Sweller's Cognitive Load Theory: Overview
From Kevin McGrew's blog, a guest post by Walter Howe, Cognitive Load Theory for School Psychologists:
This theory suggests that learning happens best under conditions that are aligned with human cognitive architecture. The structure of human cognitive architecture, while not known precisely, is discernible through the results of experimental research. Recognizing George Miller's research showing that short term memory is limited in the number of elements it can contain simultaneously, Sweller builds a theory that treats schemas, or combinations of elements, as the cognitive structures that make up an individual's knowledge base. (Sweller, 1988)
The contents of long term memory are "sophisticated structures that permit us to perceive, think, and solve problems," rather than a group of rote learned facts. These structures, known as schemas, are what permit us to treat multiple elements as a single element. They are the cognitive structures that make up the knowledge base (Sweller, 1988). Schemas are acquired over a lifetime of learning, and may have other schemas contained within themselves.
The difference between an expert and a novice is that a novice hasn't acquired the schemas of an expert. Learning requires a change in the schematic structures of long term memory and is demonstrated by performance that progresses from clumsy, error-prone, slow and difficult to smooth and effortless. The change in performance occurs because as the learner becomes increasingly familiar with the material, the cognitive characteristics associated with the material are altered so that it can be handled more efficiently by working memory.
From an instructional perspective, information contained in instructional material must first be processed by working memory. For schema acquisition to occur, instruction should be designed to reduce working memory load. Cognitive load theory is concerned with techniques for reducing working memory load in order to facilitate the changes in long term memory associated with schema acquisition.
- Have you ever done something successfully, but not known exactly how you did it? It’s a common experience. It works, but we generally either cannot repeat this feat readily or transfer this performance to other, similar situations. We have performed a particular task successfully, but we haven’t really learnt a lot.
- In CLT, this one-off success isn’t learning (in other theories it is regarded as learning, and termed implicit learning or procedural knowledge). Learning only occurs when we have abstracted a series of steps and rules that we can repeat in similar situations or even teach others so they, too, can be successful. These rules and procedures are called schemas or schemata and they are stored in long-term memory. Novices, by definition, either don’t have a schema for a particular learning task or it is very unsophisticated. Experts, on the other hand, have many, very sophisticated schemas, which they apply without thinking (i.e. the application of these schemas has become automatic).
- CLT is concerned with how we learn or (in CLT terms), how we develop schemas and automate them and become experts. It applies to learning relatively complex material, as schema acquisition and development are generally unimportant for simple tasks, although how simple a task is depends both on the task itself and the individual who is learning how to do it successfully, as you will see.
CLT has obvious implications for the design of instruction in mathematics, among other things.
Kevin McGrew keeps a number of wonderful resources: IQ's Corner ("An attempt to share contemporary research findings, insights, musings, and discussions regarding theories and applied measures of human intelligence. In other words, a quantoid linear mind trying to make sense of the nonlinear world of human cognitive abilities.") Tick Tock Talk: The IQ brain clock ("An attempt to track the "pulse" of contemporary research and theory regarding the psychology/neuroscience of brain-based mental/interval time keeping. In addition, the relevance of neuroscience research to learning/education will also be covered.")