement was associated with reduced risk."
This sort of pattern detection is becoming more common as the use of "big data" increases and computer-assisted data analysis grows increasingly sophisticated. In a very real sense, the meaning is in the network and machine and man are working together to recognize it.
- Central hubs (D) maintain the largest number of direct connections within a network and so acquire greater profile and are able to influence knowledge flow. We see this phenomenon in Facebook friends, LinkedIn connections, and other social network mechanisms. By their centrality, hubs are able to foster and maintain knowledge flow. However, "the more connections the better" is not necessarily true. What matters more is what those connections lead to (e.g., relationships, new knowledge) and how they connect the otherwise unconnected. Here D has connections only to others in its immediate cluster -- a clique, connecting with only those who are already connected to each other.
- Close connectors (F and G) have fewer connections than D, yet the pattern of their direct and indirect ties allow them to access all the nodes in the network more quickly than anyone else. They have the shortest paths to all others -- they are close to everyone else. They are in an excellent position to monitor the information flow in the network -- they have the best visibility into what is happening in the network.
- Brokers (H and J) lie between networks. H has fewer connections than the average in the local network, yet in may ways, it has one of the best locations in the network -- between two local networks (J being a member of a different local network). It plays a 'broker' role in the network. The good news is that it plays a powerful role in the network; the bad news is that it is a single point of failure. Without it, I and J would be cut off from information and knowledge in the cluster. A node with high betweenness has great influence over what flows -- and does not -- into and out of the network. H may control the outcomes in its local network.
- Bridges (H, I, and J), or boundary spanners, are more central in the larger network of networks than their immediate neighbors whose connections are only local, within their immediate cluster. Nodes that connect their group to others usually end up with high network metrics. They are well-positioned to be innovators, since they have access to ideas and information flowing in other clusters. They are in a position to combine different ideas and knowledge, found in various places, into new knowledge via pattern recognition. You can be a boundary spanner via your bridging connections to other clusters or via your concurrent membership in overlapping groups.
- Peripheral players (I) lie on the periphery of a network and have very low centrality for any network. Peripherals often are identified as "weak links" between local networks because they often don't identify with either group.
New literacies, new competencies
According to Stewart (2013), the networked world requires a new set of literacies. These new digital literacies contain an ethos component as well as a technological one: Participation, collaboration, distributed knowledge and expertise, mass participation, and rewards for all who pitch in. She compares legitimacy “practices” in terms of current institutional structures and networked structures:
Society as a whole lies somewhere between the two, but the current does seem to flow in the direction of the network. Those who plan to prosper in the future cannot afford to ignore this.
Specific required competencies discussed in the connectivist literature are described below.
Forming connections - Creating give-and-take relationships with other individuals, discussions groups, professional communities, etc.
- "We derive our competence from forming connections‟ (Siemens, 2004a).
- Since we cannot possibly experience everything ourselves as the cognitive load would be too great, other people, (the network), become our source of knowledge. The capacity for connection forming, becoming aware (of others and knowledge), and sustaining exchanges, lies at the heart of knowledge exchange today.
- Our design of methods, organizations, and systems benefit most by allowing greatest opportunity for connectivity.
- The capacity to connect produces the capacity to adapt.
- Experience has long been considered the best teacher of knowledge. Since we cannot experience everything, other people’s experiences, and hence other people, become the surrogate for knowledge. "I store my knowledge in my friends is an axiom for collecting knowledge through collecting people."
Contributing - Sharing our own personal knowledge, experiences, informed opinions, etc. for the benefit of others and the whole community.
- Instead of seeing knowledge from only one perspective (the filter), we, as individuals, can contribute our opinions and views to extend the depth (diversity) of our understanding. Knowledge can now be expressed through the aggregate of the individuals—a deafening crescendo of contrasting and complementing opinions and views.
- Connectedness allows individuals to create and distribute their own materials and identity. Instead of seeing a whole, we see the many pieces that comprise the whole, and as individuals, we can create the whole that suits our needs and interests.
Suspended certainty - Developing our ability to suspend judgement while seeking information, managing our desire for closure when ambiguity reigns, and working through ambiguity toward new understanding.
- We must resist our urge to give shape too early. Ambiguity is an unfailing companion.
- Our quest for certainty (is that not why we seek knowledge?) is challenged today. When we discover something new, someone else will build on and extend it (transvergence), or new research will prove it untrue. Or foundational conditions will change, requiring the discovery to be updated. Continual suspended certainty is today’s reality. States of “not knowing” are healthy.
- We know in part. An attitude of tolerance for ambiguity and uncertainty is required. Certainty is for a season, not a lifetime.
Seeing connections - Creativity and discovery lie in uncovering previously hidden connections between phenomena in the natural and human worlds.
- The cognitivist thinks deeply by reasoning through a long sequence of steps. The non-cognitivist thinks deeply by 'seeing' more intricate and more subtle patterns. It is a matter of recognition rather than inference.
- In the process of seeing, we are interpreting; there are different ways of seeing a situation. Seeing continuums and context. Seeing how things are organized and what that organization means.
- Seeing the different point of view. Seeing relevance. Seeing the whole.
- "To perceive in relation to actual societal trends requires a malleable framework, capable of seeing what exists, instead of deselecting elements not in line with our thinking." Ralph Waldo Emerson
- Emotions influence our ability to see knowledge. They act as gatekeepers to our neural network. Logic cannot begin unless emotions are held in balance.
- We are moving from an age defined by logic to an age defined by creativity. Creativity is the ability to see “new associations between existing ideas or concepts” ... and to bring new realities into being.
- Creativity involves the ability to form, reform, create, breakdown, and rebuild.
Recognizing patterns - Seeing that pattern, that complex pattern of associated behaviors, actions, reactions, inclinations and all the rest that make phenomena what they are. See perceptual learning.
- In chaos theory, meaning exists, but it is the learner's challenge to recognize hidden patterns.
- We think of rules of language – and it’s funny because we think that the rule tells us what to do, but the rule really is just a pattern and has come to be a rule because we’ve observed it over and over and over.
- Cause and effect is like that. And the skill here is in seeing and recognizing these patterns. Recognizing them and then being able to manipulate them.
- Literacy, of any type, is about pattern recognition, about seeing how art is like physics is like literature is like dance is like architecture is like ...
- Literacy is not about knowing where the dots are. Literacy is not about finding dots about which you may not know. Literacy is about connecting the dots and seeing the big picture that emerges.
- Recognizing trends.
Searching for information - Using specific strategies to locate the information and knowledge needed in the moment.
- Using Boolean logic and other techniques while using search engines.
- Asking the right questions of the right resources.
- Technology will be increasingly depended upon to mediate the bulk of our current knowledge seeking behavior.
- We spend much of our time seeking and trying to locate what we need—findability is still a primary knowledge behavior.
- Once knowledge is more tightly integrated in contexts of use, we can shift more attention to the act of application.
Evaluating information - Separating important and unimportant information; discerning its validity.
- We are seeking to replicate not simple representational states, but complex patterns of behaviors, experience and performance.
- If knowledge has been hardened into ideologies, or if new knowledge is seen through ideologies crafted in advance, the outcome of the discussion is essentially set.
- Debate is largely an attempt to project world views.
- How to evaluate information.
"We can provide the learner with new links to the world instead of continuing to funnel all educational programs through the teacher" (Illich, 1970). This prescient statement from forty-five years ago nicely summarizes the essence of constructivist teaching. Here, the instructor is not the source of knowledge, but rather the mentor and guide for active learners. Consider the following takes on this role:
- Master Artist where the learning forum is likened to an art studio (Siemens, 2006).
- Network Administrator helping students to gain the skills they require to construct networks for learning, to evaluate their effectiveness, and work within a fluid structure. As learners encounter new information sources, the educator encourages them to critically evaluate the source's suitability as part of a holistic and diversified learning network (Fisher, n.d.).
- Curator - Expert with advanced knowledge of a domain and guides who fosters and encourages learner exploration. "This type of instructor acknowledges the autonomy of learners, yet understands the frustration of exploring unknown territories without a map. A curator is an expert learner; he or she creates spaces in which knowledge can be created, explored, and connected. A curator balances the freedom of individual learners with the thoughtful interpretation of the subject. Learners are free to explore; they encounter displays, concepts, and artifacts representative of the discipline...(yet) the key concepts of a discipline are transparently reflected through the curatorial actions of the teacher" (in Darrow, 2009).
- Model - "To teach is to model and demonstrate. To learn is to practice and reflect" (Downes, 2012). What cannot be communicated and understood by lecture and learning activities alone can be addressed through modeling by the instructor.
- Amplifyer - Instead of explicitly saying, "you must know this," the instructor includes critical concepts in his or her dialogue with learners, comments on blogs, classroom discussions, and personal reflections. Another way of amplifying is providing a daily newsletter highlighting discussions, concepts, and resources she considers important, including both supportive and critical views. Thoughts and ideas that the instructor amplifies generally have a higher probability of being noticed by participants
- Wayfinder and Socially-Driven Sensemaker - We find our way through active exploration. Instructors can aid wayfinding through consistency of design and functionality across various tools. Ultimately, however, it is up to the learner. As learners grow and prune their personal networks, they also develop effective means to "filter abundance."
In the industrial age, knowledge consists of a set of propositions that are hypothesized and tested against experience. The ability to articulate knowledge and measure phenomenon are key. In the information age, knowledge evolves quickly. The effectiveness of knowledge is not defined by its conformity to established standards, but by its adaptive value for its users. The idea of truth devolves into an account of perspectives and points of view. For connectivist learning and teaching, the idea that there is a body of content to be acquired and remembered is explicitly rejected. To learn in a connectivist course is to grow and develop, to form a network of connections within oneself and with others. Learning is a process of pattern recognition rather than hypothesis and theory formation. Downes (2012) summarizes the connectivist framework as a cycle: Knowledge informs learning; what we learn informs community; and the community in turn creates knowledge. And the reverse: knowledge builds community, while community defines what is learned, and what is learned becomes knowledge.
- Knowledge - What we know is more accurately demonstrated in what we do, and language derives its meaning not from what it represents, but by how we use it. The logical structures we think of as comprising knowledge are just a part of a far more complex series of expressions, behaviors, interactions, manipulations, creations, emotions and more, all of which point to a much deeper structure. The words we use, the facts we describe, the rules we use are simple abstractions of what we really know. In other words, semantic knowledge is the tip of the iceberg.
- Learning - Learning is not simply remembering. By being exposed to the expert's environment and by doing some of what the expert does we can know something like the expert's knowledge. To teach is to model and demonstrate; to learn is to practice and reflect. Both teaching and learning consist of talking about and of doing. Theorizing and practicing. Abstracting and making concrete. What is key is the attitude we take as we understand that to learn is to emulate an entire "organizational state" and not merely to possess a simple set of facts.
- Community - The place in which we have learning experiences, and the environment through which we communicate with each other about those experiences. It is at once the place and the artifact of what we have learned as a group. A community relates to its constituent members in several ways. It is the environment within which a person experiences, practices and learns. It is therefore a mechanism whereby the experiences of one person may be replicated by another, through immersion in the same environment. A factory isn’t simply a mechanism for building hammers; it is a mechanism whereby one member is able to show another how hammers are built (and how forges are used, how labor is organized, etc.). A community is also the medium through which one person communicates with another. It creates a thick network of connections, whether of wire, highway, text or acoustics, through which signals are sent and received.
Web 2.0 technologies that lend themselves to networked learning include wikis, blogs, web conferencing, and podcasting. Wikis offer flexibility and limitless opportunities to create shared learning resources; they can be used to develop collaborative, student-created textbooks, or students can be encouraged or required to contribute to Wikipedia. Blogs present opportunities for students to create intelligent, thoughtful responses to topics and engage in critical discussion with others. Web conferencing tools like WebEx and Skype allow for real-time discussion and interaction through live conference sessions, remote guest speakers, the ability to connect students from other classes for combined lessons, and record and share course content. Student-produced podcasts and videocasts are becoming a popular means of assessing student learning and can replace a traditional typed essay or PowerPoint-enhanced oral presentation. Audio and video files can be published to the Web where they can be viewed and commented upon by the instructor, classmates, and the wider community. In face to face learning situations, instructors should allow students to use search engines in order to supplement class discussion.
If this conception of learning sounds unlike any other, we can note that it has much in common with constructivist learning. Meaning is more important than information. Learning is more than remembering facts. And perhaps most importantly, learning is a largely social undertaking. What connectivism does differently is take learning outside the institution and into the networked world - a new level of human reality that has not existed before. As such, it is less defined; more fuzzy. It looks to knowledge for its contribution to human adaptability rather than possession of a set of facts, theories, etc. As a new theory, it is evolving. We will do well to pay attention.
Assignments - Connectivism is about connections, and so application of the theory comes in asking students to see and create connections.
- Create and locate useful networks of professionals, websites, databases, individuals, and any other source of information that will help them remain current in the particular field of interest.
- Evaluate information as to its currency, relevance, authority, accuracy and purpose.
- Contribute to one’s networks of choice, not just for keeping others current, but also to gain visibility and credibility in order to access even more nodes of information and influence knowledge flow.
- Make connections between pieces of information in order to create new knowledge and meaning.
Specific types of assignments that can help students build these skills, all of which can be assigned to individuals and groups:
- Search engines and search strategies – learning how search engines work and practicing using them to locate information of relevance to the course.
- Resource lists – creating original resource lists, centered on a particular topic, for use and critique by other course students.
- Information evaluation assignments – assigning websites for students to research and evaluate, then report findings back to the class.
- Case studies requiring students to make connections between pieces of information in order to solve a problem.
- Power and influence – learning how personal power and influence is gained and practiced within a game or simulation.
- Investigating professional organizations – researching and evaluating organizations and deciding which ones might be most useful in keeping current with the subject under study.
- Term projects - assignments that require students to locate, evaluate, organize, analyze and present a body of information appropriate to the course level.
To summarize, here are the major elements of connectivism:
- Awareness of and receptivity to new information and information sources.
- Connection-forming by building personal networks; connecting to existing networks.
- Contribution to and involvement in the networks of one’s choice.
- Pattern recognition through increased sensing of nuances, connections, trends, “changing winds”.
- Meaning-making by understanding and describing patterns, then asking how we should adjust, adapt and respond.
- A cyclical process of reflection, experimentation, and action.
Connectivism really is different than the other theories. It does not attempt to describe how learning occurs within the individual, but looks outward and describes how learners – especially those who need to stay current and who wish to influence the future – connect to the networked world of the information age. As such, it is a logical extension of the learning enterprise.
Connectivism involves making connections with others and building upon the work that has come before. In many ways, connectivism is a return to the basics: learning from one another, trust in the creative process, and a strong sense of mentorship between teacher and pupil. With connectivism, active participation is required by all involved in the learning process. As such, the theory serves as an excellent model for life-long learning (Darrow, 2009).
A current weakness in connectivist learning is in sustaining local and smaller shared-interest networks, at least in the U.S. Very few thrive over the long term. Commercial sites have come to dominate the scene because they work to keep their networks active. LinkedIn, for example sends at least one e-mail message every day. Automated "services" include updating you on contact birthdays and work anniversaries, spotlighting celebrity writers, notifying you when someone views your profile, promoting their upgrade version and, of course, notifying you of any and all posts to your interest groups. The semantic web conceived by Tim Berhers-Lee was an attempt to make content more findable through the use of metatags, but the idea never gained a foothold due to multiple factors. Downes (2012) observes that "It is arguable that social networking, by itself, has limited practical use" for learning. This may be due to the fact that the educational establishment and the current zeitgeist are not yet there. Or it may be that the communication form does not work well with human nature. We will see what the future holds.
Our look at connectivism would not be complete without acknowledging the warnings of some important scholars about the potential downside to an emphasis on connectivity – a “new sort of nerd religion based around a core belief that a global brain is not only emerging but will replace humanity.” Jaron Lanier (2011) of Columbia University is typical of this view:
“Decay in the belief of self is driven not by technology, but by the culture of technologists, especially the recent designs of antihuman software like Facebook, which almost everyone is suddenly living their lives through. Such designs suggest that information is a free-standing substance, independent of human experience or perspective. As a result, the role of each human shifts from being a special entity to being a component of an emerging global computer. This shift has palpable consequences. For one, power accrues to the proprietors of the central nodes on the global computer. . . . Those who are not themselves on a central node (may) find their own cognition gradually turning into a commodity.”
This thinking may be just dystopian hyperbole, but when we look around and see everyone with faces buried in their mobile device, we see that something is happening. For more on this phenomenon, see Virtual Distance: Technology is rewriting the rulebook for human interaction.
Constructivism is very young and contributors are as of yet limited. These people are contributing significantly to the development of the theory:
- George Siemens
- Stephen Downes
- Clarence Fisher
- John Seely Brown, Allan Collins, and Paul Duguid (situated cognition)
- Jeffrey Elman (connectionism)
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