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Human cognitive architecture and its implications for the design of instruction: Introduction to cognitive load theory Slava Kayuga

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Page 1: Human cognitive architecture and its implications for the design of instruction: Introduction to cognitive load theory Slava Kayuga

Human cognitive architecture and its implications for the design of instruction: Introduction to cognitive load theory

Slava Kayuga

Page 2: Human cognitive architecture and its implications for the design of instruction: Introduction to cognitive load theory Slava Kayuga

Constructing mental representations of a situation or task

Long-Term Memory Knowledge base

Working Memory

Sensory Memory: Incoming information

Page 3: Human cognitive architecture and its implications for the design of instruction: Introduction to cognitive load theory Slava Kayuga

Working memory (WM)

Information enters WM once it has been selected by allocating attention to it

We have limited attention because of limitations of WM

Corresponds to consciousness or awareness: we are conscious of everything that is in WM

Page 4: Human cognitive architecture and its implications for the design of instruction: Introduction to cognitive load theory Slava Kayuga

Repeat a telephone number

12 + 13 = ?

83468437 + 93849045 = ?

Working Memory

Taking notes – extension of WM

What have you been doing just before this?

Page 5: Human cognitive architecture and its implications for the design of instruction: Introduction to cognitive load theory Slava Kayuga

Early models of memory referred to STM; it

is still commonly used today

STM was thought of in terms of only storing information (temporarily remembering)

Baddeley and Hitch (1974): we not only store information for short periods of time but also process information - hence WM

Short-term or working memory?

Page 6: Human cognitive architecture and its implications for the design of instruction: Introduction to cognitive load theory Slava Kayuga

WM capacity

Miller (1956) demonstrated that we have a short-term memory span of 7 ± 2 units of information – storage capacity

Reconsideration of WM capacity when processing is involved (Cowan, 2001)

In terms of processing information, 4 is a more likely number than 7

Page 7: Human cognitive architecture and its implications for the design of instruction: Introduction to cognitive load theory Slava Kayuga

Suppose 5 days after the day before yesterday is Friday. What day of the week is tomorrow?

WM processing capacity

Page 8: Human cognitive architecture and its implications for the design of instruction: Introduction to cognitive load theory Slava Kayuga

WM duration

Brown (1958); Peterson & Peterson (1959):

When people are distracted from rehearsing, information is lost rapidly (e.g., after 18 sec – everything was forgotten)

Page 9: Human cognitive architecture and its implications for the design of instruction: Introduction to cognitive load theory Slava Kayuga

Allocates resources to other systems- governs what enters WM

Director of cognitive work- selects strategies

Not a store or processor

Executive Control SystemControls the Operations of

Working Memory

Phonological LoopAuditory Rehearsal

WM StructureBaddeley 1986, 2001

Visual-spatial Sketch PadVisual Rehearsal

Processes visual images Spatial processing

Holds acoustic or speech-based information

Auditory rehearsal of verbal information

Page 10: Human cognitive architecture and its implications for the design of instruction: Introduction to cognitive load theory Slava Kayuga

Close your eyes and pick up an object in front of you

How many windows are in your house?

Working Memory

Repeat an unfamiliar foreign word

Page 11: Human cognitive architecture and its implications for the design of instruction: Introduction to cognitive load theory Slava Kayuga

Long-term memory (LTM)

permanent repository of the lifetime of accumulated information

unconscious component of our memory: we are not conscious of LTM information until it is activated and brought into WM

WM and LTM are two major components of Human cognitive architecture

Page 12: Human cognitive architecture and its implications for the design of instruction: Introduction to cognitive load theory Slava Kayuga

CIABBCABCBHPAMP

CIA BBC ABC BHP AMP

Role of LTM

Page 13: Human cognitive architecture and its implications for the design of instruction: Introduction to cognitive load theory Slava Kayuga

Effective WM capacity

Miller (1956): short-term memory span is 7 ± 2 chunks of information

What each chunk consists is dependent on our knowledge stored in LTM

What is in LTM would affect the way we process information in WM

Page 14: Human cognitive architecture and its implications for the design of instruction: Introduction to cognitive load theory Slava Kayuga

Information-“rich” chunks

Chunking information into meaningful parts has the effect of expanding the capacity of working memory

Examples: a Chinese character; a written English word; newspaper vs textbook

Effective WM capacity

Page 15: Human cognitive architecture and its implications for the design of instruction: Introduction to cognitive load theory Slava Kayuga

Chess studies

Compared performance of chess masters and weekend players

Question: Do chess masters look ahead more moves? Consider a greater number of

alternative moves?

Answer: verbal protocols showed NO difference between chess masters and weekend players

de Groot (1966)

Page 16: Human cognitive architecture and its implications for the design of instruction: Introduction to cognitive load theory Slava Kayuga

Investigated: players’ memory of chess boards Tested: master’s vs. weekend player’s memory for real

and random board configurations after brief (5 sec) exposure

Results: masters were superior in reconstructing real game configurations (80-90% correct compared to weekenders’ 30-40%) but NOT random configurations

Conclusion: Superiority was due to greater amount of real-game chunks in master’s LTM

Chess studiesde Groot (1966); Chase & Simon (1973)

Page 17: Human cognitive architecture and its implications for the design of instruction: Introduction to cognitive load theory Slava Kayuga

Grand masters have extensive and better organized LTM knowledge base

50-100 thousand configurations, at least 10 years of experience

This study radically changed our view on the role of LTM in human cognition

LTM is not just for memorizing things, but is the most critical component of our cognition (including learning), the source of our intellectual strength

Role of LTM

Page 18: Human cognitive architecture and its implications for the design of instruction: Introduction to cognitive load theory Slava Kayuga

Grand masters read the chess board the same way you read words in a text

Similar mechanisms for all high-level cognitive skills (e.g., text comprehension)

LTM - not a passive store of information; it is actively used in most of cognitive processes and is central to perception, learning, problem solving

LTM in human cognition

Page 19: Human cognitive architecture and its implications for the design of instruction: Introduction to cognitive load theory Slava Kayuga

“Organized structures that capture knowledge and expectations of some aspect of the world” (Bartlett, 1932)

Organized knowledge structures that represent generic concepts and categorize information according to the way in which we use it

Schemas (schemata)

Page 20: Human cognitive architecture and its implications for the design of instruction: Introduction to cognitive load theory Slava Kayuga

table toastchair butterknife jamfork clothspoon juicecup bowlplate tea

What is this list about?

Page 21: Human cognitive architecture and its implications for the design of instruction: Introduction to cognitive load theory Slava Kayuga

Schemas

Examples:

a tree schemaa face schema

reading a page of prose: schemas for letters, words, phrases, sentence structures

Restaurant script (procedural schema)

Page 22: Human cognitive architecture and its implications for the design of instruction: Introduction to cognitive load theory Slava Kayuga

Schema theory is the most commonly used framework for understanding LTM

Memory is actively constructed using schemas

Pre-existing schemas determine what incoming material is relevant Relevant material processed Irrelevant material discarded

Schemas as major building blocks of cognition

Page 23: Human cognitive architecture and its implications for the design of instruction: Introduction to cognitive load theory Slava Kayuga
Page 24: Human cognitive architecture and its implications for the design of instruction: Introduction to cognitive load theory Slava Kayuga

Schema automation

Schema automation is achieved by practicing skills until they do not require consciously controlled and effortful processing.

When basic mental operations occur automatically, resources are available for more sophisticated cognitive operations (e.g., reading, math operations, etc.)

Page 25: Human cognitive architecture and its implications for the design of instruction: Introduction to cognitive load theory Slava Kayuga

Automation

Explains why individuals can conduct difficult tasks simultaneously conduct several tasks read for meaning rather than focus on

the individual letters and words be accomplished performers (e.g.,

musicians) Automation is slow to develop and

requires significant practice

Page 26: Human cognitive architecture and its implications for the design of instruction: Introduction to cognitive load theory Slava Kayuga

Schemas

Schemas affect not only what we memorize, but how we think, reason, solve problems

Intelligence – in number and complexity of acquired schemas

Nature of expertise

Page 27: Human cognitive architecture and its implications for the design of instruction: Introduction to cognitive load theory Slava Kayuga

Expert characteristics: Domain-specific knowledge

Experts have a large store of domain-specific schemas for problem solving in the domain

Automated schemas reduce WM demands and allow higher order functions (monitoring, evaluating etc.)

Experts deal with problems at a deeper level: categorize according to deep structures (principles) rather than surface structures

Page 28: Human cognitive architecture and its implications for the design of instruction: Introduction to cognitive load theory Slava Kayuga

Expert characteristics: Treatment of problem

Task: categorize the following into 3 groups

Soldiers, 1492, discovery, kings & queens, 1914, revolution, sailors, war, 1789.

Surface structure grouping: 1492, 1914, 1789 Deep structure grouping: 1789, Kings and Queens, revolution (French Revolution)

Physics experts classified problems according to the laws of physics rather than surface structures (e.g. Chi, Glaser & Farr, 1988)

Page 29: Human cognitive architecture and its implications for the design of instruction: Introduction to cognitive load theory Slava Kayuga

Implications for improving problem solving Acquisition of extensive domain-specific

knowledge (schemas) is essential: the only way to be good in problem solving broken car: we call a mechanic (an expert), not

a general “problem solver” You can become expert problem solver in a

specific area, not in every area Studying expert solutions

emphasising higher-order skills, categorization of problems

Page 30: Human cognitive architecture and its implications for the design of instruction: Introduction to cognitive load theory Slava Kayuga

Analysis of the task domain to identify core schemas:

After 6 passengers had left the bus, 9 passengers remained. How many passengers were on the bus initially? (Change Schema)

Peter's book contains 50 pages. Peter read 15 pages in the morning. In the afternoon, he read the remaining pages and finished the book. How many pages did Peter read in the afternoon? (Group Schema) etc.

Arithmetic word problems(Marshall, 1995)

Page 31: Human cognitive architecture and its implications for the design of instruction: Introduction to cognitive load theory Slava Kayuga
Page 32: Human cognitive architecture and its implications for the design of instruction: Introduction to cognitive load theory Slava Kayuga

Go Solve Word ProblemsTom Snyder Productions

Page 33: Human cognitive architecture and its implications for the design of instruction: Introduction to cognitive load theory Slava Kayuga

Do not overload WM! If material is difficult to learn, learner WM is likely to be overloaded

Manage information-processing “bottleneck” by chunking information into meaningful groups based on available knowledge

Help students to link new information with prior knowledge

Instructional implications

Page 34: Human cognitive architecture and its implications for the design of instruction: Introduction to cognitive load theory Slava Kayuga

Enhance acquisition and automation of knowledge in LTM - a major goal

Use dual modality (visual and auditory)

Minimise interference /distractions

Provide adequate time to enable processing

Instruction that requires many inferences (things are not stated explicitly) overloads WM

Instructional implications

Page 35: Human cognitive architecture and its implications for the design of instruction: Introduction to cognitive load theory Slava Kayuga

Instructional theory that takes into account limitations of learner working memory

Cognitive load (working memory load): working memory capacity required by a particular cognitive task

Cognitive load depends on the level of interactivity between elements of information

Cognitive Load Theory

Sweller 1999; Sweller, Ayres & Kalyuga, 2011

Page 36: Human cognitive architecture and its implications for the design of instruction: Introduction to cognitive load theory Slava Kayuga

List of variables:a, x, b

Equation: ax=b

Names of electricalsymbols and what they represent

Operation of an electrical circuit

Low High

Element interactivity

Learning vocabulary of a foreign language

Learning grammar

Page 37: Human cognitive architecture and its implications for the design of instruction: Introduction to cognitive load theory Slava Kayuga

Objective measures Task and performance Secondary task Psychophysiological

Subjective measures Rating scales

Measurement of Cognitive Load

Page 38: Human cognitive architecture and its implications for the design of instruction: Introduction to cognitive load theory Slava Kayuga

Objective measures

Secondary task

Rapid RT Slow RT

Cognitive resources to simple primary task

Cognitive resources to complex primary task

Fixed cognitive capacity Fixed cognitive capacity

Resources to secondary task

Resources to secondary task

Page 39: Human cognitive architecture and its implications for the design of instruction: Introduction to cognitive load theory Slava Kayuga

very, very low mental

effort

very, very high mental

effort

neither low nor high

mental effort

In solving or studying the preceding problem I invested:

Subjective measures Rating scales

Page 40: Human cognitive architecture and its implications for the design of instruction: Introduction to cognitive load theory Slava Kayuga
Page 41: Human cognitive architecture and its implications for the design of instruction: Introduction to cognitive load theory Slava Kayuga

Subjective measures: Rating scales (NASA-

TLX)

Page 42: Human cognitive architecture and its implications for the design of instruction: Introduction to cognitive load theory Slava Kayuga

Useful, productive load (intrinsic load) – relevant to achieving learning goals

determined by the degree of element interactivity depends on specific instructional goals and prior

knowledge of the learner (chunking!)Wasteful, unproductive load (extraneous load) - irrelevant to learning, imposed by the manner in which information is presented to learners and the learning activities required of them

dependent on the design of instruction

Intrinsic + Extraneous =Total cognitive load

Types of cognitive load

Page 43: Human cognitive architecture and its implications for the design of instruction: Introduction to cognitive load theory Slava Kayuga

Efficient learningManaging intrinsic (productive) load

Reducing extraneous (wasteful) cognitive load

General rule: Do not do anything that gets in the way of learning!

If intrinsic load is low (simple tasks), there could be no need to reduce extraneous load

Page 44: Human cognitive architecture and its implications for the design of instruction: Introduction to cognitive load theory Slava Kayuga

References

Sweller, J., van Merriënboer, J. J. G., & Paas, F. G. W. C. (1998). Cognitive architecture and instructional design. Educational Psychology Review, 10, 251-296.

Van Merriënboer, J. J. G., & Sweller, J. (2005). Cognitive load theory and complex learning: Recent developments and future directions. Educational Psychology Review, 17, 147-177.