Connectivism:
A Learning Theory for the Digital Age
A Learning Theory for the Digital Age
George Siemens
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 how we live,
how we communicate, and how we learn. Learning needs and theories that describe
learning principles and processes, should be reflective of underlying social
environments. Vaill emphasizes that “learning must be a way of being – an
ongoing set of attitudes and actions by individuals and groups that they employ
to try to keep abreast of the surprising, novel, messy, obtrusive, recurring
events…” (1996, p.42).
Limitations of
Behaviorism, Cognitivism, and Constructivism
A central tenet
of most learning theories is that learning occurs inside a person. Even social
constructivist 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 not address learning that
occurs outside of people (i.e. learning that is stored and manipulated by
technology). They also fail to describe how learning happens within
organizations
Some questions
to explore in relation to learning theories and the impact of technology and
new sciences (chaos and networks) on learning:
- How are learning
theories impacted when knowledge is no longer acquired in the linear
manner?
- What adjustments need
to made with learning theories when technology performs many of the
cognitive operations previously performed by learners (information storage
and retrieval).
- How can we continue to
stay current in a rapidly evolving information ecology?
- How do learning
theories address moments where performance is needed in the absence of
complete understanding?
- What is the impact of
networks and complexity theories on learning?
- What is the impact of
chaos as a complex pattern recognition process on learning?
- With increased
recognition of interconnections in differing fields of knowledge, how are
systems and ecology theories perceived in light of learning tasks?
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 core elements – 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 connecting
specialized information sets, and the connections that enable us to learn more
are more important than our 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 and unimportant information is vital. The
ability to recognize when new information alters the landscape based on
decisions made yesterday is also critical.
Principles of connectivism:
- Learning and knowledge
rests in 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.
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