Cognitive load

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In cognitive psychology, cognitive load is the effort being used in the working memory. According to work conducted in the field of instructional design and pedagogy, broadly, there are three types of cognitive load:

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

However, over the years, the additivity of these types of cognitive load has been investigated and questioned. Now it is believed that they circularly influence each other.<ref name="Orru, 2019">Template:Cite book</ref>

Cognitive load theory was developed in the late 1980s out of a study of problem solving by John Sweller.<ref name="Sweller, 1988">Template:Cite journal</ref> Sweller argued that instructional design can be used to reduce cognitive load in learners. Much later, other researchers developed a way to measure perceived mental effort which is indicative of cognitive load.<ref name=Paas1993>Template:Cite journal</ref><ref name="Skulmowski & Rey 2017">Template:Cite journal</ref> Task-invoked pupillary response is a reliable and sensitive measurement of cognitive load that is directly related to working memory.<ref name="Granholm et al. 1996">Template:Cite journal</ref> Information may only be stored in long term memory after first being attended to, and processed by, working memory.Template:Citation needed Working memory, however, is extremely limited in both capacity and duration.<ref>Template:Cite journal</ref> These limitations will, under some conditions, impede learning.Template:Citation needed Heavy cognitive load can have negative effects on task completion, and the experience of cognitive load is not the same in everyone.Template:Citation needed The elderly, students, and children experience different, and more often higher, amounts of cognitive load.Template:Citation needed

The fundamental tenet of cognitive load theory is that the quality of instructional design will be raised if greater consideration is given to the role and limitations of working memory. With increased distractions, particularly from cell phone use, students are more prone to experiencing high cognitive load which can reduce academic success.<ref name="When it comes to Facebook there may">Template:Cite journal</ref>

TheoryEdit

In the late 1980s, John Sweller developed cognitive load theory out of a study of problem solving,<ref name="Sweller, 1988"/> in order "to provide guidelines intended to assist in the presentation of information in a manner that encourages learner activities that optimize intellectual performance".<ref name="Sweller et al., 1998">Template:Cite journal</ref> Sweller's theory employs aspects of information processing theory to emphasize the inherent limitations of concurrent working memory load on learning during instruction.Template:Citation needed It makes use of the schema as primary unit of analysis for the design of instructional materials.Template:Citation needed

HistoryEdit

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,<ref name="Miller, 1956">Template:Cite journal</ref> 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.Template:Citation needed

In 1973 Simon and Chase were the first to use the term "chunk" to describe how people might organize information in short-term memory.<ref name="Simon and Chase, 1973">Template:Cite journal</ref> This chunking of memory components has also been described as schema construction.Template:Citation needed

In the late 1980s John Sweller developed cognitive load theory (CLT) while studying problem solving.<ref name="Sweller, 1988"/> 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 suggested 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.Template:Citation needed

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;<ref name="Paas, 1992">Template:Cite journal</ref> modality effect;<ref name="Moreno & Mayer, 1999">Template:Cite journal</ref><ref name="Mousavi, Low, & Sweller, 1995">Template:Cite journal</ref> split-attention effect;<ref name="Chandler and Sweller, 1992">Template:Cite journal</ref> worked-example effect;<ref name="Cooper & Sweller, 1987">Template:Cite journal</ref><ref name="Sweller & Cooper, 1985">Template:Cite journal</ref> and expertise reversal effect.<ref name="Kalyuga, Ayres, Chandler, and Sweller, 2003">Template:Cite journal</ref>

CategoriesEdit

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 load, and extraneous cognitive load.<ref name="Sweller et al., 1998" />

IntrinsicEdit

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.<ref name="Chandler & Sweller, 1991">Template:Cite journal</ref> According to them, all instructions have an inherent difficulty associated with them (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.<ref>Template:Cite journal</ref>

Germane loadEdit

Germane load refers to the working memory resources that the learner dedicates to managing the intrinsic cognitive load associated with the essential information for learningTemplate:Citation needed. Unlike intrinsic load, which is directly related to the complexity of the material, germane load does not stem from the presented information but from the learner's characteristics. It does not represent an independent source of working memory load; rather, it is influenced by the relationship between intrinsic and extraneous load. If the intrinsic load is high and the extraneous load is low, the germane load will be high, as the learner can devote more resources to processing the essential material. However, if the extraneous load increases, the germane load decreases, and learning is affected because the learner must use working memory resources to deal with external elements instead of the essential content. This assumes a constant level of motivation, where all available working memory resources are focused on managing both intrinsic and extraneous cognitive load.

ExtraneousEdit

Extraneous cognitive load is generated by the manner in which information is presented to learners and is under the control of instructional designers.<ref name="Chandler & Sweller, 1991" /> 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, the number of resources available to process the intrinsic load and germane load (i.e., learning) is reduced. 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.<ref name="Ginns, 2006">Template:Cite journal</ref>

An example of extraneous cognitive load occurs when there are two possible ways to describe a square to a student.<ref>Template:Cite book Template:Page needed</ref> 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.Template:Citation needed

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.Template:Citation needed

Extraneous cognitive load may have different components, such as the clarity of texts or interactive demands of educational software.<ref name="Skulmowski & Rey, 2020">Template:Cite journal</ref>

MeasurementEdit

As of 1993 Paas and Van Merriënboer<ref name=Paas1993/> had 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, taking into account both mental effort ratings and performance scores. Relative condition efficiency is calculated by subtracting standardized mental effort from standardized performance and dividing by the square root of two.<ref name=Paas1993/>

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.<ref name="Paas et al. (2003)">Template:Cite journal</ref>

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.<ref name="Fredericks et al., 2005">Template:Cite journal</ref> They believe that it may be possible to use RPP measures to set limits on workloads and for establishing work allowance.

There is active research interest in using physiological responses to indirectly estimate cognitive load, particularly by monitoring pupil diameter, eye gaze, respiratory rate, heart rate, or other factors.<ref name="Heard, Harriet, and Adams (2018)">Template:Cite journal</ref> While some studies have found correlations between physiological factors and cognitive load, the findings have not held outside controlled laboratory environments. Task-invoked pupillary response is one such physiological response of cognitive load on working memory, with studies finding that pupil dilation occurs with high cognitive load.<ref name="Granholm et al. 1996"/>

Some researchers have compared different measures of cognitive load.<ref name="Skulmowski & Rey 2017" /> 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.<ref name="DeLeeuw and Mayer (2008)">Template:Cite journal</ref> A 2020 study showed that there may be various demand components that together form extraneous cognitive load, but that may need to be measured using different questionnaires.<ref name="Skulmowski & Rey, 2020"/>

Effects of heavy cognitive loadEdit

Template:See also A heavy cognitive load typically creates error or some kind of interference in the task at hand.<ref name="Paas, 1992"/><ref name="Moreno & Mayer, 1999"/><ref name="Mousavi, Low, & Sweller, 1995"/><ref name="Chandler and Sweller, 1992"/><ref name="Cooper & Sweller, 1987"/><ref name="Sweller & Cooper, 1985"/><ref name="Kalyuga, Ayres, Chandler, and Sweller, 2003"/> A heavy cognitive load can also increase stereotyping.<ref name="Biernat et al. 2006">Template:Cite journal</ref> This is because a heavy cognitive load pushes excess information into subconscious processing, which involves the use of schemas, the patterns of thought and behavior that help us to organize information into categories and identify the relationships between them.<ref>{{#invoke:citation/CS1|citation |CitationClass=web }}</ref> Stereotypical associations may be automatically activated by the use of pattern recognition and schemas, producing an implicit stereotype effect.<ref>Template:Cite journal</ref> Stereotyping is an extension of the Fundamental Attribution Error which also increases in frequency with heavier cognitive load.<ref name=Gilbert1989>Gilbert, D. T. (1989). Thinking lightly about others: Automatic components of the social inference process. In J. S. Uleman & J. A. Bargh (Eds.), Unintended thought (pp. 189–211). New York, Guilford Press.</ref> 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).

Effects of the internetEdit

The internet has transformed how individuals process, store, and retrieve information, serving both as a cognitive aid and a potential burden on working memory. While digital tools can reduce cognitive strain by offloading memory demands onto external systems,<ref name=":0">Template:Cite journal</ref> they also introduce challenges such as information overload, decision fatigue, and attention fragmentation. These multifaceted effects necessitate a nuanced understanding of the internet’s impact on cognitive load.

One prominent phenomenon illustrating this impact is the Google Effect, also known as digital amnesia. This term describes the tendency to forget information readily available online, as individuals are less inclined to remember details they can easily access through search engines.<ref name=":1">Template:Cite journal</ref> This reliance on external digital storage aligns with transactive memory theory, wherein people distribute knowledge within a group, focusing on who knows what rather than retaining all information individually. The internet extends this system, allowing vast data storage externally and emphasizing retrieval over internal recall.<ref name=":1" /> While this can free up working memory for complex problem-solving, it may also diminish long-term retention and comprehension. Studies have shown that when individuals expect information to be accessible online, they are less likely to deeply encode it, prioritizing access over understanding.<ref name=":1" />

Beyond memory offloading, digital tools enhance cognitive efficiency by simplifying complex tasks. Online learning platforms, for instance, offer interactive elements, real-time feedback, and adaptive technologies that structure information accessibly, aligning with the principle of reducing extraneous cognitive load—elements that consume mental resources without directly contributing to learning.<ref name=":0" /> Well-designed digital environments can enhance knowledge acquisition by minimizing unnecessary processing demands, allowing learners to focus on essential concepts. Features like auto-complete functions, digital calculators, and grammar-checking tools further streamline tasks, reducing the mental effort required for routine operations.<ref name=":0" /> These advantages demonstrate how, when effectively leveraged, the internet can optimize information processing and retrieval, thereby enhancing cognitive efficiency.

However, the internet also presents significant cognitive challenges. One major issue is information overload, where the vast amount of available content overwhelms cognitive capacity, leading to decision fatigue and reduced learning efficiency.<ref name=":2">Template:Cite journal</ref> The necessity of filtering through extensive information to assess credibility and relevance adds an extraneous cognitive burden, potentially diminishing focus on core learning objectives. Research indicates that excessive information can impair decision-making by increasing cognitive effort, resulting in less effective knowledge retention.<ref name=":2" /> Additionally, the prevalence of hyperlinked texts, advertisements, and continuous updates contributes to fragmented attention, making sustained, deep learning more difficult.<ref name=":2" />

Another concern is the impact of media multitasking on cognitive function. Many individuals frequently switch between multiple online streams—checking emails, browsing social media, and engaging with various digital content sources simultaneously. While this behavior may seem productive, studies suggest that heavy media multitasking is associated with reduced working memory efficiency, diminished attentional control, and increased distractibility.<ref name=":2" /> The rapid alternation between tasks prevents sustained focus, leading to shallow information processing rather than deep comprehension. Neuroimaging research has shown that frequent multitaskers exhibit decreased activation in brain regions associated with sustained attention and impulse control, indicating that digital environments can fragment cognitive resources.<ref name=":2" />

Furthermore, the internet may alter how individuals value and interact with knowledge. In traditional learning environments, effortful cognitive processing contributes to deeper retention and understanding. However, the instant accessibility of online information can create an illusion of knowledge, where individuals overestimate their understanding simply because they can quickly look up answers.<ref name=":3">Template:Citation</ref> This reliance on digital search engines can lead to a false sense of expertise, as users mistake access to information for actual comprehension.<ref name=":3" /> This shift in cognitive processing raises questions about how the internet may reshape intellectual engagement, particularly in academic and professional settings where deep learning and critical thinking are essential.<ref name=":3" />

While cognitive offloading and digital tools offer clear advantages, the long-term consequences of internet reliance remain an active area of research. The challenge lies in balancing the use of digital aids to enhance cognitive efficiency with ensuring that such reliance does not compromise memory retention, critical thinking, and attentional control. As digital environments continue to evolve, researchers emphasize the need for strategies that optimize cognitive load management, such as designing educational interfaces that promote deep learning while minimizing distractions.<ref name=":0" /> Further investigation is needed to determine best practices for integrating digital tools into learning contexts without exacerbating the cognitive drawbacks associated with information overload and media multitasking.<ref name=":2" />

Sub-population studiesEdit

Individual differencesEdit

As of 1984 it was established for example, that there were 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.<ref name="Murphy and Wright 1984">Template:Cite journal</ref>

ElderlyEdit

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.<ref name="Wingfield et al. 2007">Template:Cite journal</ref> Heavy cognitive load can disturb balance in elderly people. 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.<ref>Template:Cite journal</ref> A 2007 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.<ref>Template:Cite journal</ref> Conversely, an increasing demand for balance can increase cognitive load.Template:Citation needed

College studentsEdit

As of 2014, an increasing cognitive load for students using a laptop in school has become a concern. With the use of Facebook and other social forms of communication, adding multiple tasks jeopardizes 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.<ref>Template:Cite journal</ref> In a study from 2013, 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.<ref name="When it comes to Facebook there may"/><ref>Template:Cite journal</ref>

ChildrenEdit

In 2004, British psychologists, Alan Baddeley and Graham Hitch proposed that the components of working memory are in place at 6 years of age.<ref name="Children">Template:Cite journal</ref> They found a clear difference between adult and child knowledge. These differences were due to developmental increases in processing efficiency.<ref name="Children"/> 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.<ref name="Siegler and Alibali"/> These children do not hear, talk, or learn about schooling concepts because their parents often do not have formal education.Template:Citation needed 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.<ref name="Siegler and Alibali">Template:Cite book Template:Page needed</ref> They also develop metacognition, which helps them to understand their own cognitive activities.<ref name="Siegler and Alibali"/> Lastly, they gain greater content knowledge through their experiences.<ref name="Siegler and Alibali"/> These elements help reduce cognitive load in children as they develop.Template:Citation needed

Gesturing is a technique children use to reduce cognitive load while speaking.<ref name="Gathercole">Template:Cite journal</ref> By gesturing, they can free up working memory for other tasks.<ref name="Gathercole"/> 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.<ref>Template:Cite journal</ref> Additionally, gesturing about an object that is absent reduces the difficulty of having to picture it in their mind.<ref name="Gathercole"/>

PovertyEdit

As of 2013 it has been theorized that an impoverished environment can contribute to cognitive load.<ref name="Mani et al. 2013">Template:Cite journal</ref> 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.<ref name="Hackman and Farah">Template:Cite journal</ref>

Embodiment and interactivityEdit

Bodily activity can both be advantageous and detrimental to learning depending on how this activity is implemented.<ref name="Skulmowski & Rey">Template:Cite journal</ref> Cognitive load theorists have asked for updates that makes CLT more compatible with insights from embodied cognition research.<ref>Template:Cite journal</ref> As a result, Embodied Cognitive Load Theory has been suggested as a means to predict the usefulness of interactive features in learning environments.<ref name="Skulmowski et al., 2016">Template:Cite journal</ref> In this framework, the benefits of an interactive feature (such as easier cognitive processing) need to exceed its cognitive costs (such as motor coordination) in order for an embodied mode of interaction to increase learning outcomes.

Application in driving and pilotingEdit

With increase in secondary tasks inside cockpit, cognitive load estimation became an important problem for both automotive drivers and pilots. The research problem is investigated in various names like drowsiness detection, distraction detection and so on. For automotive drivers, researchers explored various physiological parameters<ref>Template:Cite journal</ref> like heart rate, facial expression,<ref>Template:Cite conference</ref> ocular parameters<ref>Template:Cite journal</ref> and so on. In aviation there are numerous simulation studies on analysing pilots' distraction and attention using various physiological parameters.<ref>Template:Cite book</ref> For military fast jet pilots, researchers explored air to ground dive attacks and recorded cardiac, EEG<ref>Template:Cite journal</ref> and ocular parameters.<ref>Template:Cite journal</ref>

ReferencesEdit

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