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Why children are better (or at least more open-minded) scientists than adults are: Search, temperature and the origins of human cognition. Alison Gopnik.

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Presentation on theme: "Why children are better (or at least more open-minded) scientists than adults are: Search, temperature and the origins of human cognition. Alison Gopnik."— Presentation transcript:

1 Why children are better (or at least more open-minded) scientists than adults are: Search, temperature and the origins of human cognition. Alison Gopnik Dept. of Psychology UC Berkeley

2 The Probabilistic Models Approach to Causal Learning Abstract structured representations of causal knowledge with systematic relations to data Intuitive theories –Gopnik & Meltzoff, 1997 Causal Bayes nets- Spirtes, Glymour and Scheines, 1993, Pearl 2000, Woodward 2003, Gopnik et al. 2004 Hierarchical causal Bayes nets and probabilistic logic- Griffiths and Tenebaum 2007, Goodman 2010

3 Probabilistic Models and Cognitive Development Gopnik 2012 Science Gopnik & Wellman 2012 Psychological Bulletin

4 Unanswered Questions How do children search through all the possible hypotheses? Do children learn higher-order causal principles as well as specific causal relationships? Why do children sometimes appear so irrational? Are there developmental differences ?

5 The Sampling Hypothesis Denison, Bonawitz, Gopnik, & Griffiths, Cognition, 2013

6 Why Childhood?: Longer Childhood, Bigger Brain, Smarter Animal

7 Quokka vs. Opposum Weisbecker & Goswami, PNAS 2010

8 Regression of predicted versus actual age for eight fossil juveniles and 36 recent (living) humans. Smith T M et al. PNAS 2010;107:20923-20928 ©2010 by National Academy of Sciences Fossil Dental Evidence For Immaturity

9 Exploration vs. Exploitation Search and temperature Childhood is evolution’s way of performing simulated annealing

10 Inferring Abstract Laws: Lucas, Gopnik & Griffiths Framework theories Hierarchical Bayes-nets (Griffiths & Tenenbaum) The blessing of abstraction (Goodman)

11 Which objects are blickets? Is D a blicket? Is E a blicket? Is F a blicket?

12 What if you also saw these events?

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14 “Or“ Training “And” Training Test

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16 Functional Form Procedure: “OR” and “AND” Test Trial DD D E D + FD + E + FD + F

17 Functional Form Procedure: “OR” and “AND” Conditions Do think the circle is a blicket or not a blicket? CIRCLE DIAMOND BALL

18 Functional Form Procedure: “OR” and “AND” Conditions Which of these should we use to make the machine turn on? CIRCLE DIAMOND BALL Intervention Question

19 “BASELINE” Test Trial 1 Results: Percentage of Participants who think D and F are Blickets N = 24N = 26 * ______ *** ______

20 “OR” Test Trial Results: Percentage of Participants who think D and F are Blickets ** _____ *** ______ N = 25N = 28

21 “AND” Test Trial Results: Percentage of Participants who think D and F are Blickets ** _____ N = 25N = 24

22 “BASELINE” Intervention 1 Results: Percentage of Single vs. Multiple Object Interventions N = 22N = 26

23 “OR” Intervention Results: Percentage of Single vs. Multiple Object Interventions N = 25N = 28

24 “AND” Intervention Results: Percentage of Single vs. Multiple Object Interventions N = 25N = 24 ** _______________________________________

25 “BASELINE” Intervention 1 Results: F v. DF v. DEF Interventions N = 22N = 26 ** ___________________ *** ___________________

26 “OR” Intervention Results: F v. DF v. DEF Interventions N = 25N = 28 *** ___________________ *** ___________________

27 “AND” Intervention Results: F v. DF v. DEF Interventions N = 25N = 24 *** _______________________________ * __________________ ** ________ ** _______________

28 Tulver Flowers

29 Tulver “AND” Test Trial Results: Percentage of Adults who think D and F are Tulvers N = 28N = 27

30 Adult “AND” Intervention Results: Percentage of Single vs. Multiple Object Interventions

31 Adult “AND” Intervention Results: F v. DF v. DEF Interventions N = 28N = 27

32 Learning Higher-Order Causal Relations: Walker & Gopnik, Psychological Science In press, Learn causal properties of objects between 19- and 24-months (Gopnik, 2012; Sobel & Kirkham, 2006; Meltzoff, Waismeyer & Gopnik, 2012) Determine whether effects were caused by their own actions at 16-months (Gweon & Shchulz, 2011)

33 Relational Reasoning in Non-Human Primates Failure as evidence for key difference in human cognition (Penn, Holyoke, & Povinelli, 2008) Depends on culture/language (Gentner, 2010) Not a qualitative difference (Premack, 1988) Primates can learn –Hundreds of trials (Premack, 1988) –Learning to use words for “same” and “different” (Premack, 1983)

34 46 participants 18- to 24-month-olds (mean 20.9 mos.) ------------------------------------------------------------ Created a causal version of Premack’s (1983) match-to-sample task –Observe an abstract relational pattern (AA’, BB’, CC’ lead to a reward) –Select between AB (object match) and DD (relational match) Experiment 1 Match-to-Sample

35 Match-to-Sample Trial 1a 35

36 Match-to-Sample Trial 1b

37 Match-to-Sample Trial 2a

38 Match-to-Sample Trial 2b

39 Match-to-Sample Trial 3a

40 Match-to-Sample Trial 3b

41 Novel Distractor Familiar Novel Paired Test Blocks Match-to-Sample Test Trial 1 41

42 Novel Distractor Familiar Novel Paired Test Blocks Match-to-Sample Test Trial 2 42

43 18- to 24-month-olds, t(45) = 2.47, p<.02** 18-20 month olds: p=.72 21-23 month olds: p<.02** Significant difference between age groups: p<.05** Results: Match-to-Sample Percentage of Infants who Selected the Pair * 43

44 Experiment 1a: Control Due to “matching” the experimenter’s selection or a baseline preference for pairs? 21 participants total 21- to 24-month-olds (mean = 22.4 mos.) --------------------------------------------------------------- Occlude the 2 nd object in the pair No evidence for relational property “same” Prediction: random selection on test items 44

45 Control Trial 1a

46 Control Trial 1b

47 Control Trial 2a

48 Control Trial 2b

49 Control Trial 3a

50 Control Trial 3b

51 Novel Distractor Familiar Novel Paired Test Blocks Control Test Trial

52 21- to 24-month-olds in Experiment 1: p<.02 21- to 24-month-olds in Experiment 2: p=.65 (ns) Significant diff. between infants in Exp 1 and Exp 2: p<.05 Results: Control Experiment Percentage of Infants who Selected the Pair *

53 Experiment 2: Relational Match-to-Sample 2 conditions: “same” and “different” 38 participants, 19 per condition Age: 18- to 30-months (mean 25.8 mos.) ----------------------------------------------------------- Present + and - evidence for the relation “same” or “different” Evidence presented as pairs of objects Single test trial

54 “Same” Trial 1

55 “Same” Trial 2

56 “Same” Trial 3

57 “Same” Trial 4

58 “Same” Condition Test Trial

59 “Different” Trial 1

60 “Different” Trial 2

61 “Different” Trial 3

62 “Different” Trial 4

63 “Different” Condition Test Trial

64 Results: RMTS Percent Infants who Selected the Correct Pair Median split (younger: mean = 22.8; older: mean = 28.7) 18-24 month olds: p=.08 (one-tail); p=.16 (two-tail) 25-30 month olds: p<.001 (two-tail exact binomial test) No significant diff between age groups, p=.58 *

65 Summary and Discussion Infants can learn abstract relational causal principles (same/different) and use them to guide action Appears very early in development May help explain how children acquire abstract causal knowledge

66 U-Shaped Curve? Piloting: older children pass the “same” condition, but fail the “different” condition Older children doing WORSE than younger children? This would support a U-shape – acquiring prior that “different” is a low probability relation 30-48-month-olds (M=36.2 months)

67 Preliminary Results

68 Conclusions Yes, damn it, children are little scientists They may be better, or at least more open-minded scientists than we are Apparent irrationalities may actually be causal inference advantages Normative philosophical inquiries and empirical psychological ones can be mutually illuminating

69 Collaborators and Support Clark Glymour Tom Griffiths Elizabeth Bonawitz Caren Walker Chris Lucas Sophie Bridgers NSF The James S. McDonnell Foundation Causal Learning Collaborative

70 Reasoning and Learning about Complex Causal Structures: Backtracking/conditioning vs Surgery/Intervening

71 Pretense and Causal Reasoning Buchsbaum et al, Philosophical Transactions of the Royal Society, ’12 Counterfactuals in causal reasoning and learning Intuitive link between causal counterfactuals and pretense – are they related?

72 Monkey’s Birthday Two within-subject phases –Counterfactual phase –Pretense phase 52 preschool age children –26 four year olds –26 three year olds “Birthday machine” for Monkey’s birthday

73 Counterfactual Phase Introduced to “birthday machine” and two objects –Plays happy birthday when “zando” is on top –Does nothing when “not a zando” is on top Asked counterfactuals –“if this one was not a zando what would happen if we put it on the machine?” –“if this one was a zando, what would happen if we put it on the machine?”

74 Pretense Phase Confederate needs to borrow real machine and objects Introduce box + two wood blocks for pretend How do we pretend to make the machine go? –What do we pretend when we put each block on the machine? –Reverse roles of blocks and repeat

75 Expt. 2: Mean Correct on Counterfactual and Pretense Questions ***

76 Music No Music Partial Correlation Counterfactuals and Pretense accounting for age, conservation, executive function: p < 0.05*, r = 0.38

77 Reasoning about Complex Causal Structures in Pretense

78 In this book, we are going to learn about my friend Katie’s dog named Sparky and cat named Buster. Sparky and Buster spend a lot of time in Katie’s backyard. Sometimes Sparky barks. When Sparky barks, it makes Buster feel scared. Other times, Sparky wags his tail. When Sparky wags his tail, it makes Buster feel happy. When Buster is scared, his fear makes him run up a tree to hide from Sparky. When Buster is happy, his happiness makes him wrestle with Sparky. When Sparky barks, his barking also makes the birds fly out of the tree. When Sparky wags his tail, the wagging makes the fleas on his tail dizzy. Sometimes there are ladybugs in Katie’s backyard. Other times there are butterflies in Katie’s backyard.

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80 Reasoning about Complex Causal Structures in Pretense Bark Wag Ladybugs Butterflies Run Wrestle Birds Fleas Scared Happy

81 Reasoning about Complex Causal Structures in Pretense: Backtracking vs Surgery

82 Preliminary Results +*

83 * + **

84 Learning Higher-Order Causal Relations, Walker & Gopnik 2012

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91 Novel Distractor Familiar Novel Paired Test Blocks

92 Novel Distractor Familiar Novel Paired Test Blocks

93 18-20 month olds: p=.72 21-23 month olds: p<.02 Sig diff between age groups: p<.05 * Results: Experiment 1 Percentage of Infants who Selected the Paired Block

94 Novel Distractor Familiar Novel Paired Test Blocks

95 21-23 month olds in Exp 1: p<.02 21-23 month olds in Exp 2: p=.72 Sig diff between infants in Exp 1 and Exp 2: p<.05 * Results: Experiment 1 vs. 2 Percentage of Infants who Selected the Paired Block

96 Summary and Discussion Preschool age children can reason about counterfactuals for a novel causal relationship Maintain and intervene on a newly learned causal relationship within a pretend scenario Flexibly reassign the causal roles of pretend objects


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