cognitive load theory by J. sweller

Cognitive Load Theory  (Sweller)

John Sweller is the opponent of cognitive theory who  describes the human cognitive archteecture, and the need to apply sound instructional design principles based on our knowledge of the brain and memory. Sweller first describes the different types of memory, and how both are interrelated, because schemas held in long-term memory, acting as a “central executive”, directly affect the manner in which information is synthesized in working memory. Sweller then explains that in the absence of schemas, instructional guidance must provide a substitute for learners to develop either own schemas.

Cognitive load refers to the total amount of mental effort being used in the working memory. Cognitive load theory was developed out of the study of problem solving by John sweller in the late 1980s. Sweller argued that instructional design can be used to reduce cognitive load in learners. Cognitive load theory differentiates cognitive load into three types: intrinsic, extraneous, and germane.

Intrinsic cognitive load is the effort associated with a specific topic. Extraneous cognitive load refers to the way information or tasks are presented to a learner. And, germane cognitive load refers to the work put into creating a permanent store of knowledge, or a schema.

High cognitive load in the elderly has been shown to affect their center of balance. With increased distractions and cell phone use students are more prone to experiencing high cognitive load which can reduce academic success. Children have less general knowledge than adults which increases their cognitive load. Recent theoretical advances include the incorporation of embodied cognition in order to predict the cognitive load resulting from embodied interactions.

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".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.

History

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 units 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.

 types

Intrinsic cognitive load

First described by Chandler and Sweller, intrinsic cognitive load is the idea that all instruction has an inherent difficulty associated with it .  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

Extraneous cognitive load, by contrast, is under the control of instructional designers.  This form of cognitive load is generated by the manner in which information is presented to learners .  To illustrate an example of extraneous cognitive load, assume there are  at least two possible ways to describe a geometric shape like a triangle.  An instructor could describe a triangle in a verbally, but to show a diagram of a triangle is much better because the learner does not have to deal with extraneous, unnecessary information.

Germane cognitive load

Germane load is a third kind of cognitive load which is encouraged to be promoted.  Germane load is the load dedicated to the processing, construction and automation of schemas. While intrinsic load is generally thought to be immutable, instructional designers can manipulate extraneous and germane load. It is suggested that they limit extraneous load and promote germane load.

Measurement

Pass 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).

Pass 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 neurophysiologic 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.

Task-invoked pupillary response is a form of measurement that directly reflects the cognitive load on working memory. Greater pupil dilation is found to be associated with high cognitive load. Pupil constriction occurs when there is low cognitive load. Task-invoked pupillary response shows a direct correlation with working memory, making it an effective measurement of cognitive load explicitly unrelated to learning.

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 in different ways to extraneous, intrinsic, and germane load.

Individual differences in processing capacity

Evidence has been found that individuals systematically differ in their processing capacity. For example, there are individual differences in processing capacities between novices and experts. Experts have more knowledge or experience with regard to a specific task which reduces the cognitive load associated with the task. Novices do not have this experience or knowledge and thus have heavier cognitive load.

It has been theorized that an impoverished environment can contribute to cognitive load. Regardless of the task at hand, or the processes used in solving the task, people who experience poverty also experience higher cognitive load. A number of factors contribute to the cognitive load in people with lower socioeconomic status that are not present in middle and upper-class people.

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

A heavy cognitive load typically creates error or some kind of interference in the task at hand. A heavy cognitive load can also increase stereotyping. Stereotyping is an extension of the Fundamental Attribution Error which also increases in frequency with heavier 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.

Elderly

The danger of heavy cognitive load is seen in the elderly population. Aging can cause declines in the efficiency of working memory which can contribute to higher cognitive load. The relationship between heavy cognitive load and control of center of mass are heavily correlated in the elderly population. As cognitive load increases, the sway in center of mass in elderly individuals increases. Another study examined the relationship between body sway and cognitive function and their relationship during multitasking and found disturbances in balance led to a decrease in performance on the cognitive task. Heavy cognitive load can disturb balance in elderly people. Conversely, an increasing demand for balance can increase cognitive load.

Students

With the widespread acceptance of laptops in the classroom an increasing cognitive load while in school is a major concern. With the use of Facebook and other social forms of communication, adding multiple tasks is hurting students performance in the classroom. When many cognitive resources are available, the probability of switching from one task to another is high and does not lead to optimal switching behavior. Both students who were heavy Facebook users and students who sat nearby those who were heavy Facebook users performed poorly and resulted in lower GPA.

Children

The components of working memory as proposed by British psychologists, Alan Baddeley and Graham Hitch, are in place at 6 years of age. However, there is a clear difference between adult and child knowledge. These differences are due to developmental increases in processing efficiency. Children lack general knowledge, and this is what creates increased cognitive load in children. Children in impoverished families often experience even higher cognitive load in learning environments than those in middle-class families.These children do not hear, talk, or learn about schooling concepts because their parents often do not have formal education. When it comes to learning, their lack of experience with numbers, words, and concepts increases their cognitive load.

As children grow older they develop superior basic processes and capacities. They also develop metacognition, which helps them to understand their own cognitive activities. Lastly, they gain greater content knowledge through their experiences. These elements help reduce cognitive load in children as they develop.

Gesturing is a technique children use to reduce cognitive load while speaking. By gesturing, they can free up working memory for other tasks. Pointing allows a child to use the object they are pointing at as the best representation of it, which means they do not have to hold this representation in their working memory, thereby reducing their cognitive load. Additionally, gesturing about an object that is absent reduces the difficulty of having to picture it in their mind.

Human mental workload has gained importance, in the last few decades, as a fundamental design concept in human-computer interaction, education and other fields. For people interacting with interfaces, computers and technological devices in general, the construct plays an important role. At a low level, while processing information, often people feel annoyed and frustrated; at higher level, mental workload is critical and dangerous as it leads to confusion, it decreases the performance of information processing and it increases the chances of errors and mistakes. It is extensively documented that either mental overload or underload negatively affect performance. Hence, designers and practitioners who are ultimately interested in system or human performance need answers about operator workload at all stages of system design and operation. At an early system design phase, designers require some explicit model to predict the mental workload imposed by their technologies on end-users so that alternative system designs can be evaluated. However, human mental workload is a multifaceted and complex construct mainly applied in cognitive sciences. A plethora of ad-hoc definitions can be found in the literature. Generally, it is not an elementary property, rather it emerges from the interaction between the requirements of a task, the circumstances under which it is performed and the skills, behaviours and perceptions of the operator. Although measuring mental workload has advantages in interaction and interface design, its formalisation as an operational and computational construct has not sufficiently been addressed. Many researchers agree that too many ad-hoc models are present in the literature and that they are applied subjectively by mental workload designers thereby limiting their application in different contexts and making comparison across different models difficult.