When is Too Much Not Enough - James Madison University · When is Too Much Not Enough? Using...

JMU CFI May Symposium 2017 Dr. Michael S. Kirkpatrick

When is Too Much Not Enough? Using Cognitive Theories of Learning to Shape Instructional Choices

Michael S. Kirkpatrick May 10, 2017


What is “learning?”


EinstellungA B C Target

Sample 29 3 20

Einstellung 1 21 127 3 100





Critical 1 23 49 3 20

Critical 2 15 39 3 18

Critical 3 18 48 4 22

Critical 4 14 36 8 6

Solution Explanation: 29 - 3 - 3 - 3 = 20

Experimental Solution: B - A - C - C = Target

J.D. Bransford et al., How People Learn: Brain, Mind, Experience, and School. National Academy Press. 2000. https://www.nap.edu/catalog/9853/how-people-learn-brain-mind-experience-and-school-expanded-edition

127-21-3-3163-14-25-25

43-18-10-10

42-9-6-6

59-20-4-4

49-23-3-339-15-3-3

48-18-4-4

36-14-8-8

https://www.nap.edu/catalog/9853/how-people-learn-brain-mind-experience-and-school-expanded-edition


EinstellungA B C Target

Sample 29 3 20






Critical 1 23 49 3 20

Critical 2 15 39 3 18

Critical 3 18 48 4 22

Critical 4 14 36 8 6

Einstellung Solution: 49 - 23 - 3 - 3 = 20

Direct Solution: 23 - 3 = 20




EinstellungEinstellung (percent)

Direct (percent)

No solution (percent)

Control (children) 1 89 10

Experimental (children) 72 24 4

Control (adults) 0 100 0

Experimental (adults) 74 26 0




Branches of Educational Psychology

Behavioral (Skinner)

Cognitive (Bjork, Sweller)

Constructivism (Vygotsky, Bruner)

Developmental (Piaget)


Learning is…

Change

Knowledge

Attitudes

Abilities

Area of inquiry

Factual knowledge

Context

Retrieval

ApplicationMetacognition

ProgressPractice

Feedback


Learning is…misunderstood

Common myths about learning: • Good learning makes us feeling confident and clear. • Learning is aware and purposeful. • Getting emotional interferes with learning. • You have to be interested to learn. • Intelligent people learn more easily. • Learning style adaptations are helpful. • Rereading texts is helpful. • Learning is learning.

M. Pasupathi, How We Learn. The Great Courses. Chantilly, VA, USA: The Teaching Company, 2012. P. Brown, H. Roediger, and M. McDaniel, Make It Stick : The Science of Successful Learning. Cambridge, MA, USA: Harvard University Press, 2014.


In-class Physics Demos

The evidence supporting active learning suggests that passive engagement with information can contribute to reinforcing misconceptions. One study examined how effective in-class physics demonstrations were in helping to understand concepts. All students began with a reading assignment. Some students then took part in an in-class demonstration; the control group did not observe or take part in a demonstration. The students completed a short test to conclude the experiment. Which group did the worst on the post-test, missing the most points?


In-class Physics Demos

Which group did the worst on the post-test, missing the most points? (A) Students who did not observe a demo (control group) (B) Students who only observed the demo (C) Students who predicted the outcome before it occurred by

writing down a guess (D) Students who discussed the outcome with peers after

observing what occurred

E. Mazur, Keynote address at ICER 2011. https://computinged.wordpress.com/2011/08/17/eric-mazurs-keynote-at-icer-2011-observing-demos-hurts-learning-and-confusion-is-a-sign-of-understanding/

http://www.physics.indiana.edu/~sdi/ajpv3i.pdf


Knowledge and human cognitive architecture


Types of KnowledgeBiologically Secondary

Biologically Primary

✓ ✕✓✕


Retrieval Fluency

34 HOW PEOPLE LEARN, EXPANDED EDITION

BOX 2.1 What Experts See

FIGURE 2.1 Chess boardpositions used in memoryexperiments. SOURCE:Adapted from Chase andSimon (1973).

Copyright © National Academy of Sciences. All rights reserved.


HOW EXPERTS DIFFER FROM NOVICES 35

In one study, a chess master, a Class A player (good but not a master), anda novice were given 5 seconds to view a chess board position from themiddle of a chess game; see Figure 2.1. After 5 seconds the board wascovered, and each participant attempted to reconstruct the board positionon another board. This procedure was repeated for multiple trials untileveryone received a perfect score. On the first trial, the master playercorrectly placed many more pieces than the Class A player, who in turnplaced more than the novice: 16, 8, and 4, respectively.

However, these results occurred only when the chess pieces werearranged in configurations that conformed to meaningful games of chess.When chess pieces were randomized and presented for 5 seconds, therecall of the chess master and Class A player were the same as the nov-ice—they placed from 2 to 3 positions correctly. Data over trials for validand random middle games are shown in Figure 2.2.

FIGURE 2.2 Recall by chessplayers by level of expertise.

25

20

15

10

5

01 2 3 4 5 6 7

Trial

Pie

ces

corr

ect

ly r

eca

lled

MasterClass A playerBeginner



the expert teachers had very different understandings of the events theywere watching than did the novice teachers; see examples in Box 2.2.

The idea that experts recognize features and patterns that are not no-ticed by novices is potentially important for improving instruction. Whenviewing instructional texts, slides, and videotapes, for example, the informa-tion noticed by novices can be quite different from what is noticed by ex-perts (e.g., Sabers et al., 1991; Bransford et al., 1988). One dimension ofacquiring greater competence appears to be the increased ability to segmentthe perceptual field (learning how to see). Research on expertise suggeststhe importance of providing students with learning experiences that specifi-cally enhance their abilities to recognize meaningful patterns of information(e.g., Simon, 1980; Bransford et al., 1989).

ORGANIZATION OF KNOWLEDGEWe turn now to the question of how experts’ knowledge is organized

and how this affects their abilities to understand and represent problems.Their knowledge is not simply a list of facts and formulas that are relevant totheir domain; instead, their knowledge is organized around core concepts or“big ideas” that guide their thinking about their domains.

FIGURE 2.3 Recall for numbers andchess pieces. SOURCE: Adaptedfrom Chi (1978).

10

5

0Randomnumbers

Chesspieces

Children with chessexperiences

Adults without chessexperiences

Item

s re

calle

d (N

umbe

r)



the expert teachers had very different understandings of the events theywere watching than did the novice teachers; see examples in Box 2.2.

The idea that experts recognize features and patterns that are not no-ticed by novices is potentially important for improving instruction. Whenviewing instructional texts, slides, and videotapes, for example, the informa-tion noticed by novices can be quite different from what is noticed by ex-perts (e.g., Sabers et al., 1991; Bransford et al., 1988). One dimension ofacquiring greater competence appears to be the increased ability to segmentthe perceptual field (learning how to see). Research on expertise suggeststhe importance of providing students with learning experiences that specifi-cally enhance their abilities to recognize meaningful patterns of information(e.g., Simon, 1980; Bransford et al., 1989).

ORGANIZATION OF KNOWLEDGEWe turn now to the question of how experts’ knowledge is organized

and how this affects their abilities to understand and represent problems.Their knowledge is not simply a list of facts and formulas that are relevant totheir domain; instead, their knowledge is organized around core concepts or“big ideas” that guide their thinking about their domains.

FIGURE 2.3 Recall for numbers andchess pieces. SOURCE: Adaptedfrom Chi (1978).

10

5

0Randomnumbers

Chesspieces

Children with chessexperiences

Adults without chessexperiences

Item

s re

calle

d (N

umbe

r)



BOX 2.1 What Experts See

FIGURE 2.1 Chess boardpositions used in memoryexperiments. SOURCE:Adapted from Chase andSimon (1973).



2017 May CFI Symposium JMU Dr. Sanjay Gupta is Cool

90 ft

90 ft x

Apply the Pythagorean theorem to the above triangle to find the value of x.

In a baseball diamond, the distance between each base is 90 ft. Which of the following is true about the shortest distance between 1st and 3rd bases (the red line shown above)? 1. It is less than 90 ft. 2. It is between 90 and 180 ft. 3. It is greater than 180 ft.

90 ft 90 ft

90 ft 90 ft

Far transfer


Memory Architecture


Human Cognitive Architecture

Information store

Borrowing/ reorganizing

Randomness as genesis

Narrow limits of change

Environmental linking

Working memory

Long-term memory

Amassing Acquiring

Interaction

WM Capacity: 4-7 items (2-3 novel) 20 seconds maximum

Central executive

Auditory loop

Visual- spatial


Key findings

What works: • Deliberative effort • Interleaved and spaced

practice • Try to solve problem before

being taught • Testing as calibration • Pre-learning foundation • Elaborative encoding

What doesn’t: • Massed practice • Rereading texts • Learning style adaptations • Intuitive judgments

P. Brown, H. Roediger, and M. McDaniel, Make It Stick : The Science of Successful Learning. Cambridge, MA, USA: Harvard University Press, 2014.


Cognitive load theory and its effects


Cognitive Load Theory

High Intrinsic

Load

Low Intrinsic

Load

Extraneous Load

Germane Load

Goal-free effect

Modality effect

Worked example effect

Imagination effect

A

BC D

E

Variability effect

Transient info effect

Redundancy effect


In a baseball diamond, the distance between each base is 90 ft. Which of the following is true about the shortest distance between 1st and 3rd bases (the red line shown above)? 1. It is less than 90 ft. 2. It is between 90 and 180 ft. 3. It is greater than 180 ft.

90 ft 90 ft

90 ft 90 ft

Worked exampleStep 1: Identify the shapes There are two right triangles with sides that are 90 ft and the red line as hypotenuse.

Step 2: Recall the formula Pythagorean theorem:

a2 + b2 = c2

Step 3: Substitute known values 902 + 902 = c2

Step 4: Solve for c 8100 + 8100 = c2 16,200 = c2 sqrt(16,200) = sqrt(c2) 90 sqrt(2) = c

Step 5: Make a selection Since 1 < sqrt(2) < 2, 90 < c < 180, so the correct answer is (2) between 90 and 180 ft.


Variability effectCalculate distance between (1,1) and (4,5)

Step 1: Identify the facts Distance is the length of a hypotenuse, for a triangle with sides as the change in x and the change in y.

Step 2: Recall the formula Pythagorean theorem:

a2 + b2 = c2

Step 3: Substitute known values (4-1)2 + (5-1)2 = c2

Step 4: Solve for c 32 + 42 = c2 9 + 16 = c2 25 = c2 5 = c

Low variability: Find distance between (2,3) and (8,11).

Medium variability: Find distance between (2,1) and (x,13).

High variability: Find (x,y) that has distance of 5 from (3,4).


Redundancy Effect

The redundancy effect occurs when information is presented in a way that includes redundant material. One example of this is to present the same idea using both visual and executive modalities, such as reading from a PowerPoint slide that has a lot of text on it. The text itself is processed initially as visual imagery, then as auditory as we “read aloud” to ourselves internally. This induces extraneous cognitive load as our minds have to cross-reference the three forms to make sure they are the same. The effect is made worse when the instructor’s voice is also reading the words. Those words must also be cross-checked for accuracy. In the end, the information is lost before it can be transferred to LTM.


Notice anything?


Redundancy Effect

The redundancy effect occurs when information is presented in a way that includes redundant material. One example of this is to present the same idea using both visual and executive modalities, such as reading from a PowerPoint slide that has a lot of text on it. The text itself is processed initially as visual imagery, then as auditory as we “read aloud” to ourselves internally. This induces extraneous cognitive load as our minds have to cross-reference the three forms to make sure they are the same. The effect is made worse when the instructor’s voice is also reading the words. Those words must also be cross-checked for accuracy. In the end, the information is lost before it can be transferred to LTM.


Applications of effects

Redundancy effect

Transient info effect

Goal-free effect

Modality effect

Worked example effect

Imagination effectTesting effect

Variability effect


Expertise reversal and guidance fading effects


Questions?

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