Driscoll (2000) defines learning as “a persisting change in human performance or performance potential…[which] must come about as a result of the learner’s experience and interaction with the world” (p.11). This definition encompasses many of the attributes commonly associated with behaviorism, 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 content or other people.
Driscoll, M. (2000). Psychology of Learning for Instruction. Needham Heights, MA, Allyn & Bacon.
“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 (undated).”
Stephenson, K., (Internal Communication, no. 36) What Knowledge Tears Apart, Networks Make Whole.Retrieved December 10, 2004 from http://www.netform.com/html/icf.pdf.
Our ability to learn what we need for tomorrow is more important than what we know today.
Siemens, Connectivism http://www.elearnspace.org/Articles/connectivism.htm
Reflection is a form of mental processing – like a form of thinking – that we use to fulfill a purpose or to achieve some anticipated outcome. It is applied to relatively complicated or unstructured ideas for which there is not an obvious solution and is largely based on the further processing of knowledge and understanding and possibly emotions that we already possess (based on Moon 1999)
Moon, J. (1999) Reflection in Learning and Professional Development. London: Kogan Page.
What? So what? Now what?
Double-loop learning is an educational concept and process that involves teaching people to think more deeply about their own assumptions and beliefs. It was created by Chris Argyris, a leading organizational trainer, in the mid-1980’s, and developed over the next decade into an effective tool. Double-loop learning is different than single-loop learning which involves changing methods and improving efficiency to obtain established objectives (i.e., “doing things right”). Double-loop learning concerns changing the objectives themselves (i.e., “doing the right things”).
Chris Argyris coined the terms “Double Loop Learning” and “Single Loop Learning. Single loop learning has often been compared to a thermostat in that it makes a “decision” to either turn on or off. Double loop learning is like a thermostat that asks “why” — Is this a good time to switch settings? Are there people in here? Are they in bed? Are they dressed for a colder setting? — thus it orientates itself to the present environment in order to make the wisest decision.