What is Connectivism? Week 1: CCK09
Original: George Siemens, What is connectivism?, September 12, 2009, licence; Forked: James Neill, September 17, 2009
Anyone can edit: Be bold
Note that there are also tweets (#CCK09), blog posts, and a Discussion forum about this topic. Mashups of the feeds include: [1]. |
Connectivism is a learning theory advocated by George Siemens and Stephen Downes, among others, which emphasizes the importance and role of networks and connections between people (and things?) as prominent (central) to the learning process.
"Connectivism is a learning theory that explains how Internet technologies have created new opportunities for people to learn and share information across the World Wide Web and among themselves... A key feature of connectivism is that much learning can happen across peer networks that take place online."[1]
This learning theory claims individual's knowledge is distributed and lives not only in their brain, but also in connections with electronic and human components. That, in turn, allows the learner to develop in their course of learning. It is truly a learning theory for this digital era.
The theory of connectivism has been created to understand how we learn in a networked society and exists due to the exponential growth and complexity of information available on the Internet and the new possibilities to communicate on global networks (Siemens, 2008). The three learning theories most frequently utilized in instructional contexts: behaviorism, constructivism, and cognitivism receive an ambitious approach named connectivism which addresses learning within and across the networks.
Additionally, connectivism refers to connected learning networks, or “nodes”. The greater the network of a node, the greater the connection and therefore, the greater the likelihood of learning. Weaker connected nodes or small world networks, such as finding a new hobby or new job, rely more on chance rather than high-level nodes or networks (Siemens, 2005). A strength of the connectivist approach is its emphasis on learners claiming autonomy over their own learning in development of a personal learning network (Siemens, 2005).
The Principles of Connectivism
• Learning and knowledge rest in the diversity of opinions.
• Learning is a process of connecting specialized nodes or information sources.
• Learning may reside in non-human appliances.
• Capacity to know more is more critical than what is currently known.
• Nurturing and maintaining connections is needed to facilitate continual learning.
• Ability to see connections between fields, ideas, and concepts is a core skill.
• Currency (accurate, up-to-date knowledge) is the intent of all connectivist learning activities.
• Decision-making is itself a learning process. Choosing what to learn and the meaning of incoming information is seen through the lens of a shifting reality. While there is a right answer now, it may be wrong tomorrow due to alterations in the information climate affecting the decision (Siemens, 2004).
• Knowledge is created as learners work to understand the experiences around them (Driscoll, 2000).
• Learning as community development.
Weaker and Stronger Ties
The concept of weaker ties making a network stronger is presented in Network Theory, based on Granovetter’s article on the nature of strong and weak ties, and was further expanded upon by Barabási (2003) and Buchanan (2003) with the observation that many networks are “scale free.” “Power functions mathematically define the fact that in real networks, the majority of points have only a few ties, and these numerous little points coexist with a few large central points that have an unusually large number of ties” (Barabási, 2003, p. 100).
Péter Csermely makes the point that weak ties are what make networks strong. “A tie between two elements of the network is weak if taking away or adding the tie does not influence in a statistically sensitive way the average of the network’s typical characteristics (usually one of the group-defining characteristics of the network). Weak ties stabilize networks” (Csermely, 2005, p. 363).
In 2006 Jones and co-authors also discussed the non-hierarchical nature of networked learning in which many weak ties exist, including the ties between students and their professors, each other, and other sources of knowledge.
Siemens says that, “Knowledge does not only reside in the mind of an individual, knowledge resides in a distributed manner across a network . . . learning is the act of recognizing patterns shaped by complex networks" (Siemens, 2006, p. 10).
Role of the Educator
Siemens discusses the role of the educator in one of four models: Master Artist, Network Administrator, Concierge, and Curator. The idea of the Master Artist (Seely Brown, 2006) sets the instructor as a master painter in an art class, free to observe the students and point out areas of exceptionalism. Here the students learn from each other with inspiration and guidance from the Master. Clarence Fisher (n.d.) postulates that the teacher functions as a Network Administrator, helping the learner create their learning network. The instructor is available to give perspective on the information and assist the student in evaluating their findings to decide which is the best sources for learning. The Concierge model, by Curtis Bonk (2007), sees educators directing their students by offering resources to start their exploration. The Concierge shows the learner avenues they may not have found on their own, sometimes through a traditional lecture format and other times allowing the learner to explore on their own. Siemens adds the last role of the educator as Curator: "A curator is an expert learner. Instead of dispensing knowledge, he (she) creates spaces in which knowledge can be crafted, explored, and connected. While curators understand their field very well, they don't adhere to traditional in-class teacher-centric power structures. A curator balances the freedom of individual learners with the thoughtful interpretation of the subject being explored. While learners are free to explore, they encounter displays, concepts, and artifacts representative of the discipline" (Siemens, 2008).
All four roles work together with the goal of joining educator expertise to learner construction. As educator take on the active and essential role of teaching and evaluating learners, they must be mindful of the “rapid information growth, increased learner control of information creation and dissemination, and the growing reliance on network models to address complex changes in society are trends that continue to impact much of society.” Educators must support students by facilitating learning experiences that are social, engaging, and connected to prior knowledge (Siemens, 2008, p. 17).
In the Overview of Connectivism video, George Siemens (2013) discusses how connectivism emerged through the digital age as opposed to a face-to-face classroom setting. Connectivism is a "social connected process of learning." Siemens asserts that, "in a networked world, learning is a network forming process, knowledge is a networked product" and occurs at three levels: a biological level, forming conceptual connections, and, lastly, through external social spaces.
Within connectivism in open online learning environments is that the learning involves "active engagement of people with resources in communication with others, rather than the transfer of knowledge from educator to learner" (Kop, 2011, p.20). This means that knowledge is shared among everyone and a sense of connectivism is gained. The knowledge isn't just gained with people in the same room, but can be distributed across the internet, with users engaging with it online "constitute learning" (Kop, 2011, p.20).
A helpful way to get started with understanding connectivism is to read over the connectivism glossary.
What follows is some (currently) lightly adapted content originally by Siemens about "what is connectivism?" - an initial class reading - which readers should feel welcomed to edit and improve upon as an introduction to connectivism.
Mergel’s emphasis on Ertmer’s and Newby’s “five definitive questions to distinguish learning theory” (Distinguishing One Learning section, ¶ 1) provides a framework to organize various theories:
The table below indicates how prominent learning theories differ from connectivism:
Property |
Experiential | |||||
Learning theorists |
Thorndike, Pavlov, Watson, Guthrie, Hull, Tolman, Skinner |
Koffka, Kohler, Lewin, Piaget, Ausubel, Bruner, Gagne |
Piaget, Vygotsky |
Maslow, Rogers |
Kolb |
Siemens, Downes |
How learning occurs |
Overt and covert behaviors are the same with respect to how they are acquired and modified - they differ only in terms of who can observe the changes. learning is represented as a persistent change in either an overt or covert behaviour. |
Structured, computational |
Social, meaning created by each learner (personal) |
Reflection on personal experience |
Learning through doing |
Distributed within a network, social, technologically enhanced, recognizing and interpreting patterns |
Influencing factors |
Relationship between the antecedent stimuli and consequence stimuli on the response (behaviour). Main mechanism of behaviour change are the changes in the environment following a behaviour (reinforcement/punishment) |
Existing schema, previous experiences |
Engagement, participation, social, cultural |
Motivation, experiences, relationships |
Engagement , participation |
Diversity of network, strength of ties, context of occurrence |
Role of memory |
Memory is the precurrent behavior that occurs at the time of acquisition in preparation for problem solving that occurs at the time of remembering (Palmer, 1991) |
Encoding, storage, retrieval |
Prior knowledge remixed to current context |
Holds changing concept of self |
Reflection, critical analysis, synthesis |
Adaptive patterns, representative of current state, existing in networks |
How transfer occurs |
stimulus-response-stimulus |
Duplicating knowledge constructs of “knower” |
Socialization |
Facilitation, openness |
Cycle of concrete experiences, reflective observation, abstract conceptualization, active experimentation |
Connecting to (adding) nodes and growing the network (social/conceptual/biological) |
Types of learning best explained |
Task-based learning, Reasoning, problem solving, interpersonal skill development, complex learning |
Reasoning, clear objectives, problem solving |
Social, vague |
Self-directed |
Connecting concrete with abstract, development of new concepts |
Complex learning, rapid changing core, diverse knowledge sources |
Even Siemens (2008) points out that his idea of a new learning theory “based on network structures, complex changing environments, and distributed cognition” has drawn criticism (Learning and Knowing in Networks: Changing roles for Educators and Designers). For example, Pløn Verhagen (2006), in his critique of connectivism, deems it ineffective and “unsubstantiated philosophising” (¶ 14). In Bill Kerr’s challenge to connectivism (2006), he agrees that networks have become important for learning but disagrees that connectivism is necessary because we already have existing theories that satisfactorily address learning in a technologically connected world. Curtis Bonk similarly argues against connectivism as theory and instead suggests it “belongs in a sociological, or anthropological, conception of learning” (Siemens 2008).
Frances Bell ((2011). Connectivism: Its place in theory-informed research and innovation in technology-enabled learning. The International Review of Research in Open and Distributed Learning, 12(3), 98-118. https://doi.org/10.19173/irrodl.v12i3.902) argues that although Connectivism is influential, without the development of a substantial research base it will not be perceived as a standalone learning theory.
Another critique is that other, more suitable, theories exist to answer the questions connectivism attempts to address, such as communities of practice, actor-network theory, and activity theory.
Despite these and other detractors, proponents of connectivism and the concept of networked learning in general, continue to pursue a model of learning that reflects the network-like structure of online interactions that Siemens proposes. Siemens presents as evidence the attendance and discussion at University of Manitoba’s 2007 Online Connectivism Conference, and the level of interest in the course he built with Stephen Downes, Connectivism and Connective Knowledge (CCK08). However, the popularity of a topic or theory should not be the sole basis for declaring something a "new learning theory."
The alternative? Some propose that connectivism be viewed as pedagogy rather than theory, as methodology rather than model, as practice rather than principle. Seen in this way, connectivism as a pedagogical movement has some promising methods worthy of consideration and adoption. Cf. Connectivism as Pedagogy.
What then, do we find to be distinct about connectivism?
Search for Connectivism (learning theory) on Wikipedia. |