Siemens - A Learning Theory for the Digital Age

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Connectivism: A Learning Theory for the Digital Age December 12, 2004 George Siemens Update (April 5, 2005): I've added a website to explore this concept at www.connectivism.ca Introduction Behaviorism, cognitivism, and constructivism are the three broad learning theories most often utilized in the creation of instructional environments. These theories, however, were developed in a time when learning was not impacted through technology. Over the last twenty years, technology has reorganized ho
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  Connectivism: A Learning Theory for the Digital Age  December 12, 2004George Siemens   Update (April 5, 2005): I've added a website to explore thisconcept at www.connectivism.ca  Introduction Behaviorism, cognitivism, and constructivism are the three broad learning theories most often utilizedin the creation of instructional environments. These theories, however, were developed in a time whenlearning was not impacted through technology. Over the last twenty years, technology has reorganizedhow we live, how we communicate, and how we learn. Learning needs and theories that describelearning principles and processes, should be reflective of underlying social environments. Vaillemphasizes that “learning must be a way of being – an ongoing set of attitudes and actions byindividuals and groups that they employ to try to keep abreast o the surprising, novel, messy,obtrusive, recurring events…” (1996, p.42).Learners as little as forty years ago would complete the required schooling and enter a career thatwould often last a lifetime. Information development was slow. The life of knowledge was measured indecades. Today, these foundational principles have been altered. Knowledge is growing exponentially.In many fields the life of knowledge is now measured in months and years. Gonzalez (2004) describesthe challenges of rapidly diminishing knowledge life: “One of the most persuasive factors is the shrinking half-life of knowledge. The “half-lifeof knowledge” is the time span from when knowledge is gained to when it becomesobsolete. Half of what is known today was not known 10 years ago. The amount of knowledge in the world has doubled in the past 10 years and is doubling every 18 monthsaccording to the American Society of Training and Documentation (ASTD). To combat theshrinking half-life of knowledge, organizations have been forced to develop new methodsof deploying instruction.” Some significant trends in learning: ã Many learners will move into a variety of different, possibly unrelated fields over the course of their lifetime. ã Informal learning is a significant aspect of our learning experience. Formal education no longercomprises the majority of our learning. Learning now occurs in a variety of ways – throughcommunities of practice, personal networks, and through completion of work-related tasks. ã Learning is a continual process, lasting for a lifetime. Learning and work related activities are nolonger separate. In many situations, they are the same. ã Technology is altering (rewiring) our brains. The tools we use define and shape our thinking. ã The organization and the individual are both learning organisms. Increased attention toknowledge management highlights the need for a theory that attempts to explain the linkbetween individual and organizational learning. ã Many of the processes previously handled by learning theories (especially in cognitiveinformation processing) can now be off-loaded to, or supported by, technology. ã Know-how and know-what is being supplemented with know-where (the understanding of whereto find knowledge needed).  Background  Driscoll (2000) defines learning as “a persisting change in human performance or performancepotential…[which] must come about as a result of the learner’s experience and interaction with theworld” (p.11). This definition encompasses many of the attributes commonly associated withbehaviorism, cognitivism, and constructivism – namely, learning as a lasting changed state (emotional,mental, physiological (i.e. skills)) brought about as a result of experiences and interactions with contentor other people.Driscoll (2000, p14-17) explores some of the complexities of defining learning. Debate centers on: ã Valid sources of knowledge - Do we gain knowledge through experiences? Is it innate (present atbirth)? Do we acquire it through thinking and reasoning? ã Content of knowledge – Is knowledge actually knowable? Is it directly knowable through humanexperience? ã The final consideration focuses on three epistemological traditions in relation to learning:Objectivism, Pragmatism, and Interpretivism ã Objectivism (similar to behaviorism) states that reality is external and is objective, andknowledge is gained through experiences. ã Pragmatism (similar to cognitivism) states that reality is interpreted, and knowledge isnegotiated through experience and thinking. ã Interpretivism (similar to constructivism) states that reality is internal, and knowledge isconstructed.All of these learning theories hold the notion that knowledge is an objective (or a state) that isattainable (if not already innate) through either reasoning or experiences. Behaviorism, cognitivism,and constructivism (built on the epistemological traditions) attempt to address how it is that a personlearns.Behaviorism states that learning is largely unknowable, that is, we can’t possibly understand what goeson inside a person (the “black box theory”). Gredler (2001) expresses behaviorism as being comprisedof several theories that make three assumptions about learning:1.Observable behaviour is more important than understanding internal activities2.Behaviour should be focused on simple elements: specific stimuli and responses3.Learning is about behaviour changeCognitivism often takes a computer information processing model. Learning is viewed as a process of inputs, managed in short term memory, and coded for long-term recall. Cindy Buell details this process: “In cognitive theories, knowledge is viewed as symbolic mental constructs in the learner's mind, andthe learning process is the means by which these symbolic representations are committed to memory.” Constructivism suggests that learners create knowledge as they attempt to understand theirexperiences (Driscoll, 2000, p. 376). Behaviorism and cognitivism view knowledge as external to thelearner and the learning process as the act of internalizing knowledge. Constructivism assumes thatlearners are not empty vessels to be filled with knowledge. Instead, learners are actively attempting tocreate meaning. Learners often select and pursue their own learning. Constructivist principlesacknowledge that real-life learning is messy and complex. Classrooms which emulate the “fuzziness” of this learning will be more effective in preparing learners for life-long learning. Limitations of Behaviorism, Cognitivism, and Constructivism  A central tenet of most learning theories is that learning occurs inside a person. Even socialconstructivist views, which hold that learning is a socially enacted process, promotes the principality of the individual (and her/his physical presence – i.e. brain-based) in learning. These theories do notaddress learning that occurs outside of people (i.e. learning that is stored and manipulated bytechnology). They also fail to describe how learning happens within organizations  Learning theories are concerned with the actual process of learning, not with the value of what is beinglearned. In a networked world, the very manner of information that we acquire is worth exploring. Theneed to evaluate the worthiness of learning something is a meta-skill that is applied before learningitself begins. When knowledge is subject to paucity, the process of assessing worthiness is assumed tobe intrinsic to learning. When knowledge is abundant, the rapid evaluation of knowledge is important.Additional concerns arise from the rapid increase in information. In today’s environment, action is oftenneeded without personal learning – that is, we need to act by drawing information outside of ourprimary knowledge. The ability to synthesize and recognize connections and patterns is a valuable skill.Many important questions are raised when established learning theories are seen through technology.The natural attempt of theorists is to continue to revise and evolve theories as conditions change. Atsome point, however, the underlying conditions have altered so significantly, that further modification isno longer sensible. An entirely new approach is needed.Some questions to explore in relation to learning theories and the impact of technology and newsciences (chaos and networks) on learning: ã How are learning theories impacted when knowledge is no longer acquired in the linear manner? ã What adjustments need to made with learning theories when technology performs many of thecognitive operations previously performed by learners (information storage and retrieval). ã How can we continue to stay current in a rapidly evolving information ecology? ã How do learning theories address moments where performance is needed in the absence of complete understanding? ã What is the impact of networks and complexity theories on learning? ã What is the impact of chaos as a complex pattern recognition process on learning? ã With increased recognition of interconnections in differing fields of knowledge, how are systemsand ecology theories perceived in light of learning tasks? An Alternative Theory  Including technology and connection making as learning activities begins to move learning theories intoa digital age. We can no longer personally experience and acquire learning that we need to act. Wederive our competence from forming connections. Karen Stephenson states: “Experience has long been considered the best teacher of knowledge. Since we cannotexperience everything, other people’s experiences, and hence other people, become thesurrogate for knowledge. ‘I store my knowledge in my friends’ is an axiom for collectingknowledge through collecting people (undated).” Chaos is a new reality for knowledge workers. ScienceWeek (2004) quotes Nigel Calder's definition thatchaos is “a cryptic form of order”. Chaos is the breakdown of predictability, evidenced in complicatedarrangements that initially defy order. Unlike constructivism, which states that learners attempt tofoster understanding by meaning making tasks, chaos states that the meaning exists – the learner'schallenge is to recognize the patterns which appear to be hidden. Meaning-making and formingconnections between specialized communities are important activities.Chaos, as a science, recognizes the connection of everything to everything. Gleick (1987) states: “Inweather, for example, this translates into what is only half-jokingly known as the Butterfly Effect – thenotion that a butterfly stirring the air today in Peking can transform storm systems next month in NewYork” (p. 8). This analogy highlights a real challenge: “sensitive dependence on initial conditions” profoundly impacts what we learn and how we act based on our learning. Decision making is indicativeof this. If the underlying conditions used to make decisions change, the decision itself is no longer ascorrect as it was at the time it was made. The ability to recognize and adjust to pattern shifts is a keylearning task.Luis Mateus Rocha (1998) defines self-organization as the “spontaneous formation of well organizedstructures, patterns, or behaviors, from random initial conditions.” (p.3). Learning, as a self-organizing  process requires that the system (personal or organizational learning systems) “be informationallyopen, that is, for it to be able to classify its own interaction with an environment, it must be able tochange its structure…” (p.4). Wiley and Edwards acknowledge the importance of self-organization as alearning process: “Jacobs argues that communities self-organize is a manner similar to social insects:instead of thousands of ants crossing each other’s pheromone trails and changing their behavioraccordingly, thousands of humans pass each other on the sidewalk and change their behavioraccordingly.”. Self-organization on a personal level is a micro-process of the larger self-organizingknowledge constructs created within corporate or institutional environments. The capacity to formconnections between sources of information, and thereby create useful information patterns, is requiredto learn in our knowledge economy. Networks, Small Worlds, Weak Ties  A network can simply be defined as connections between entities. Computer networks, power grids, andsocial networks all function on the simple principle that people, groups, systems, nodes, entities can beconnected to create an integrated whole. Alterations within the network have ripple effects on thewhole.Albert-László Barabási states that “nodes always compete for connections because links representsurvival in an interconnected world” (2002, p.106). This competition is largely dulled within a personallearning network, but the placing of value on certain nodes over others is a reality. Nodes thatsuccessfully acquire greater profile will be more successful at acquiring additional connections. In alearning sense, the likelihood that a concept of learning will be linked depends on how well it iscurrently linked. Nodes (can be fields, ideas, communities) that specialize and gain recognition for theirexpertise have greater chances of recognition, thus resulting in cross-pollination of learningcommunities.Weak ties are links or bridges that allow short connections between information. Our small worldnetworks are generally populated with people whose interests and knowledge are similar to ours.Finding a new job, as an example, often occurs through weak ties. This principle has great merit in thenotion of serendipity, innovation, and creativity. Connections between disparate ideas and fields cancreate new innovations. Connectivism  Connectivism is the integration of principles explored by chaos, network, and complexity and self-organization theories. Learning is a process that occurs within nebulous environments of shifting coreelements – not entirely under the control of the individual. Learning (defined as actionable knowledge)can reside outside of ourselves (within an organization or a database), is focused on connectingspecialized information sets, and the connections that enable us to learn more are more important thanour current state of knowing.Connectivism is driven by the understanding that decisions are based on rapidly altering foundations.New information is continually being acquired. The ability to draw distinctions between important andunimportant information is vital. The ability to recognize when new information alters the landscapebased on decisions made yesterday is also critical.Principles of connectivism: ã Learning and knowledge rests in diversity of opinions. ã Learning is a process of connecting specialized nodes or information sources. ã Learning may reside in non-human appliances. ã Capacity to know more is more critical than what is currently known ã Nurturing and maintaining connections is needed to facilitate continual learning. ã Ability to see connections between fields, ideas, and concepts is a core skill. ã Currency (accurate, up-to-date knowledge) is the intent of all connectivist learning activities. ã Decision-making is itself a learning process. Choosing what to learn and the meaning of incominginformation is seen through the lens of a shifting reality. While there is a right answer now, itmay be wrong tomorrow due to alterations in the information climate affecting the decision.
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