SlideShare a Scribd company logo
1 of 20
Cognitive Load Theory
Wisconsin Mathematics Council Ignite session: May 3rd, 2017
www.dylanwiliamcenter.com
Dylan Wiliam (@dylanwiliam)
www.dylanwiliam.net
Kinds of knowledge: an evolutionary approach
Biologically primary knowledge
• Recognizing faces
• Recognizing speech
• General problem solving
• Learnable
Biologically secondary knowledge
• Reading
• Writing
• Mathematics
• Learnable
2
Geary (2007, 2008)
Countdown game
Target number: 127
25 3
9 4
1
A model of human memory
4
Long-term
memory
Short-term
memory
Environment
Limited Limitless
• The purpose of math instruction is to build domain-
specific mathematical knowledge—i.e., long-term
memory
5
Memory in chess
• Studies of memory in chess
– Djakow, Petrovskij, and Rudik (1927)
– Adriaan De Groot (1946)
– Chase and Simon (1973)
6
Memory in chess (1)
7 Random
Player level Number of pieces correctly placed
Novice 2
Club player 3
Expert 3
Mid-game
Player level Number of pieces correctly placed
Novice 5
Club player 9
Expert 16
Memory in chess (2)
8 End
game
Player level Number of pieces correctly placed
Novice 4
Club player 7
Expert 8
Attempts to simulate the performance of the expert chess
player with computers suggest that the expert can
recognize at least 10,000, but less than 100,000, different
arrangements of chess pieces or “chunks,” with a most
likely value around 13,500 (Simon & Gilmartin, 1973)
What is learning?
• Learning is “a change in long-term memory”
(Kirschner, Sweller, & Clark, 2016 p. 77)
• “The aim of all instruction is to alter long-term
memory. If nothing has changed in long-term
memory, nothing has been learned.” (ibid p. 77)
• “Novices need to use thinking skills. Experts use
knowledge” (Sweller et al., 2011 p. 21)
9
John Sweller
10
A mathematical problem
• Transform a given number to a target number using
just two mathematical operations:
– subtract 29
– multiply by 3
• For example
– Starting number: 27
– Target number: 1027
• Solution:
– x 3, — 29, x 3, — 29, x 3, — 29, x 3, — 29
11
The origins of cognitive load theory
• All the problems could be solved only in one way,
which involved alternating the two available
operations
• Students solved the problems
• But they did not notice the fact that all the
problems had similar solution strategies
• For novices, solving problems is not the best way to
get better at solving problems
12
Cognitive load theory
• Cognitive load
– Intrinsic
• “imposed by the basic structure of information being taught”
– Extraneous
• “imposed by the manner in which the information is presented
or the activities in which learners must engage”
• Levels of cognitive load are determined by element
interactivity
13
Element interactivity
14
High
Low Medium
Scalene
Isosceles
Equilateral
“Interacting elements are defined as elements that must be
processed simultaneously in working memory because they
are logically related” (Sweller, Ayres, & Kalyuga, 2011 p. 58)
Instructional design
• Good instruction minimizes both extraneous and
intrinsic cognitive load
– Extraneous cognitive load is reduced through good
instructional design
– Intrinsic cognitive load is reduced through good
instructional sequencing
15
The goal-free effect
• “When novices solve a conventional problem, they
will frequently work backwards from the goal to
the givens using a means–ends strategy.”
• “In contrast, experts, using schemas held in long-
term memory, know the solution and are more
likely to work forward from the givens to the goal.”
• “Working memory may be overwhelmed by a
means–ends strategy, reducing or even preventing
learning”
16
Worked-example/problem completion effects
• “Studying worked examples provides one of the
best, possibly the best, means of learning how to
solve problems in a novel domain.” (p. 107)
• Strategies
– Present worked example and ask students to solve a
similar problem
– Increase engagement by using completion problems
– Guidance fading: forwards is better than backwards
17
Split-attention effect
In the figure shown, find a value for ∠ DBE
Solution:
∠ ABC = 180° – ∠ BAC – ∠ BCA
= 180° – 45° – 55°
= 80°
∠ DBE = ∠ ABC (vertically opposite)
= 80°
18
A
B
D C
E
45°
55°
Sweller, Merrienboer and Paas (1998)
Integrated example with no split attention
19
A
B
D C
E
45°
55°
180° – 55° – 45°
= 80°
1
2
80°
Other important aspects
• Redundancy
• Modality effects
• Transient information effects
• Expertise reversal effect
• Collective working memory effects
20

More Related Content

Similar to 2017-05-03 WMC Ignite session.pptx

Personalizing the K-8 Math Experience: Increase Student Engagement and Achiev...
Personalizing the K-8 Math Experience: Increase Student Engagement and Achiev...Personalizing the K-8 Math Experience: Increase Student Engagement and Achiev...
Personalizing the K-8 Math Experience: Increase Student Engagement and Achiev...DreamBox Learning
 
Connect with Maths~ Teaching maths through problem solving
Connect with Maths~ Teaching maths through problem solvingConnect with Maths~ Teaching maths through problem solving
Connect with Maths~ Teaching maths through problem solvingRenee Hoareau
 
Guided Math Presentation
Guided Math PresentationGuided Math Presentation
Guided Math PresentationKeri Stoyle
 
Kdg mp and problem solving intro 8.28.12
Kdg mp and problem solving intro 8.28.12Kdg mp and problem solving intro 8.28.12
Kdg mp and problem solving intro 8.28.12Laura Chambless
 
Problem solving secondary
Problem solving   secondary Problem solving   secondary
Problem solving secondary Warren Brown
 
Problem solving cognitive psychology
Problem solving cognitive psychology Problem solving cognitive psychology
Problem solving cognitive psychology MashalFatima11
 
3rd Grade Webinar Slideshow
3rd Grade Webinar Slideshow3rd Grade Webinar Slideshow
3rd Grade Webinar Slideshowjwalts
 
Practicing the Mathematical Practices
Practicing the Mathematical PracticesPracticing the Mathematical Practices
Practicing the Mathematical PracticesNicole Rigelman
 
Effectively Differentiating Mathematics Instruction to Help Struggling Students
Effectively Differentiating Mathematics Instruction to Help Struggling StudentsEffectively Differentiating Mathematics Instruction to Help Struggling Students
Effectively Differentiating Mathematics Instruction to Help Struggling StudentsDreamBox Learning
 
Cubing thinkdotpp
Cubing thinkdotppCubing thinkdotpp
Cubing thinkdotpppimath
 
MoStep Six Presentation, By Sarah Cress
MoStep Six Presentation, By Sarah CressMoStep Six Presentation, By Sarah Cress
MoStep Six Presentation, By Sarah CressSarah Cress-Ackermann
 
Math Presentation
Math PresentationMath Presentation
Math PresentationSmart Ed
 
Mathpresentation 170503073857 (1)
Mathpresentation 170503073857 (1)Mathpresentation 170503073857 (1)
Mathpresentation 170503073857 (1)JohnReyLaureano
 
15min frogdesign
15min frogdesign15min frogdesign
15min frogdesignNRBLB
 
Module 2 Slides.ppt
Module 2 Slides.pptModule 2 Slides.ppt
Module 2 Slides.pptwondmhunegn
 
A Problem With Problem Solving Teaching Thinking Without Teaching Knowledge
A Problem With Problem Solving  Teaching Thinking Without Teaching KnowledgeA Problem With Problem Solving  Teaching Thinking Without Teaching Knowledge
A Problem With Problem Solving Teaching Thinking Without Teaching KnowledgeCheryl Brown
 

Similar to 2017-05-03 WMC Ignite session.pptx (20)

Nsw 2011 final amc
Nsw 2011 final amcNsw 2011 final amc
Nsw 2011 final amc
 
Personalizing the K-8 Math Experience: Increase Student Engagement and Achiev...
Personalizing the K-8 Math Experience: Increase Student Engagement and Achiev...Personalizing the K-8 Math Experience: Increase Student Engagement and Achiev...
Personalizing the K-8 Math Experience: Increase Student Engagement and Achiev...
 
Mathematicalprocess
MathematicalprocessMathematicalprocess
Mathematicalprocess
 
Connect with Maths~ Teaching maths through problem solving
Connect with Maths~ Teaching maths through problem solvingConnect with Maths~ Teaching maths through problem solving
Connect with Maths~ Teaching maths through problem solving
 
Guided Math Presentation
Guided Math PresentationGuided Math Presentation
Guided Math Presentation
 
Kdg mp and problem solving intro 8.28.12
Kdg mp and problem solving intro 8.28.12Kdg mp and problem solving intro 8.28.12
Kdg mp and problem solving intro 8.28.12
 
Problem solving secondary
Problem solving   secondary Problem solving   secondary
Problem solving secondary
 
Problem solving cognitive psychology
Problem solving cognitive psychology Problem solving cognitive psychology
Problem solving cognitive psychology
 
3rd Grade Webinar Slideshow
3rd Grade Webinar Slideshow3rd Grade Webinar Slideshow
3rd Grade Webinar Slideshow
 
Practicing the Mathematical Practices
Practicing the Mathematical PracticesPracticing the Mathematical Practices
Practicing the Mathematical Practices
 
Effectively Differentiating Mathematics Instruction to Help Struggling Students
Effectively Differentiating Mathematics Instruction to Help Struggling StudentsEffectively Differentiating Mathematics Instruction to Help Struggling Students
Effectively Differentiating Mathematics Instruction to Help Struggling Students
 
The Teaching of Mathematics
The Teaching of MathematicsThe Teaching of Mathematics
The Teaching of Mathematics
 
Cubing thinkdotpp
Cubing thinkdotppCubing thinkdotpp
Cubing thinkdotpp
 
Strategies that grow dendrites
Strategies that grow dendritesStrategies that grow dendrites
Strategies that grow dendrites
 
MoStep Six Presentation, By Sarah Cress
MoStep Six Presentation, By Sarah CressMoStep Six Presentation, By Sarah Cress
MoStep Six Presentation, By Sarah Cress
 
Math Presentation
Math PresentationMath Presentation
Math Presentation
 
Mathpresentation 170503073857 (1)
Mathpresentation 170503073857 (1)Mathpresentation 170503073857 (1)
Mathpresentation 170503073857 (1)
 
15min frogdesign
15min frogdesign15min frogdesign
15min frogdesign
 
Module 2 Slides.ppt
Module 2 Slides.pptModule 2 Slides.ppt
Module 2 Slides.ppt
 
A Problem With Problem Solving Teaching Thinking Without Teaching Knowledge
A Problem With Problem Solving  Teaching Thinking Without Teaching KnowledgeA Problem With Problem Solving  Teaching Thinking Without Teaching Knowledge
A Problem With Problem Solving Teaching Thinking Without Teaching Knowledge
 

Recently uploaded

When Quality Assurance Meets Innovation in Higher Education - Report launch w...
When Quality Assurance Meets Innovation in Higher Education - Report launch w...When Quality Assurance Meets Innovation in Higher Education - Report launch w...
When Quality Assurance Meets Innovation in Higher Education - Report launch w...Gary Wood
 
TỔNG HỢP HƠN 100 ĐỀ THI THỬ TỐT NGHIỆP THPT TOÁN 2024 - TỪ CÁC TRƯỜNG, TRƯỜNG...
TỔNG HỢP HƠN 100 ĐỀ THI THỬ TỐT NGHIỆP THPT TOÁN 2024 - TỪ CÁC TRƯỜNG, TRƯỜNG...TỔNG HỢP HƠN 100 ĐỀ THI THỬ TỐT NGHIỆP THPT TOÁN 2024 - TỪ CÁC TRƯỜNG, TRƯỜNG...
TỔNG HỢP HƠN 100 ĐỀ THI THỬ TỐT NGHIỆP THPT TOÁN 2024 - TỪ CÁC TRƯỜNG, TRƯỜNG...Nguyen Thanh Tu Collection
 
How To Create Editable Tree View in Odoo 17
How To Create Editable Tree View in Odoo 17How To Create Editable Tree View in Odoo 17
How To Create Editable Tree View in Odoo 17Celine George
 
The Story of Village Palampur Class 9 Free Study Material PDF
The Story of Village Palampur Class 9 Free Study Material PDFThe Story of Village Palampur Class 9 Free Study Material PDF
The Story of Village Palampur Class 9 Free Study Material PDFVivekanand Anglo Vedic Academy
 
Personalisation of Education by AI and Big Data - Lourdes Guàrdia
Personalisation of Education by AI and Big Data - Lourdes GuàrdiaPersonalisation of Education by AI and Big Data - Lourdes Guàrdia
Personalisation of Education by AI and Big Data - Lourdes GuàrdiaEADTU
 
會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文
會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文
會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文中 央社
 
DEMONSTRATION LESSON IN ENGLISH 4 MATATAG CURRICULUM
DEMONSTRATION LESSON IN ENGLISH 4 MATATAG CURRICULUMDEMONSTRATION LESSON IN ENGLISH 4 MATATAG CURRICULUM
DEMONSTRATION LESSON IN ENGLISH 4 MATATAG CURRICULUMELOISARIVERA8
 
Analyzing and resolving a communication crisis in Dhaka textiles LTD.pptx
Analyzing and resolving a communication crisis in Dhaka textiles LTD.pptxAnalyzing and resolving a communication crisis in Dhaka textiles LTD.pptx
Analyzing and resolving a communication crisis in Dhaka textiles LTD.pptxLimon Prince
 
OSCM Unit 2_Operations Processes & Systems
OSCM Unit 2_Operations Processes & SystemsOSCM Unit 2_Operations Processes & Systems
OSCM Unit 2_Operations Processes & SystemsSandeep D Chaudhary
 
diagnosting testing bsc 2nd sem.pptx....
diagnosting testing bsc 2nd sem.pptx....diagnosting testing bsc 2nd sem.pptx....
diagnosting testing bsc 2nd sem.pptx....Ritu480198
 
Improved Approval Flow in Odoo 17 Studio App
Improved Approval Flow in Odoo 17 Studio AppImproved Approval Flow in Odoo 17 Studio App
Improved Approval Flow in Odoo 17 Studio AppCeline George
 
Sternal Fractures & Dislocations - EMGuidewire Radiology Reading Room
Sternal Fractures & Dislocations - EMGuidewire Radiology Reading RoomSternal Fractures & Dislocations - EMGuidewire Radiology Reading Room
Sternal Fractures & Dislocations - EMGuidewire Radiology Reading RoomSean M. Fox
 
Rich Dad Poor Dad ( PDFDrive.com )--.pdf
Rich Dad Poor Dad ( PDFDrive.com )--.pdfRich Dad Poor Dad ( PDFDrive.com )--.pdf
Rich Dad Poor Dad ( PDFDrive.com )--.pdfJerry Chew
 
會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽
會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽
會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽中 央社
 
Stl Algorithms in C++ jjjjjjjjjjjjjjjjjj
Stl Algorithms in C++ jjjjjjjjjjjjjjjjjjStl Algorithms in C++ jjjjjjjjjjjjjjjjjj
Stl Algorithms in C++ jjjjjjjjjjjjjjjjjjMohammed Sikander
 
The Liver & Gallbladder (Anatomy & Physiology).pptx
The Liver &  Gallbladder (Anatomy & Physiology).pptxThe Liver &  Gallbladder (Anatomy & Physiology).pptx
The Liver & Gallbladder (Anatomy & Physiology).pptxVishal Singh
 

Recently uploaded (20)

When Quality Assurance Meets Innovation in Higher Education - Report launch w...
When Quality Assurance Meets Innovation in Higher Education - Report launch w...When Quality Assurance Meets Innovation in Higher Education - Report launch w...
When Quality Assurance Meets Innovation in Higher Education - Report launch w...
 
TỔNG HỢP HƠN 100 ĐỀ THI THỬ TỐT NGHIỆP THPT TOÁN 2024 - TỪ CÁC TRƯỜNG, TRƯỜNG...
TỔNG HỢP HƠN 100 ĐỀ THI THỬ TỐT NGHIỆP THPT TOÁN 2024 - TỪ CÁC TRƯỜNG, TRƯỜNG...TỔNG HỢP HƠN 100 ĐỀ THI THỬ TỐT NGHIỆP THPT TOÁN 2024 - TỪ CÁC TRƯỜNG, TRƯỜNG...
TỔNG HỢP HƠN 100 ĐỀ THI THỬ TỐT NGHIỆP THPT TOÁN 2024 - TỪ CÁC TRƯỜNG, TRƯỜNG...
 
How To Create Editable Tree View in Odoo 17
How To Create Editable Tree View in Odoo 17How To Create Editable Tree View in Odoo 17
How To Create Editable Tree View in Odoo 17
 
The Story of Village Palampur Class 9 Free Study Material PDF
The Story of Village Palampur Class 9 Free Study Material PDFThe Story of Village Palampur Class 9 Free Study Material PDF
The Story of Village Palampur Class 9 Free Study Material PDF
 
Personalisation of Education by AI and Big Data - Lourdes Guàrdia
Personalisation of Education by AI and Big Data - Lourdes GuàrdiaPersonalisation of Education by AI and Big Data - Lourdes Guàrdia
Personalisation of Education by AI and Big Data - Lourdes Guàrdia
 
VAMOS CUIDAR DO NOSSO PLANETA! .
VAMOS CUIDAR DO NOSSO PLANETA!                    .VAMOS CUIDAR DO NOSSO PLANETA!                    .
VAMOS CUIDAR DO NOSSO PLANETA! .
 
會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文
會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文
會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文
 
DEMONSTRATION LESSON IN ENGLISH 4 MATATAG CURRICULUM
DEMONSTRATION LESSON IN ENGLISH 4 MATATAG CURRICULUMDEMONSTRATION LESSON IN ENGLISH 4 MATATAG CURRICULUM
DEMONSTRATION LESSON IN ENGLISH 4 MATATAG CURRICULUM
 
Mattingly "AI & Prompt Design: Named Entity Recognition"
Mattingly "AI & Prompt Design: Named Entity Recognition"Mattingly "AI & Prompt Design: Named Entity Recognition"
Mattingly "AI & Prompt Design: Named Entity Recognition"
 
Analyzing and resolving a communication crisis in Dhaka textiles LTD.pptx
Analyzing and resolving a communication crisis in Dhaka textiles LTD.pptxAnalyzing and resolving a communication crisis in Dhaka textiles LTD.pptx
Analyzing and resolving a communication crisis in Dhaka textiles LTD.pptx
 
OSCM Unit 2_Operations Processes & Systems
OSCM Unit 2_Operations Processes & SystemsOSCM Unit 2_Operations Processes & Systems
OSCM Unit 2_Operations Processes & Systems
 
Supporting Newcomer Multilingual Learners
Supporting Newcomer  Multilingual LearnersSupporting Newcomer  Multilingual Learners
Supporting Newcomer Multilingual Learners
 
diagnosting testing bsc 2nd sem.pptx....
diagnosting testing bsc 2nd sem.pptx....diagnosting testing bsc 2nd sem.pptx....
diagnosting testing bsc 2nd sem.pptx....
 
Improved Approval Flow in Odoo 17 Studio App
Improved Approval Flow in Odoo 17 Studio AppImproved Approval Flow in Odoo 17 Studio App
Improved Approval Flow in Odoo 17 Studio App
 
Mattingly "AI and Prompt Design: LLMs with NER"
Mattingly "AI and Prompt Design: LLMs with NER"Mattingly "AI and Prompt Design: LLMs with NER"
Mattingly "AI and Prompt Design: LLMs with NER"
 
Sternal Fractures & Dislocations - EMGuidewire Radiology Reading Room
Sternal Fractures & Dislocations - EMGuidewire Radiology Reading RoomSternal Fractures & Dislocations - EMGuidewire Radiology Reading Room
Sternal Fractures & Dislocations - EMGuidewire Radiology Reading Room
 
Rich Dad Poor Dad ( PDFDrive.com )--.pdf
Rich Dad Poor Dad ( PDFDrive.com )--.pdfRich Dad Poor Dad ( PDFDrive.com )--.pdf
Rich Dad Poor Dad ( PDFDrive.com )--.pdf
 
會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽
會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽
會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽會考英聽
 
Stl Algorithms in C++ jjjjjjjjjjjjjjjjjj
Stl Algorithms in C++ jjjjjjjjjjjjjjjjjjStl Algorithms in C++ jjjjjjjjjjjjjjjjjj
Stl Algorithms in C++ jjjjjjjjjjjjjjjjjj
 
The Liver & Gallbladder (Anatomy & Physiology).pptx
The Liver &  Gallbladder (Anatomy & Physiology).pptxThe Liver &  Gallbladder (Anatomy & Physiology).pptx
The Liver & Gallbladder (Anatomy & Physiology).pptx
 

2017-05-03 WMC Ignite session.pptx

  • 1. Cognitive Load Theory Wisconsin Mathematics Council Ignite session: May 3rd, 2017 www.dylanwiliamcenter.com Dylan Wiliam (@dylanwiliam) www.dylanwiliam.net
  • 2. Kinds of knowledge: an evolutionary approach Biologically primary knowledge • Recognizing faces • Recognizing speech • General problem solving • Learnable Biologically secondary knowledge • Reading • Writing • Mathematics • Learnable 2 Geary (2007, 2008)
  • 4. A model of human memory 4 Long-term memory Short-term memory Environment Limited Limitless
  • 5. • The purpose of math instruction is to build domain- specific mathematical knowledge—i.e., long-term memory 5
  • 6. Memory in chess • Studies of memory in chess – Djakow, Petrovskij, and Rudik (1927) – Adriaan De Groot (1946) – Chase and Simon (1973) 6
  • 7. Memory in chess (1) 7 Random Player level Number of pieces correctly placed Novice 2 Club player 3 Expert 3 Mid-game Player level Number of pieces correctly placed Novice 5 Club player 9 Expert 16
  • 8. Memory in chess (2) 8 End game Player level Number of pieces correctly placed Novice 4 Club player 7 Expert 8 Attempts to simulate the performance of the expert chess player with computers suggest that the expert can recognize at least 10,000, but less than 100,000, different arrangements of chess pieces or “chunks,” with a most likely value around 13,500 (Simon & Gilmartin, 1973)
  • 9. What is learning? • Learning is “a change in long-term memory” (Kirschner, Sweller, & Clark, 2016 p. 77) • “The aim of all instruction is to alter long-term memory. If nothing has changed in long-term memory, nothing has been learned.” (ibid p. 77) • “Novices need to use thinking skills. Experts use knowledge” (Sweller et al., 2011 p. 21) 9
  • 11. A mathematical problem • Transform a given number to a target number using just two mathematical operations: – subtract 29 – multiply by 3 • For example – Starting number: 27 – Target number: 1027 • Solution: – x 3, — 29, x 3, — 29, x 3, — 29, x 3, — 29 11
  • 12. The origins of cognitive load theory • All the problems could be solved only in one way, which involved alternating the two available operations • Students solved the problems • But they did not notice the fact that all the problems had similar solution strategies • For novices, solving problems is not the best way to get better at solving problems 12
  • 13. Cognitive load theory • Cognitive load – Intrinsic • “imposed by the basic structure of information being taught” – Extraneous • “imposed by the manner in which the information is presented or the activities in which learners must engage” • Levels of cognitive load are determined by element interactivity 13
  • 14. Element interactivity 14 High Low Medium Scalene Isosceles Equilateral “Interacting elements are defined as elements that must be processed simultaneously in working memory because they are logically related” (Sweller, Ayres, & Kalyuga, 2011 p. 58)
  • 15. Instructional design • Good instruction minimizes both extraneous and intrinsic cognitive load – Extraneous cognitive load is reduced through good instructional design – Intrinsic cognitive load is reduced through good instructional sequencing 15
  • 16. The goal-free effect • “When novices solve a conventional problem, they will frequently work backwards from the goal to the givens using a means–ends strategy.” • “In contrast, experts, using schemas held in long- term memory, know the solution and are more likely to work forward from the givens to the goal.” • “Working memory may be overwhelmed by a means–ends strategy, reducing or even preventing learning” 16
  • 17. Worked-example/problem completion effects • “Studying worked examples provides one of the best, possibly the best, means of learning how to solve problems in a novel domain.” (p. 107) • Strategies – Present worked example and ask students to solve a similar problem – Increase engagement by using completion problems – Guidance fading: forwards is better than backwards 17
  • 18. Split-attention effect In the figure shown, find a value for ∠ DBE Solution: ∠ ABC = 180° – ∠ BAC – ∠ BCA = 180° – 45° – 55° = 80° ∠ DBE = ∠ ABC (vertically opposite) = 80° 18 A B D C E 45° 55° Sweller, Merrienboer and Paas (1998)
  • 19. Integrated example with no split attention 19 A B D C E 45° 55° 180° – 55° – 45° = 80° 1 2 80°
  • 20. Other important aspects • Redundancy • Modality effects • Transient information effects • Expertise reversal effect • Collective working memory effects 20