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CS-411 : Digital Education & Learning Analytics ÉCOLE POLYTECHNIQUE FÉDÉRALE DE LAUSANNE Pierre Dillenbourg, Patrick Jermann & Łukasz Kidziński Chapter 2: From Behaviorism to Mastery learning

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Page 1: Chapter 2: From Behaviorism to Mastery learning Behaviorism to Mastery learning Examples of exam questions ① In which ways does this learning technology correspond to a behaviorist

CS-411 : Digital Education & Learning Analytics

ÉC OLE POL Y TEC H NIQ U EFÉ DÉRA LE D E LA USANNE

Pierre Dillenbourg, Patrick Jermann & Łukasz Kidziński

Chapter 2:

From Behaviorism to Mastery learning

Page 2: Chapter 2: From Behaviorism to Mastery learning Behaviorism to Mastery learning Examples of exam questions ① In which ways does this learning technology correspond to a behaviorist

Examples of exam questions

①  In which ways does this learning technology correspond to a behaviorist approach ?

②  For which kind of learners is it relevant to choose inverted progressivity ?

Page 3: Chapter 2: From Behaviorism to Mastery learning Behaviorism to Mastery learning Examples of exam questions ① In which ways does this learning technology correspond to a behaviorist

Yvan  Pavlov,  1849-­‐1936    Classical  Condi6oning  

h9p://www.nob

elprize

.org/nob

el_p

rizes/m

edicine/laureates/19

04/pavlov-­‐bio.html  

h9p://www.rhsmpsychology.com/Handouts/classical_condi6oning.htm  

Page 4: Chapter 2: From Behaviorism to Mastery learning Behaviorism to Mastery learning Examples of exam questions ① In which ways does this learning technology correspond to a behaviorist

Edward  L.  Thorndike (1874 – 1949) The Law of Effect : any behavior that is fol lowed by pleasant consequences is likely to be repeated, and any behavior followed by unpleasant consequences is likely to be stopped.

h9p://psycho

logy.abo

ut.com

/od/profi

lesm

z/p/ed

ward-­‐thornd

ike.htm  

Edward  L.  Thorndike,  The  Law  of  Effect,  The  American  Journal  of  Psychology  Vol.  39,  No.  1/4  (Dec.,  1927),  pp.  212-­‐222:  h9p://www.jstor.org/stable/1415413  

h9p://www.simplypsychology.org/edward-­‐thorndike.html  

Page 5: Chapter 2: From Behaviorism to Mastery learning Behaviorism to Mastery learning Examples of exam questions ① In which ways does this learning technology correspond to a behaviorist

John Watson (1878- 1958) Behaviourism "Give me a dozen healthy infants, well-formed, and my own specified world to bring them up in and I'll guarantee to take any one at random and train him to become any type of specialist I might select -- doctor, lawyer, artist, merchant-chief and, yes, even beggar-man and thief, regardless of his talents, penchants, tendencies, abilities, vocations, and race of his ancestors." --John Watson, Behaviorism, 1930

h9p://psycho

logy.abo

ut.com

/od/be

havioralpsycho

logy/f/beh

aviorism.htm

 

The Little Albert Experiment

Page 6: Chapter 2: From Behaviorism to Mastery learning Behaviorism to Mastery learning Examples of exam questions ① In which ways does this learning technology correspond to a behaviorist

Burrhus  Frederic  Skinner  (1904-­‐1990),  Operant  Conditonning  

h9ps://sites.google.com/a/adams12.org/harp-­‐mrhs-­‐home-­‐v1/06-­‐powerpoint-­‐sec6on/skinner-­‐s-­‐operant-­‐condi6oning  

Page 7: Chapter 2: From Behaviorism to Mastery learning Behaviorism to Mastery learning Examples of exam questions ① In which ways does this learning technology correspond to a behaviorist

Key ideas in behaviorism

①  Psychology is becoming more scientific ②  The brain is a black box; the focus is on

behaviors ③  Learning is « engineered » ④  Association results from immediate feedback ⑤  The learner is permanently active ⑥  Small steps increase the probability of positive

feedback è Programmed instruction

Page 8: Chapter 2: From Behaviorism to Mastery learning Behaviorism to Mastery learning Examples of exam questions ① In which ways does this learning technology correspond to a behaviorist

B. F. Skinner

Page 9: Chapter 2: From Behaviorism to Mastery learning Behaviorism to Mastery learning Examples of exam questions ① In which ways does this learning technology correspond to a behaviorist
Page 10: Chapter 2: From Behaviorism to Mastery learning Behaviorism to Mastery learning Examples of exam questions ① In which ways does this learning technology correspond to a behaviorist

Linear Instruction

h9p://66.31.107.147/~heines/academic/papers/2002elearn/images/Lumsdaine_Glaser/  

Page 11: Chapter 2: From Behaviorism to Mastery learning Behaviorism to Mastery learning Examples of exam questions ① In which ways does this learning technology correspond to a behaviorist

1.  Information

2.  Question

3.  Feeback

1.  Information

2.  Question

3.  Feeback

1.  Information

2.  Question

3.  Feeback

1.  Information

2.  Question

3.  Feeback

1.  Information

2.  Question

3.  Feeback

•   Decomposi6on:  Segmen6ng  complex  contents  into  a  sequence  of  learning  steps  that  contains  an  elementary  piece  of  informa6on    

•   Keep  the  student  ac6ve  all  the  6me,  ask  the  student  to  process  any  new  piece  of  informa6on  

•   Provide  immediate  feedback  

•   Let  the  student  move  on  at  his  or  her  own  speed  

Based  on  behaviourism-­‐inspired  “programmed  learning  instruc6on”  

Frame-­‐Based  Models  

Page 12: Chapter 2: From Behaviorism to Mastery learning Behaviorism to Mastery learning Examples of exam questions ① In which ways does this learning technology correspond to a behaviorist

Branched Instruction

AutoTutor, Crowder

h9p://ute3.umh.ac.be/u6

cef/master/m341/par6e_2.htm  

Page 13: Chapter 2: From Behaviorism to Mastery learning Behaviorism to Mastery learning Examples of exam questions ① In which ways does this learning technology correspond to a behaviorist

1.  Information

2.  Question

3.  Feeback

1.  Information

2.  Question

3.  Feeback

1.  Information

2.  Question

3.  Feeback

1.  Information

2.  Question

3.  Feeback

1.  Information

2.  Question

3.  Feeback

•   Decomposi6on:  Segmen6ng  complex  contents  into  a  sequence  of  learning  steps  that  contains  an  elementary  piece  of  informa6on    

•   Keep  the  student  ac6ve  all  the  6me,  ask  the  student  to  process  any  new  piece  of  informa6on  

•   Provide  immediate  feedback  

•   Let  the  student  move  on  at  his  or  her  own  speed.    

•   Individualisa6on:  adapt  instruc6on  to  the  student  needs  

Based  on  behaviourism-­‐inspired  “programmed  learning  instruc6on”  

Frame-­‐Based  Models  

Page 14: Chapter 2: From Behaviorism to Mastery learning Behaviorism to Mastery learning Examples of exam questions ① In which ways does this learning technology correspond to a behaviorist

Module  1  

Module  2  

Module  3  Test    

Module  4  

Test    

Test    

Mastery Learning

•  Larger granularity: modules > frames

•  Permanent control of effectiveness

Page 15: Chapter 2: From Behaviorism to Mastery learning Behaviorism to Mastery learning Examples of exam questions ① In which ways does this learning technology correspond to a behaviorist

"about 90% of the tutored students ... attained the level of summative achievement reached by only the highest 20% of the control class

B. Bloom

Bloom, B. (1984). "The 2 Sigma Problem: The Search for Methods of Group Instruction as Effective as One-to-One Tutoring", Educational Researcher, 13:6(4-16).

Page 16: Chapter 2: From Behaviorism to Mastery learning Behaviorism to Mastery learning Examples of exam questions ① In which ways does this learning technology correspond to a behaviorist

a1 a2..1 a2.2

Pre-requisites test

Remediation

a3

a4

a5

a6

a7

a8

Pre-test

Post-Test

Int. Test

Redo [a4-a5]

Skip [a4-a5]

Item Order

Diff

icul

ty

Uphill strategy: go up until he fails

Downhill strategy: go down until he succeeds

Discriminant strategy: increase/decrease difficulty based on success – cut the space in 2

Modular Instruction Pre-requisite test: Does the learner has the pre-requisite to start the course ? Pre-test: Should the learner skip some modules ? Intermediate-test: Didthe learner reach the objectives of this module ? Post-test: Did the learner reach the objectives of this course?

Adaptive Testing

Page 17: Chapter 2: From Behaviorism to Mastery learning Behaviorism to Mastery learning Examples of exam questions ① In which ways does this learning technology correspond to a behaviorist

Personalized Instruction Individual instruction

Adaptative instruction

Cronbach, L. & Snow, R. (1977). Aptitudes and Instructional Methods: A Handbook for Research on Interactions. New York: Irvington

Aptitude-treatment Interactions: The effect of a pedagogical method

varies for different learners,

Page 18: Chapter 2: From Behaviorism to Mastery learning Behaviorism to Mastery learning Examples of exam questions ① In which ways does this learning technology correspond to a behaviorist

Statique Dynamique

Condition Animation

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0.00

0.20

0.40

scor

e d'

infé

renc

e (c

entr

é-ré

duit)

Solo

Duo

Interaction des variables animation etcollaboration sur l'inférence

Aptitude-treatment Interactions

Sangin,  M.,  Molinari,  G.,  Dillenbourg,  P.,  Rebetez,  C.,  &  Bétrancourt,  M.  (2006).  Collabora6ve  learning  with  animated  pictures:  The  role  of  verbaliza6ons.  In  Proceedings  of  the  7th  interna6onal  conference  on  Learning  Sciences  (pp.  667-­‐673).  Interna6onal  Society  of  the  Learning  Sciences.  

Page 19: Chapter 2: From Behaviorism to Mastery learning Behaviorism to Mastery learning Examples of exam questions ① In which ways does this learning technology correspond to a behaviorist

Bloom’s Taxonomy

h9p://wglink.pbworks.com/w/page/38080839/Bloom's%20Triangles  

Page 20: Chapter 2: From Behaviorism to Mastery learning Behaviorism to Mastery learning Examples of exam questions ① In which ways does this learning technology correspond to a behaviorist

One goal

Diverse O

bjectives Taxonomy

Taxonomy as a prism

Page 21: Chapter 2: From Behaviorism to Mastery learning Behaviorism to Mastery learning Examples of exam questions ① In which ways does this learning technology correspond to a behaviorist

http://www.trainsmartinc.com/about-us/instructional-design/

1.  Objectives 2.  Audience 3.  Contents

Page 22: Chapter 2: From Behaviorism to Mastery learning Behaviorism to Mastery learning Examples of exam questions ① In which ways does this learning technology correspond to a behaviorist

Find summit opposite to ab

Measure [c – ab]

Select a base

Measure the base

Multiply

Divide by 2

ab

Draw line by c orthogonal to ab

c

height

h b

hb

surface

Triangle abc

c a

b

Content Analysis (mathetic analysis)

Page 23: Chapter 2: From Behaviorism to Mastery learning Behaviorism to Mastery learning Examples of exam questions ① In which ways does this learning technology correspond to a behaviorist

A triangle is a polygon with 3 vertices.

A polygon is a plane figure bounded by a finite chain of straight

line segments

A plane is a flat two-dimensional surface

A line segment is a part of a line that is bounded by two

distinct end points

The vertex of an angle is the point where two line segments join or meet

A right triangle is a triangle in which one angle is a right

tangle

In a right triangle, the square of the hypotenuse is the sum of square of the two other sides.

A right angle has a amplitude of 90 degrees

An hypotenuse is the side of a right triangle opposed

to the right angle Content Analysis

(semantic analysis)

Page 24: Chapter 2: From Behaviorism to Mastery learning Behaviorism to Mastery learning Examples of exam questions ① In which ways does this learning technology correspond to a behaviorist

Instructional design: from tradition to engineering

ÉC OLE POL Y TEC H NIQ U EFÉ DÉRA LE D E LA USANNE

h9p://www.historicbridges.org/