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Cognitive Load Theory

Cognitive Load Theory (CLT) is an instructional theory that starts from the idea that our working memory is limited with respect to the amount of information it can hold, and the number of operations it can perform on that information (Van Gerven et. al., 2003). That means a learner should be encouraged to use his or her limited working memory efficiently, especially when learning a difficult task (Van Gerven et. al., 2003). We need to recognize the role and the limitation of working memory to help develop quality instruction (Cooper, 1998). Thus, we as instructional designers need to find ways to help optimize the working memory. Hence, the key aspect of the theory is the relation between long-term memory and working memory, and how instructional materials interact with this cognitive system (Ayres, 2006).

Cognitive load may vary due to intrinsic, germane, or extraneous demands.

Theorist

John Sweller
Dr. John Sweller is currently working at the University of New South Wales, Sydney, Australia. He leads a team investigating cognitive processes and their applications for teaching techniques and instructional design, with cognitive load theory being the major framework (UNSW, 2006).

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Diagram

Cognitive load may vary due to intrinsic, germane, or extraneous demands.

+ + =

Figure 1: By Chipperfield (2006)

Cipperfield (2006) states that for a given problem or task, ‘I’ cannot be changed. But ‘G’ and ‘E’ can vary and are inversely proportional to each other. Because according to Chipperfield (2006), the more extraneous load the less room for germane load. Thus, the duty of an instructional designer is to limit the amount of extraneous load and to build instructional presentations and activities that encourage germane load or schema formation to take place.

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Terms

Overview
We cannot change the intrinsic load, thus it leaves us only to work with germane and extraneous load. Germane load helps in new schema formation. Our ideal instructional design objective will be to increase the germane load and reduce the extraneous load. This means the more extraneous load the less room for germane load.

Intrinsic cognitive load: It depends completely on the complexity or difficulty level of the information or of the to-be-learned content. It is the memory required by the thinking task at a given time (Chipperfield, 2006). It measures the amount of the working memory in use due to the interactivity of the amount of information being processed (Chipperfield, 2006).
This cannot be modified by instructional design.
When Intrinsic Cognitive load is low: When the cognitive load is low (simple content) sufficient mental resource may remain to enable a learner to learn from “any” type of instructional material even that which imposes a high level of extraneous cognitive load.

When Intrinsic Cognitive load is High: If the intrinsic cognitive load is high (difficult content) and the extraneous cognitive load is also high, then total cognitive load will exceed mental resources and learning may fail to occur.

Modifying the instructional materials: Modifying the instructional material to engineer a lower level of extraneous cognitive load will facilitate learning, if the resulting total cognitive load falls to a level that is within the bounds of mental resources.

Germane load: Is the load that helps building new complex schema in a successive manner helping the learner to move from novice to expert. It is a self effort to learn, and memorize information learned.
Extraneous cognitive load: Results from the techniques in which the to-be-learned information is presented. Extraneous cognitive load does not contribute to learning (Chipperfield, 2006). This can be modified by instructional design. It can be changed in a variety of ways, by enhancing the organization, chunking, and presentation techniques of to-be-learned information. Other ways are by using adjunct aids, and providing specific learning instructions.
Cognitive load: Refers to the total amount of cognitive activity imposed on working memory at an instance in time. The major factor that contributes to cognitive load is the number of items that need to be attended to.
Cognitive schemata: Are information structures in long-term memory that enable someone to solve a certain category of problems and at the same time save working memory by chunking information elements and production rules into a whole. It facilitates transfer of performance of an acquired knowledge (Van Gerven, 2003). According to Chipperfield (2006), the difference between an expert and novice schema is based on their ability to categorize problems using schemas stored in long-term memory.

Cooper (1998) and Chipperfield (2006) talk about two distinguishing feature of expertise as being:
a. The expensive schemas (information networks) that an expert holds.
b. The high level of automation (ability to perform tasks without concentration) the expert exhibits.

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Implications

Principles of Cognitve Learning (Cipperfield, 2006)
According to Chipperfield (2006), CLT is based on the following principles of cognitive learning:

  1. That short-term memory (working memory) is limited in capacity to about seven informational units.
  2. Long-term memory is unlimited in capacity and is where all information and knowledge is stored.
  3. Knowledge is stored in long-term memory as schemas or schemata.
  4. Schemas, no matter how large or how complex, are treated as a single entity in working memory.
  5. Schemas can become automated.
Principles of Cognitive Load Theory (Cooper, 1998)
  1. Working memory is extremely limited.
  2. Long term memory is essentially unlimited.
  3. The process of learning requires working memory to be actively engaged in the comprehension (and processing) of instructional material to encode to-be-learned information into long term memory.
  4. If the resources of working memory are exceeded then learning will be ineffective.

Principles of cognitive load theory application to instructional design (Copper, 1998)

  1. Excessively high levels of cognitive load may result directly from the instructional materials presented to students.
  2. Redesigning instructional materials to reduce the levels of extraneous cognitive load may enhance learning.
  3. Content areas that are more likely to demonstrate beneficial results from improved instructional design are those that deal with “complex” information when the elements of to-be-learned information interact with one another (therefore imposing a high level of intrinsic cognitive load).

Practical Design Recommendations:

According to Kearsley (2006), cognitive load theory can be best applied in the areas of instructional design of cognitively difficult and technically challenging material. He states that to maintain effective learning environment we need to keep the cognitive load of the learners at a minimum during the learning process.

Miller (2006) discusses from Swellers paper written in 1999 about some instructional design recommendation provided by Sweller (1999). (Sweller, J. (1999). Instructional design in technology areas. Australian Educational Review No. 43, ACER Press, Camberwell, Australia.)

  1. Change problem solving methods to avoid means-ends approaches that impose a heavy working memory load by using goal-free problems or worked examples.
  2. Physically integrate multiple sources of information whenever possible to eliminate the need for learners to have to mentally integrate that information which increases the load on working memory.
  3. Reduce redundancy and repetitive information whenever possible so that the load on working memory is lessened.
  4. Use auditory and visual information under conditions where both sources of information are essential (i.e. non-redundant) to understanding. This helps increase the capacity of working memory.

Theory Implications

Cognitive load theory has many implications in the design of learning materials. It is our objective to minimize extraneous cognitive load thus maximizing the germane load. Extraneous cognitive load does not contribute to learning.
(Copper, 1998)
1. Remembering information (Cooper, 1998): Our brain has an ability to think and behave intellectually because of this, human are able to quickly identify meaning to a stimulated provided and are held relatively permanently in the long-term memory. It is similar to Gestalt’s Law of Closure: people tent to fill in missing pieces to form a complete picture (Ormrod, 1999).
2. Chunking information (Cooper, 1998): When presenting a “large” set of to-be-learned information it is better to “chunk” the information into smaller groups. This is possible based on Gestalt’s Law of Proximity (people tend to perceive as a unit those things that are close together in space [Ormrod, 1999]) and Similarity (people tent to perceive as a unit those things that are similar to one another [Ormrod, 1999]).
3. Use Goal free problems (Cooper, 1998): To understand this first we need to look at means-ends analysis.
Means-ends analysis: Means-ends analysis to solve problems (Cooper, 1998): this is a problem solving strategy, which is widely used to solve traditional problems by people who are not highly familiar with specific problem type. In this procedure, you solve problem backwards from goal to the given problem rather than working forward from the given theproblem to the goal.

  1. Bad Example: if y = x +6, z = 6, find the value of y.
    A novice problem solver (using means-ends analysis) would first focus on the goal state (find the value of y). After reading the question half way through, the problem the novice learner will forget certain elements of the equation, because their working memory has been heavily taxed attending to many elements of the problem. Nevertheless, eventually he will come to the answer of y=15, which is the goal state.

Goal free problem: Means-ends analysis operates on the principle of reducing differences between the goal state and problem givens. If problems are “goal free” ie “find what you can”, then a problem solver has little option but to focus on the information provided (the given data) and to use it where ever possible. This automatically induces a forwards working solution path similar to those generated byexpert problem solvers. Such forward working solutions impose very low levels of cognitive load and facilitate learning.

  1. Good Example: if y = x +6, z = 6, find what you can
    In this case the attention will be focused on “z=6” as this is the only variable with numeric value. Re-reading the question you can identify what value needs to be substituted in the equation. Thus, the learner comes to the answer y = 15 because nothing else needs to be found anymore. It is seen that this type of solution path is far simpler than that generated by means ends analysis.
4. Modality effect: People learn better when words are presented as speech rather than onscreen text.
5. Multimedia effect: People learn better when both words and graphics are included, as long as the graph is not self-explanatory.
6. Contiguity effect: People learn better when you place print words near corresponding graphics.
7. Redundancy effect: Simultaneous presentations of similar (redundant) content must be avoided. Avoid words as narrations and identical text with graphics.
8. Coherence effect: Peoples’ learning is hindered when extraneous sound, pictures, and words are used in teaching.
9. Split attention effect: Instructional materials, which require both textual and graphical sources of instruction, should integrate the text into the graphic in such a way that the relationships between textual components and graphical components are clearly indicated.
10. Worked example effect: Use worked examples to replace some practice. Students learn by studying worked examples. Make sure the examples and practice items are presented in an alternative sequence: example type 1, practice type 1, example type 2, practice type 2. This strategy is highly effective for teaching math based content (Cooper, 1998).
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Examples

1. While designing an instructional textbook for a third grade science class the cognitive load of the text can be reduced by :

a. using large type sizes (14 points)
b. white space
c. more readable text
d. clear layouts
e. clarify text by examples
f. summaries
g. headings
h. signals

In combining an illustration of blood flow through the heart with text and labels, the separation of the text from the illustration forces the learner to look back and forth between the specified parts of the illustration and the text. If the diagram is self-explanatory, research data indicates that processing the text unnecessarily increases working memory load. If the information could be replaced with numbered arrows in the labeled illustration, the learner could concentrate better on learning the content from the illustration alone. Alternatively, if the text is essential to intelligibility, placing it on the diagram rather than separated will reduce cognitive load associated with searching for relations between the text and the diagram.

2. If you want the learner to learn a list of names of states in two different countries you can minimizing the amount of information presented at one time through chunking, sequencing, grouping and visual cues of content to reduce cognitive load.

a. Chunking:

Grouping
State
Cities
Southern States

Alabama
Texas

Mobile, Montgomery, Birmingham
Houston, Dallas, Austin, San Antonio

 

b. Visual Cues:

State
Cue
Florida Sunshine State
New Jersey Garden State
Texas Star State

3. Kearsley (2006) combining an illustration of blood flow through the heart with text and labels (contiguity theory), the separation of the text from the illustration forces the learner to look back and forth between the specified parts of the illustration and the text. If the diagram is self-explanatory, research data indicates that processing the text unnecessarily increases working memory load. If the information could be replaced with numbered arrows in the labeled illustration, the learner could concentrate better on learning the content from the illustration alone. Alternatively, if the text is essential to intelligibility, placing it on the diagram rather than separated will reduce cognitive load associated with searching for relations between the text and the diagram (Sweller, 1999). (Sweller, J. Instructional Design in Technical Areas, [Camberwell, Victoria, Australia: Australian Council for Educational Research, 1999]).

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Resources

  1. Ayres, P. (2006). UNSW, 2006. Cognitive load theory at UNSW. Sydney, Australia: University of New South Wales (UNSW). Retrieved on November 10, 2006 from http://education.arts.unsw.edu.au/research/
  2. Bruning, R. H., et. al. (2004). Cognitive psychology and instruction.4th ed. New Jersey: Prentice hall, pp 30-31.
  3. Chipperfield, B. (2006). Cognitive Load Theory and Instructional Design Saskatoon. Saskatchewan, Canada: University of Saskatchewan (USASK). Retrieved on November 7, 2006 from http://www.usask.ca/education/coursework/802papers/
    chipperfield/chipperfield.pdf
  4. Cooper, G. (1998). Research into Cognitive Load Theory and Instructional Design at UNSW. Sydney, Australia: University of New South Wales (UNSW). Retrieved on November 10, 2006 from http://education.arts.unsw.edu.au/staff/sweller/clt/index.html
  5. Clark, R. C., & Mayer,R. E. (2003). e-Learning and the science of instruction. Does Practice Make Perfect? In e-Learning and the Science of Instruction (pp. 149-171). San Francisco: Pfeiffer
  6. Kearsley, G. (2006). Cognitive Load theory (J. Sweller). Retrieved on November 15, 2006, from the Explorations in Learning & Instruction: The Theory into Practice Database Website: http://tip.psychology.org/sweller.html
  7. Miller, M. (2006). Cognitive Load Theory. San Diego, California: San Diego State University, Retrieved on November 7, 2006 from the Encyclopedia of Educational Technology Website: http://coe.sdsu.edu/eet/Articles/cogloadtheory/index.htm
  8. Ormrod, J. E., (1999). Human learning. New Jersey: Merrill Prentice Hall, pp. 150 – 154.
  9. UNSW (2006). Prof John Sweller. UNSW, Sydney, Australia: University of New South Wales (UNSW). Retrieved on November 30, 2006 from http://education.arts.unsw.edu.au/staff/staff.php?first=John&last=Sweller
  10. Van Gerven, Pascal W. M. (2003). The efficiency of multimedia learning into old age. British journal of educational psychology, 73 (4), 489-505.
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Credits

Theory
Ayres, P. (2006). UNSW, 2006. Cognitive load theory at UNSW. Sydney, Australia: University of New South Wales (UNSW). Retrieved on November 10, 2006 from http://education.arts.unsw.edu.au/research/ UNSW (2006). Prof John Sweller. UNSW, Sydney, Australia: University of New South Wales (UNSW). Retrieved on November 30, 2006 from http://education.arts.unsw.edu.au/staff/staff.php?first=John&last=Sweller Van Gerven, Pascal W. M. (2003). The efficiency of multimedia learning into old age. British journal of educational psychology, 73 (4), 489-505. Theorist
UNSW (2006). Prof John Sweller. UNSW, Sydney, Australia: University of New South Wales (UNSW). Retrieved on November 30, 2006 from http://education.arts.unsw.edu.au/staff/staff.php?first=John&last=Sweller
 

Development of Diagrammatic Representations

Diagram Design: Suhana Chikatla Diagrammatic representation: Idea used and modified from - Miller, M. (2006). Cognitive Load Theory. San Diego, California: San Diego State University, Retrieved on November 7, 2006 from the Encyclopedia of Educational Technology Website: http://coe.sdsu.edu/eet/Articles/cogloadtheory/index.htm

Terms and Definitions

    Chipperfield, B. (2006). Cognitive Load Theory and Instructional Design Saskatoon. Saskatchewan, Canada: University of Saskatchewan (USASK). Retrieved on November 7, 2006 from http://www.usask.ca/education/coursework/802papers/
    chipperfield/chipperfield.pdf
    Cooper, G. (1998). Research into Cognitive Load Theory and Instructional Design at UNSW. Sydney, Australia: University of New South Wales (UNSW). Retrieved on November 10, 2006 from http://education.arts.unsw.edu.au/staff/sweller/clt/index.html Miller, M. (2006). Cognitive Load Theory. San Diego, California: San Diego State University, Retrieved on November 7, 2006 from the Encyclopedia of Educational Technology Website: http://coe.sdsu.edu/eet/Articles/cogloadtheory/index.htm Van Gerven, Pascal W. M. (2003). The efficiency of multimedia learning into old age. British journal of educational psychology, 73 (4), 489-505.

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