# Cognitive load

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Effort being used in the working memory

In [cognitive psychology](/source/Cognitive_psychology), **cognitive load** is the effort being used in the [working memory](/source/Working_memory). According to work conducted in the field of [instructional design](/source/Instructional_design) and [pedagogy](/source/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](/source/Schema_(psychology))).

- *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.[1]

Cognitive load theory was developed in the late 1980s out of a study of [problem solving](/source/Problem_solving) by [John Sweller](/source/John_Sweller).[2] Sweller argued that [instructional design](/source/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.[3][4] [Task-invoked pupillary response](/source/Task-invoked_pupillary_response) is a reliable and sensitive measurement of cognitive load that is directly related to working memory.[5] Much information, such as [Declarative knowledge](/source/Declarative_knowledge), may only be stored in [long-term memory](/source/Long-term_memory) after first being attended to, and processed by, working memory. This was originally thought to be true for all long-term memory under the classic "gateway" model of the [Atkinson–Shiffrin memory model](/source/Atkinson%E2%80%93Shiffrin_memory_model). However, modern research has shown that some long-term memory can be encoded while bypassing, or working in parallel with, working memory.[6] Working memory, however, is extremely limited in both capacity and duration.[7] These limitations will, under some conditions, impede learning.[*[citation needed](https://en.wikipedia.org/wiki/Wikipedia:Citation_needed)*] Heavy cognitive load can have negative effects on task completion, and the experience of cognitive load is not the same in everyone.[*[citation needed](https://en.wikipedia.org/wiki/Wikipedia:Citation_needed)*] The elderly, students, and children experience different, and more often higher, amounts of cognitive load.[*[citation needed](https://en.wikipedia.org/wiki/Wikipedia: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 the rise in digital technology and smartphones, students are more prone to experiencing high cognitive load, which can reduce academic success.[8]

## Theory

In the late 1980s, educational psychologist [John Sweller](/source/John_Sweller) developed cognitive load theory out of a study of [problem solving](/source/Problem_solving),[2] in order "to provide guidelines intended to assist in the presentation of information in a manner that encourages learner activities that optimize intellectual performance".[9] Sweller's theory employs aspects of [information processing](/source/Information_processing_(psychology)) theory to emphasize the inherent limitations of concurrent [working memory](/source/Working_memory) load on learning during instruction.[*[citation needed](https://en.wikipedia.org/wiki/Wikipedia:Citation_needed)*] It makes use of the [schema](/source/Schema_(psychology)) as primary unit of analysis for the design of [instructional materials](/source/Instructional_materials).[*[citation needed](https://en.wikipedia.org/wiki/Wikipedia:Citation_needed)*]

### 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](/source/George_Armitage_Miller). In his classic paper,[10] Miller was perhaps the first to suggest that human [working memory capacity](/source/Working_memory#Capacity) has inherent limits. His experimental results suggested that humans are generally able to hold only [seven plus or minus two units](/source/The_Magical_Number_Seven%2C_Plus_or_Minus_Two) of information in short-term memory.[11]

In 1973 Simon and Chase were the first to use the term *chunk* to describe how people might organize information in [short-term memory](/source/Short-term_memory).[12] This chunking of memory components has also been described as [schema](/source/Schema_(psychology)) construction.[13]

In the late 1980s Sweller developed cognitive load theory (CLT) while studying problem solving.[2] Studying learners as they solved problems, he and his associates found that learners often use a problem-solving strategy called [means–ends analysis](/source/Means%E2%80%93ends_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.[*[citation needed](https://en.wikipedia.org/wiki/Wikipedia: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;[14] [modality effect](/source/Modality_effect);[15][16] [split-attention effect](/source/Split-attention_effect);[17] [worked-example effect](/source/Worked-example_effect);[18][19] and [expertise reversal effect](/source/Expertise_reversal_effect).[20]

## Categories

Cognitive load theory provides a general framework with broad implications for instructional design by focusing on the limitations of human working memory as a central constraint on learning. The primary aim of the theory is to guide the effective use of this limited cognitive resource by structuring learning conditions and instructional materials in ways that reduce extraneous cognitive load and optimize intrinsic cognitive load. By doing so, instructional designers can better direct learners' attention toward essential information and processes that support schema construction, thereby increasing germane cognitive load. Cognitive load theory distinguishes among three types of cognitive load: intrinsic, extraneous, and germane cognitive load.[9]

### Intrinsic

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.[21] According to them, all instructions have an inherent difficulty associated with them (e.g., the calculation of 2 + 2, versus solving a [differential equation](/source/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.[22]

### Germane load

*Germane load* refers to the working memory resources that the learner dedicates to managing the intrinsic cognitive load associated with the essential information for learning.[*[citation needed](https://en.wikipedia.org/wiki/Wikipedia: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.

### Extraneous

Extraneous cognitive load is generated by the manner in which information is presented to learners and is under the control of instructional designers.[21] 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.[23]

An example of extraneous cognitive load occurs when there are two possible ways to describe a square to a student.[24] 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.[*[citation needed](https://en.wikipedia.org/wiki/Wikipedia: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.[*[citation needed](https://en.wikipedia.org/wiki/Wikipedia:Citation_needed)*]

Extraneous cognitive load may have different components, such as the clarity of texts or interactive demands of educational software.[25]

## Measurement

As of 1993 Paas and Van Merriënboer[3] 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.[3]

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.[26]

The ergonomic approach seeks a quantitative neurophysiological expression of cognitive load which can be measured using common instruments, for example using the [heart rate](/source/Heart_rate)-[blood pressure](/source/Blood_pressure) product (RPP) as a measure of both cognitive and physical occupational workload.[27] 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.[28] 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](/source/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.[5]

Some researchers have compared different measures of cognitive load.[4] 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.[29] 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.[25] Some research suggests that cognitive load theory has "Additivity hypothesis", which indicates that the three separate types of cognitive load may overlap. This would mean that cognitive load theory would need a clearer distinction between types of cognitive load.[30]

## Effects of heavy cognitive load

See also: [Audience effect](/source/Audience_effect) and [Drive theory](/source/Drive_theory)

A heavy cognitive load typically creates [error](/source/Error) or some kind of interference in the task at hand.[14][15][16][17][18][19][20][*[excessive citations](https://en.wikipedia.org/wiki/Wikipedia:Citing_sources#Bundling_citations)*] A heavy cognitive load can also increase [stereotyping](/source/Stereotype).[31] This is because a heavy cognitive load pushes excess information into [subconscious](/source/Subconscious) processing, which involves the use of schemas, the patterns of thought and behavior that help to organize information into categories and identify the relationships between them.[32] Stereotypical associations may be automatically activated by the use of pattern recognition and schemas, producing an [implicit stereotype](/source/Implicit_stereotype) effect.[33] Stereotyping is an extension of the [fundamental attribution error](/source/Fundamental_attribution_error), which also increases in frequency with heavier cognitive load.[34] The notions of cognitive load and [arousal](/source/Arousal) contribute to the overload hypothesis explanation of [social facilitation](/source/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 internet

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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,[35] they also introduce challenges such as [information overload](/source/Information_overload), [decision fatigue](/source/Decision_fatigue), and [attention fragmentation](/source/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](/source/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.[36] This reliance on external digital storage aligns with [transactive memory](/source/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.[36] 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.[36]

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.[35] 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.[35] 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](/source/Information_overload), where the vast amount of available content overwhelms cognitive capacity, leading to decision fatigue and reduced learning efficiency.[37] 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.[37] Additionally, the prevalence of hyperlinked texts, advertisements, and continuous updates contributes to [fragmented attention](/source/Fragmented_attention), making sustained, deep learning more difficult.[37]

Another concern is the impact of [media multitasking](/source/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](/source/Attentional_control), and increased [distractibility](/source/Distractibility).[37] The rapid alternation between tasks prevents sustained focus, leading to shallow information processing rather than deep comprehension. [Neuroimaging](/source/Neuroimaging) research has shown that frequent multitaskers exhibit decreased activation in brain regions associated with sustained attention and [impulse control](/source/Impulse_control), indicating that digital environments can fragment cognitive resources.[37]

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.[38] This reliance on digital search engines can lead to a false sense of expertise, as users mistake access to information for actual comprehension.[38] 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.[38]

One domain where the effect of the internet may have adverse consequences for both cognitive performance and brain health is spatial navigation. As part of their training, London taxi-drivers need to memorize and navigate through the city's complex streets, leading to structural changes in the size of a key brain region associated with memory consolidation, the hippocampus.[39] More recent studies suggest such enlargement may provide protection against age-related dementia.[40][41] As a result, an over-reliance on GPS systems in apps like Google Maps, which dispense with the need for remembering routes and spatial reasoning, may also suppress brain plasticity for spatial navigation and its beneficial health effects.

While cognitive offloading[42] 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, attentional control, and even brain health. 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.[35] 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.[37]

## Emerging effects of AI

A growing body of evidence also suggests that AI may have a uniquely harmful effect on our cognition.[43][44][45][46][47][48][49] Beyond search algorithms being relied on for spatial navigation, more recent machine learning applications outsource key mental functions, such as sensing the world (for example, face recognition), moving our bodies (robotics controllers), making choices (recommendation systems), and solving problems (chatbots). In the realm of education, productive struggle requiring the use of our working and long-term memory systems among others is considered "[desirable difficulty](/source/Desirable_difficulty)" and facilitates improved cognitive performance.[47][48] Similarly, in healthcare, regularly applying skills ensures their retention and proficiency, as illustrated by a study showing poorer surgical outcomes among physicians, or [deskilling](/source/Deskilling), when their AI tool was discontinued.[44]

## Sub-population studies

### Individual differences

As of 1984 it was established, for example, that there are individual differences in processing capacities between [novices](/source/Novice) and [experts](/source/Expert). 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.[50] We also see structural differences in long-term memory as reflected in the London taxi driver studies cited above.[39]

### 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.[51] Heavy cognitive load can disturb [balance](/source/Balance_(ability)) in elderly people. The relationship between heavy cognitive load and control of [center of mass](/source/Center_of_mass) are heavily correlated in the elderly population. As cognitive load increases, the sway in center of mass in elderly individuals increases.[52] 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.[53] Conversely, an increasing demand for balance can increase cognitive load.[*[citation needed](https://en.wikipedia.org/wiki/Wikipedia:Citation_needed)*]

### College students

As of 2014, an increasing cognitive load for students using a laptop in school has become a concern. With the use of [Facebook](/source/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.[54] 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](/source/GPA).[8][55]

### Children

In 2004, British psychologists, [Alan Baddeley](/source/Alan_Baddeley) and [Graham Hitch](/source/Graham_Hitch) proposed that the components of working memory are in place at six years of age.[56] They found a clear difference between adult and child knowledge. These differences were due to developmental increases in processing efficiency.[56] Children lack [general knowledge](/source/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.[57] These children do not hear, talk, or learn about schooling concepts because their parents often do not have formal education.[*[citation needed](https://en.wikipedia.org/wiki/Wikipedia: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.[57] They also develop [metacognition](/source/Metacognition), which helps them to understand their own cognitive activities.[57] Lastly, they gain greater content knowledge through their experiences.[57] These elements help reduce cognitive load in children as they develop.[*[citation needed](https://en.wikipedia.org/wiki/Wikipedia:Citation_needed)*]

[Gesturing](/source/Gesture) is a technique children use to reduce cognitive load while speaking.[58] By gesturing, they can free up working memory for other tasks.[58] 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.[59] Additionally, gesturing about an object that is absent reduces the difficulty of having to picture it in their mind.[58]

### Poverty

As of 2013 it has been theorized that an impoverished environment can contribute to cognitive load.[60] 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](/source/Socioeconomic_status) that are not present in middle and upper-class people.[61]

## Embodiment and interactivity

Bodily activity can both be advantageous and detrimental to learning depending on how this activity is implemented.[62] Cognitive load theorists have asked for updates that makes CLT more compatible with insights from [embodied cognition](/source/Embodied_cognition) research.[63] As a result, embodied cognitive load theory has been suggested as a means to predict the usefulness of interactive features in learning environments.[64] 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 piloting

With increase in secondary tasks inside the cockpit, cognitive load estimation has become an important problem for both automotive drivers and pilots. The issue has been addressed with various features such as [drowsiness detection](/source/Driver_drowsiness_detection). For automotive drivers, researchers have explored various physiological parameters[65] like heart rate, facial expression,[66] and ocular parameters.[67] In aviation there are numerous simulation studies on analysing pilots' distraction and attention using various physiological parameters.[68] For military fast jet pilots, researchers have explored air-to-ground dive attacks and recorded cardiac, EEG[69] and ocular parameters.[70]

## See also

- [Educational psychology](/source/Educational_psychology) – Branch of psychology concerned with the scientific study of human learning

- [Energy (psychological)](/source/Energy_(psychological))

- [Human factors and ergonomics](/source/Human_factors_and_ergonomics)

- [Information overload](/source/Information_overload) – Decision making with too much information

- [Occupational stress](/source/Occupational_stress) – Tensions related to work

- [Sensory overload](/source/Sensory_overload) - A similar, but subconscious overload, due to excessive sensory information being processed by the brain

- [Task-invoked pupillary response](/source/Task-invoked_pupillary_response) – Pupilliary dilation from cognitive effort

- [Task loading](/source/Task_loading) – Relationship between operator capacity and the accumulated activities that must be done

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1. **[^](#cite_ref-53)** Faulkner, Kimberly A.; Redfern, Mark S.; Cauley, Jane A.; Landsittel, Douglas P.; Studenski, Stephanie A.; Rosano, Caterina; Simonsick, Eleanor M.; Harris, Tamara B.; Shorr, Ronald I.; Ayonayon, Hilsa N.; Newman, Anne B.; Health, Aging, and Body Composition, Study. (April 2007). "Multitasking: Association Between Poorer Performance and a History of Recurrent Falls". *Journal of the American Geriatrics Society*. **55** (4): 570–576. [doi](/source/Doi_(identifier)):[10.1111/j.1532-5415.2007.01147.x](https://doi.org/10.1111%2Fj.1532-5415.2007.01147.x). [PMID](/source/PMID_(identifier)) [17397436](https://pubmed.ncbi.nlm.nih.gov/17397436). [S2CID](/source/S2CID_(identifier)) [32223760](https://api.semanticscholar.org/CorpusID:32223760).{{[cite journal](https://en.wikipedia.org/wiki/Template:Cite_journal)}}: CS1 maint: multiple names: authors list ([link](https://en.wikipedia.org/wiki/Category:CS1_maint:_multiple_names:_authors_list))

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1. ^ [***a***](#cite_ref-Children_56-0) [***b***](#cite_ref-Children_56-1) Gathercole, Susan E.; Pickering, Susan J.; Ambridge, Benjamin; Wearing, Hannah (2004). "The Structure of Working Memory From 4 to 15 Years of Age". *Developmental Psychology*. **40** (2): 177–190. [CiteSeerX](/source/CiteSeerX_(identifier)) [10.1.1.529.2727](https://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.529.2727). [doi](/source/Doi_(identifier)):[10.1037/0012-1649.40.2.177](https://doi.org/10.1037%2F0012-1649.40.2.177). [PMID](/source/PMID_(identifier)) [14979759](https://pubmed.ncbi.nlm.nih.gov/14979759).

1. ^ [***a***](#cite_ref-Siegler_and_Alibali_57-0) [***b***](#cite_ref-Siegler_and_Alibali_57-1) [***c***](#cite_ref-Siegler_and_Alibali_57-2) [***d***](#cite_ref-Siegler_and_Alibali_57-3) Siegler, Robert S.; Alibali, Martha Wagner (2005). *Children's Thinking*. Pearson Education/Prentice Hall. [ISBN](/source/ISBN_(identifier)) [978-0-13-111384-8](https://en.wikipedia.org/wiki/Special:BookSources/978-0-13-111384-8).[*[page needed](https://en.wikipedia.org/wiki/Wikipedia:Citing_sources)*]

1. ^ [***a***](#cite_ref-Gathercole_58-0) [***b***](#cite_ref-Gathercole_58-1) [***c***](#cite_ref-Gathercole_58-2) Ping, Raedy; Goldin-Meadow, Susan (May 2010). ["Gesturing Saves Cognitive Resources When Talking About Nonpresent Objects"](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3733275). *Cognitive Science*. **34** (4): 602–619. [doi](/source/Doi_(identifier)):[10.1111/j.1551-6709.2010.01102.x](https://doi.org/10.1111%2Fj.1551-6709.2010.01102.x). [PMC](/source/PMC_(identifier)) [3733275](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3733275). [PMID](/source/PMID_(identifier)) [21564226](https://pubmed.ncbi.nlm.nih.gov/21564226).

1. **[^](#cite_ref-59)** Ballard, Dana H.; [Hayhoe, Mary M.](/source/Mary_Hayhoe); Pook, Polly K.; Rao, Rajesh P. N. (1 December 1997). "Deictic codes for the embodiment of cognition". *Behavioral and Brain Sciences*. **20** (4): 723–742. [CiteSeerX](/source/CiteSeerX_(identifier)) [10.1.1.49.3813](https://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.49.3813). [doi](/source/Doi_(identifier)):[10.1017/s0140525x97001611](https://doi.org/10.1017%2Fs0140525x97001611). [PMID](/source/PMID_(identifier)) [10097009](https://pubmed.ncbi.nlm.nih.gov/10097009). [S2CID](/source/S2CID_(identifier)) [1961389](https://api.semanticscholar.org/CorpusID:1961389).

1. **[^](#cite_ref-Mani_et_al._2013_60-0)** Mani, A.; Mullainathan, S.; Shafir, E.; Zhao, J. (29 August 2013). "Poverty Impedes Cognitive Function". *Science*. **341** (6149): 976–980. [Bibcode](/source/Bibcode_(identifier)):[2013Sci...341..976M](https://ui.adsabs.harvard.edu/abs/2013Sci...341..976M). [CiteSeerX](/source/CiteSeerX_(identifier)) [10.1.1.398.6303](https://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.398.6303). [doi](/source/Doi_(identifier)):[10.1126/science.1238041](https://doi.org/10.1126%2Fscience.1238041). [PMID](/source/PMID_(identifier)) [23990553](https://pubmed.ncbi.nlm.nih.gov/23990553). [S2CID](/source/S2CID_(identifier)) [1684186](https://api.semanticscholar.org/CorpusID:1684186).

1. **[^](#cite_ref-Hackman_and_Farah_61-0)** Hackman, Daniel A.; Farah, Martha J. (February 2009). ["Socioeconomic status and the developing brain"](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3575682). *Trends in Cognitive Sciences*. **13** (2): 65–73. [doi](/source/Doi_(identifier)):[10.1016/j.tics.2008.11.003](https://doi.org/10.1016%2Fj.tics.2008.11.003). [PMC](/source/PMC_(identifier)) [3575682](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3575682). [PMID](/source/PMID_(identifier)) [19135405](https://pubmed.ncbi.nlm.nih.gov/19135405).

1. **[^](#cite_ref-Skulmowski_&_Rey_62-0)** Skulmowski, Alexander; Rey, Günter Daniel (7 March 2018). ["Embodied learning: introducing a taxonomy based on bodily engagement and task integration"](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5840215). *Cognitive Research: Principles and Implications*. **3** (1): 6. [doi](/source/Doi_(identifier)):[10.1186/s41235-018-0092-9](https://doi.org/10.1186%2Fs41235-018-0092-9). [PMC](/source/PMC_(identifier)) [5840215](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5840215). [PMID](/source/PMID_(identifier)) [29541685](https://pubmed.ncbi.nlm.nih.gov/29541685).

1. **[^](#cite_ref-63)** Paas, Fred; Sweller, John (6 September 2011). ["An Evolutionary Upgrade of Cognitive Load Theory: Using the Human Motor System and Collaboration to Support the Learning of Complex Cognitive Tasks"](https://doi.org/10.1007%2Fs10648-011-9179-2). *Educational Psychology Review*. **24** (1): 27–45. [doi](/source/Doi_(identifier)):[10.1007/s10648-011-9179-2](https://doi.org/10.1007%2Fs10648-011-9179-2). [hdl](/source/Hdl_(identifier)):[1765/31101](https://hdl.handle.net/1765%2F31101).

1. **[^](#cite_ref-Skulmowski_et_al.,_2016_64-0)** Skulmowski, Alexander; Pradel, Simon; Kühnert, Tom; Brunnett, Guido; Rey, Günter Daniel (January 2016). "Embodied learning using a tangible user interface: The effects of haptic perception and selective pointing on a spatial learning task". *Computers & Education*. 92–93: 64–75. [doi](/source/Doi_(identifier)):[10.1016/j.compedu.2015.10.011](https://doi.org/10.1016%2Fj.compedu.2015.10.011). [S2CID](/source/S2CID_(identifier)) [10493691](https://api.semanticscholar.org/CorpusID:10493691).

1. **[^](#cite_ref-65)** Healey, J.A.; Picard, R.W. (June 2005). "Detecting stress during real-world driving tasks using physiological sensors". *IEEE Transactions on Intelligent Transportation Systems*. **6** (2): 156–166. [Bibcode](/source/Bibcode_(identifier)):[2005ITITr...6..156H](https://ui.adsabs.harvard.edu/abs/2005ITITr...6..156H). [CiteSeerX](/source/CiteSeerX_(identifier)) [10.1.1.73.4200](https://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.73.4200). [doi](/source/Doi_(identifier)):[10.1109/TITS.2005.848368](https://doi.org/10.1109%2FTITS.2005.848368). [S2CID](/source/S2CID_(identifier)) [1409560](https://api.semanticscholar.org/CorpusID:1409560).

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1. **[^](#cite_ref-67)** Prabhakar, Gowdham; Mukhopadhyay, Abhishek; Murthy, Lrd; Modiksha, Madan; Sachin, Deshmukh; Biswas, Pradipta (1 December 2020). ["Cognitive load estimation using ocular parameters in automotive"](https://doi.org/10.1016%2Fj.treng.2020.100008). *Transportation Engineering*. **2** 100008. [doi](/source/Doi_(identifier)):[10.1016/j.treng.2020.100008](https://doi.org/10.1016%2Fj.treng.2020.100008).

1. **[^](#cite_ref-68)** Kramer, Arthur F. (2020). "Physiological metrics of mental workload: A review of recent progress". In Damos, D. (ed.). *Multiple Task Performance*. CRC Press. pp. 279–328. [doi](/source/Doi_(identifier)):[10.1201/9781003069447-14](https://doi.org/10.1201%2F9781003069447-14). [ISBN](/source/ISBN_(identifier)) [978-1-003-06944-7](https://en.wikipedia.org/wiki/Special:BookSources/978-1-003-06944-7). [S2CID](/source/S2CID_(identifier)) [241713101](https://api.semanticscholar.org/CorpusID:241713101).

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## Further reading

- Barrett, H. Clark; Frederick, David A.; Haselton, Martie G.; Kurzban, Robert (2006). "Can manipulations of cognitive load be used to test evolutionary hypotheses?". *Journal of Personality and Social Psychology*. **91** (3): 513–518. [CiteSeerX](/source/CiteSeerX_(identifier)) [10.1.1.583.7931](https://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.583.7931). [doi](/source/Doi_(identifier)):[10.1037/0022-3514.91.3.513](https://doi.org/10.1037%2F0022-3514.91.3.513). [PMID](/source/PMID_(identifier)) [16938033](https://pubmed.ncbi.nlm.nih.gov/16938033).

- Cooper, Graham (1 December 1990). ["Cognitive load theory as an aid for instructional design"](https://doi.org/10.14742%2Fajet.2322). *Australasian Journal of Educational Technology*. **6** (2). [doi](/source/Doi_(identifier)):[10.14742/ajet.2322](https://doi.org/10.14742%2Fajet.2322).

- Cooper, Graham (1998). ["Research into Cognitive Load Theory and Instructional Design at UNSW"](https://web.archive.org/web/20070830131437/http://education.arts.unsw.edu.au/staff/sweller/clt/index.html). Archived from [the original](http://education.arts.unsw.edu.au/staff/sweller/clt/index.html) on 30 August 2007.

- Plass, J.L.; Moreno, R.; Brünken, R., eds. (2010). *Cognitive Load Theory*. New York: Cambridge University Press. [ISBN](/source/ISBN_(identifier)) [978-0-521-67758-5](https://en.wikipedia.org/wiki/Special:BookSources/978-0-521-67758-5).

- ["UNSW Cognitive Load Theory Conference- Sydney Australia 24-26 March 2007"](https://web.archive.org/web/20070409152039/http://education.arts.unsw.edu.au/news/conferences.html). 31 October 2005. Archived from [the original](http://education.arts.unsw.edu.au/news/conferences.html) on 9 April 2007.

- Khawaja, M. Asif; Chen, Fang; Marcus, Nadine (April 2014). "Measuring Cognitive Load Using Linguistic Features: Implications for Usability Evaluation and Adaptive Interaction Design". *International Journal of Human-Computer Interaction*. **30** (5): 343–368. [doi](/source/Doi_(identifier)):[10.1080/10447318.2013.860579](https://doi.org/10.1080%2F10447318.2013.860579). [S2CID](/source/S2CID_(identifier)) [2374883](https://api.semanticscholar.org/CorpusID:2374883).

- Sweller, John (January 1994). "Cognitive load theory, learning difficulty, and instructional design". *Learning and Instruction*. **4** (4): 295–312. [doi](/source/Doi_(identifier)):[10.1016/0959-4752(94)90003-5](https://doi.org/10.1016%2F0959-4752%2894%2990003-5). [S2CID](/source/S2CID_(identifier)) [145058758](https://api.semanticscholar.org/CorpusID:145058758).

- Sweller, J. (1999). *Instructional design in technical areas*. Camberwell, Australia: Australian Council for Educational Research. [ISBN](/source/ISBN_(identifier)) [978-0-86431-312-6](https://en.wikipedia.org/wiki/Special:BookSources/978-0-86431-312-6).

### 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 (4) [ISSN](/source/ISSN_(identifier)) [0046-1520](https://search.worldcat.org/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](/source/ISO_9241) Ergonomics of Human System Interaction

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Adapted from the Wikipedia article [Cognitive load](https://en.wikipedia.org/wiki/Cognitive_load) by Wikipedia contributors ([contributor history](https://en.wikipedia.org/wiki/Cognitive_load?action=history)). Available under [Creative Commons Attribution-ShareAlike 4.0 International](https://creativecommons.org/licenses/by-sa/4.0/). Changes may have been made.