In cognitive psychology, cognitive load is the load related to the executive control of working memory (WM). Theories contend that during complex learning activities the amount of information and interactions that must be processed simultaneously can either underload or overload the finite amount of working memory one possesses. All elements must be processed before meaningful learning can continue.
Instruction may be aimed at teaching learners either problem solving skills or thinking and reasoning skills (including perception, memory, language, etc.). Among psychologists it is widely acknowledged that, compared to "cold" learning, people learn more effectively when they can build on what they already understand (known as existing schemas). But the more a person attempts to learn in a shorter amount of time, the more difficult it is to process that information in working memory. Consider the difference between having to study a subject in one's native language versus trying to study a subject in a foreign language. The cognitive load is much higher in the second instance because the brain must work harder to process language while simultaneously trying to integrate new information.
Another aspect of cognitive load theory involves understanding how many discrete units of information can be retained in short-term memory before information loss occurs. An example of this principle that seems to be commonly cited is the use of 7-digit phone numbers, based on the theory that the average person can retain only seven "chunks" of information in short-term memory.
Cognitive load theory
"Cognitive load theory has been designed to provide guidelines intended to assist in the presentation of information in a manner that encourages learner activities that optimize intellectual performance". John Sweller's theory employs aspects of information processing theory to emphasize the inherent limitations of concurrent working memory load on learning during instruction. It makes use of the schema as primary unit of analysis for the design of instructional materials.
The history of cognitive load theory
The history of cognitive load theory can be traced to the beginning of Cognitive Science in the 1950s and the work of G.A. Miller. In his classic paper, Miller was perhaps the first to suggest our working memory capacity has inherent limits. His experimental results suggested that humans are generally able to hold only seven plus or minus two digits of information in short-term memory. And in the early 1970s Simon and Chase were the first to use the term "chunk" to describe how people might organize information in short-term memory. This chunking of memory components has also been described as schema construction.
In the late 1980s John Sweller developed cognitive load theory (CLT) while studying problem solving. Studying learners as they solved problems, he and his associates found that learners often use a problem solving strategy called means-ends analysis. He suggests problem solving by means-ends analysis requires a relatively large amount of cognitive processing capacity, which may not be devoted to schema construction. Sweller suggests that instructional designers should prevent this unnecessary cognitive load by designing instructional materials which do not involve problem solving. Examples of alternative instructional materials include what are known as worked-examples and goal-free problems.
In the 1990s, cognitive load theory was applied in several contexts. The empirical results from these studies led to the demonstration of several learning effects: the completion-problem effect; modality effect; split-attention effect; worked-example effect; and expertise reversal effect.
Cognitive load theory provides a general framework and has broad implications for instructional design, by allowing instructional designers to control the conditions of learning within an environment or, more generally, within most instructional materials. Specifically, it provides empirically-based guidelines that help instructional designers decrease extraneous cognitive load during learning and thus refocus the learner's attention toward germane materials, thereby increasing germane (schema related) cognitive load. This theory differentiates between three types of cognitive load: intrinsic cognitive load, germane cognitive load, and extraneous cognitive load.
Intrinsic cognitive load is the inherent level of difficulty associated with a specific instructional topic. The term was first used in the early 1990s by Chandler and Sweller. According to them, all instruction has an inherent difficulty associated with it (e.g., the calculation of 2 + 2, versus solving a differential equation). This inherent difficulty may not be altered by an instructor. However many schemas may be broken into individual "subschemas" and taught in isolation, to be later brought back together and described as a combined whole.
Extraneous cognitive load is generated by the manner in which information is presented to learners and is under the control of instructional designers. This load can be attributed to the design of the instructional materials. Because there is a single, limited cognitive resource, using resources to process the extraneous load reduces the amount of resources available to process the intrinsic load and germane load (i.e., learning). Thus, especially when intrinsic and/or germane load is high (i.e., when a problem is difficult), materials should be designed so as to reduce the extraneous load.
An example of extraneous cognitive load occurs when there are two possible ways to describe a square to a student. A square is a figure and should be described using a figural medium. Certainly an instructor can describe a square in a verbal medium, but it takes just a second and far less effort to see what the instructor is talking about when a learner is shown a square, rather than having one described verbally. In this instance, the efficiency of the visual medium is preferred. This is because it does not unduly load the learner with unnecessary information. This unnecessary cognitive load is described as extraneous.
Chandler and Sweller introduced the concept of extraneous cognitive load. This article was written to report the results of six experiments that they conducted to investigate this working memory load. Many of these experiments involved materials demonstrating the split attention effect. They found that the format of instructional materials either promoted or limited learning. They proposed that differences in performance were due to higher levels of the cognitive load imposed by the format of instruction. "Extraneous cognitive load" is a term for this unnecessary (artificially induced) cognitive load.
Germane cognitive load is that load devoted to the processing, construction and automation of schemas. It was first described by Sweller, Van Merriënboer and Paas in 1998. While intrinsic cognitive load is generally thought to be immutable (although techniques can be applied to manage complexity by segmenting and sequencing complex material), instructional designers can manipulate extraneous and germane load. It is suggested that they limit extraneous load and promote germane load.
Until the 1998 article by Sweller, Van Merriënboer & Paas, cognitive load theory primarily concentrated on the reduction of extraneous cognitive load. With this article, cognitive load researchers began to seek ways of redesigning instruction to redirect what would be extraneous load, to now be focused toward schema construction (germane load). Thus it is very important for instructional designers to "reduce extraneous cognitive load and redirect learners' attention to cognitive processes that are directly relevant to the construction of schemas".
Paas and Van Merriënboer developed a construct (known as relative condition efficiency) which helps researchers measure perceived mental effort, an index of cognitive load. This construct provides a relatively simple means of comparing instructional conditions. It combines mental effort ratings with performance scores. Group mean z-scores are graphed and may be compared with a one-way Analysis of variance (ANOVA).
Paas and Van Merriënboer used relative condition efficiency to compare three instructional conditions (worked examples, completion problems, and discovery practice). They found learners who studied worked examples were the most efficient, followed by those who used the problem completion strategy. Since this early study many other researchers have used this and other constructs to measure cognitive load as it relates to learning and instruction.
The ergonomic approach seeks a quantitative neurophysiological expression of cognitive load which can be measured using common instruments, for example using the heart rate-blood pressure product (RPP) as a measure of both cognitive and physical occupational workload. They believe that it may be possible to use RPP measures to set limits on workloads and for establishing work allowance. Buettner proposed a method to measure the cognitive workload based on capturing eye movements and pupillary responses via eye-tracking technology.
Some researchers have compared different measures of cognitive load. For example, Deleeuw and Mayer (2008)  compared three commonly used measures of cognitive load and found that they responded differently to extraneous, intrinsic, and germane load.
Individual differences in processing capacity
Evidence has been found that individuals systematically differ in their processing capacity. A series of experiments support the assumption that each individual has a fixed capacity for processing information, irrespective of the task in question, or more accurately, irrespective of the processes an individual uses in solving any given task. Tasks ranged from remembering simple lists, lists supplemented with a fixed constant and simple arithmetic.
Identifying the processing capacity of individuals could be extremely useful in further adapting instruction (or predicting the behavior) of individuals. Accordingly, further research would clearly be desirable. First, it is essential to compute the memory load imposed by detailed analysis of the processes to be used. Second, it is essential to ensure that individual subjects are actually using those processes. The latter requires intensive pre-training.
Effects of heavy cognitive load
The notions of cognitive load and arousal contribute to the "Overload Hypothesis" explanation of social facilitation: in the presence of an audience, subjects tend to perform worse in subjectively complex tasks (whereas they tend to excel in subjectively easy tasks). See also: audience effect and drive theory.
- Workplace stress
- Task-invoked pupillary response
- Task loading (in scuba diving)
- Information overload
- Paas, F., Renkel, A., & Sweller, J. (2004). "Cognitive Load Theory: Instructional Implications of the Interaction between Information Structures and Cognitive Architecture". Instructional Science 32: 1–8. doi:10.1023/B:TRUC.0000021806.17516.d0.
- Sweller, J. (1988). "Cognitive load during problem solving: Effects on learning". Cognitive Science 12 (2): 257–285. doi:10.1016/0364-0213(88)90023-7.
- Sweller, J., Van Merriënboer, J., & Paas, F. (1998). "Cognitive architecture and instructional design". Educational Psychology Review 10 (3): 251–296. doi:10.1023/A:1022193728205.
- Miller, G.A. (1956). "The magic number seven plus or minus two: some limits on our capacity to process information". Psychological Review 63 (2): 81–97. doi:10.1037/h0043158. PMID 13310704.
- Chase, W.G. & Simon, H.A. (1973). "Perception in chess". Cognitive Psychology 4 (1): 55–81. doi:10.1016/0010-0285(73)90004-2.
- Paas, F. (1992). "Training strategies for attaining transfer of problem-solving skill in statistics: A cognitive-load approach". Journal of Educational Psychology 84 (4): 429–434. doi:10.1037/0022-06188.8.131.529.
- Moreno, R., & Mayer, R. (1999). "Cognitive principles of multimedia learning: The role of modality and contiguity". Journal of Educational Psychology 91 (2): 358–368. doi:10.1037/0022-06184.108.40.2068.
- Mousavi, S., Low, R., & Sweller, J. (1995). "Reducing cognitive load by mixing auditory and visual presentation modes". Journal of Educational Psychology 87 (2): 319–334. doi:10.1037/0022-06220.127.116.119.
- Chandler, P., & Sweller, J. (1992). "The split-attention effect as a factor in the design of instruction". British Journal of Educational Psychology 62: 233–246. doi:10.1111/j.2044-8279.1992.tb01017.x.
- Cooper, G., & Sweller, J. (1987). "Effects of schema acquisition and rule automation on mathematical problem-solving transfer". Journal of Educational Psychology 79 (4): 347–362. doi:10.1037/0022-0618.104.22.1687.
- Sweller, J., & Cooper, G.A. (1985). "The use of worked examples as a substitute for problem solving in learning algebra". Cognition and Instruction 2 (1): 59–89. doi:10.1207/s1532690xci0201_3.
- Kalyuga, S., Ayres, P. Chandler, P. and Sweller, J. (2003). "The Expertise Reversal Effect". Educational Psychologist 38 (1): 23–31. doi:10.1207/S15326985EP3801_4.
- Chandler, P. & Sweller, J. (1991). "Cognitive Load Theory and the Format of Instruction". Cognition and Instruction 8 (4): 293–332. doi:10.1207/s1532690xci0804_2.
- Kirschner, P.A., Sweller, J., and Clark, R.E. (2006) Why minimal guidance during instruction does not work: an analysis of the failure of constructivist, discovery, problem-based, experiential, and inquiry-based teaching. Educational Psychologist 41 (2) 75–86
- Ginns, P. (2006). "Integrating information: A meta-analysis of the spatial contiguity and temporal contiguity effects". Learning and Instruction 16 (6): 511–525. doi:10.1016/j.learninstruc.2006.10.001.
- (Sweller et al., 1998, p. 265)
- Paas, F.G.W.C., and Van Merriënboer, J.J.G. (1993). "The efficiency of instructional conditions: An approach to combine mental-effort and performance measures". Human Factors 35 (4): 737–743.
- Paas, F., Tuovinen, J.E., Tabbers, H.K., & Van Gerven, P.W.M. (2003). "Cognitive load measurement as a means to advance cognitive load theory". Educational Psychologist 38 (1): 63–71. doi:10.1207/S15326985EP3801_8.
- Fredericks T.K., Choi S.D., Hart J., Butt S.E., and Mital A. (2005). "An investigation of myocardial aerobic capacity as a measure of both physical and cognitive workloads". International Journal of Industrial Ergonomics 35 (12): 1097–1107. doi:10.1016/j.ergon.2005.06.002.
- Buettner, R. (2013). "Cognitive Workload of Humans Using Artificial Intelligence Systems: Towards Objective Measurement Applying Eye-Tracking Technology". KI 2013: Advances in Artificial Intelligence. LNAI 8077. pp. 37–48. doi:10.1007/978-3-642-40942-4_4.
- DeLeeuw, K.E., & Mayer, R.E. (2008). "A comparison of three measures of cognitive load: Evidence for separable measures of intrinsic, extraneous, and germane load.". Journal of Educational Psychology 100 (1): 223–234. doi:10.1037/0022-0622.214.171.124.
- Scandura, J.M. (1971). "Deterministic theorizing in structural learning: Three levels of empiricism". Journal of Structural Learning 3: 21–53.
- Voorhies, D. & Scandura, J.M. (1977). 7. "Determination of memory load in information processing.". Problem Solving, NY: Academic Press. pp. 299–316.
Journal Special Issues
For those wishing to learn more about cognitive load theory, please consider reading these journals and special issues of those journals:
- Educational Psychologist, vol. 43 (2008) ISSN 0046-1520
- Applied Cognitive Psychology vol. 20(3) (2006)
- Applied Cognitive Psychology vol. 21(6) (2007)
- ETR&D vol. 53 (2005)
- Instructional Science vol. 32(1) (2004)
- Educational Psychologist vol. 38(1) (2003)
- Learning and Instruction vol. 12 (2002)
- Computers in Human Behavior vol. 25 (2) (2009)
For ergonomics standards see:
- ISO 10075-1:1991 Ergonomic Principles Related to Mental Workload – Part 1: General Terms and Definitions
- ISO 10075-2:1996 Ergonomic Principles Related To Mental Workload – Part 2: Design Principles
- ISO 10075-3:2004 Ergonomic Principles Related To Mental Workload – Part 3: Principles And Requirements Concerning Methods For Measuring And Assessing Mental Workload
- ISO 9241 Ergonomics of Human System Interaction
- Barrett, H. C.; Frederick, D.; Haselton, M.; Kurzban, R. (2006). "Can manipulations of cognitive load be used to test evolutionary hypotheses?". Journal of Personality and Social Psychology 91 (3): 513–518. doi:10.1037/0022-35126.96.36.1993. PMID 16938033.
- Cooper, G. (1990). "Cognitive load theory as an aid for instructional design". Australian Journal of Educational Technology 6 (2): 108–113.
- Cooper, Graham (1998). "Research into Cognitive Load Theory and Instructional Design at UNSW".
- Plass, J.L., Moreno, R., & Brünken, R., ed. (2010). Cognitive Load Theory. New York: Cambridge University Press. ISBN 9780521677585.
- UNSW Cognitive Load Theory Conference - Sydney Australia 24-26 March 2007
- Measuring Cognitive Load using Linguistic Features – Implications for Usability Evaluation and Adaptive Interaction Design 21 Nov 2013
- Sweller, J. (1994). "Cognitive Load Theory, learning difficulty, and instructional design". Learning and Instruction 4 (4): 295–312. doi:10.1016/0959-4752(94)90003-5.
- Sweller, J. (1999). Instructional design in technical areas. Camberwell, Australia: Australian Council for Educational Research. ISBN 0-86431-312-8.
- Cognitive Load Theory – a brief introduction to Cognitive load theory
- video of John Sweller explaining Extraneous load