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EP2. Social learning
Elena Pasquinelli
Educa4on, cogni4on, cerveau Cogmaster 2010‐2011
Transmission of generic knowledge
• Induc4on problem: Humans are capable of transmiFng/extrac4ng general knowledge from par4cular instances – When such instances are repe44ve and frequent, sta$s$cal mechanisms* are invoked.
– When this is not the case (single instance) we need a further mechanisms for explaining induc4on.
• Such a mechanisms is hypothesized to rely on human‐human communica4on – Verbal and not verbal (demonstra4on)
A STEP BACK TO EARLY LEARNING MECHANISMS: ‐ STATISTICAL LEARNING
‐ IMPLICIT LEARNING ‐ LEARNING BY IMITATION ‐ EXPLANATORY LEARNING
‐ LEARNING BY ANALOGY
Learning = the modifica4on of behavior in light of experience
• sta4s4cal learning, • learning by imita4on, • explana4on‐based or
causal learning • and learning by analogy. • Using these simple
learning mechanisms, the brain appears to build up complex representa4ons about how the world is.” (Goswami, 2008, p. 52)
• Under this defini4on, learning is a common func4on to different animal species
Early learning mechanisms 1. sta4s4cal learning
• “Babies appear to be able to make connec4ons between events that are reliably associated, even while in the womb.
• Once outside the womb, they appear to be able to track sta$s$cal dependencies in the world, such as condi4onal probabili4es between visual events or between sounds. This turns out to be a very powerful learning mechanism.”
Sta4s4cal learning and language • Language acquisi4on has provoked a
debate on nature (Chomsky) vs nurture (Skinner)
• Cri4cal periods in language learning differ in the three aspects of language: phone4cs (before 12 months), syntax (18‐36), lexicon (forever)
• Why are children be^er than adults? • Kuhl, 2004: neural commitment
– Once perceptual systems are commi^ed they filter new informa4on
– Commitment is done between 6 and 12 months (for phone4cs): before, children dis4nguish all the phone4c units of all languages
• How can children succeed in a difficult task as iden$fying and grouping the more or less 40 phonemes that compose their language? In the middle of a great variability of speech?
Sta4s4cal learning and language • Sta4s4cal learning
(Saffran, et al, 1996) applies to the capacity to iden4fy phonemes and to the capacity of segmen4ng words – Japanese and English
infants are both exposed to both /r/ and /l/ sounds, but in Japanese the sound /r/ is much more frequent
– Babies spot the transi4onal probabili4es between syllables
Language: sta4s4cal learning is not enough
• Sta4s4cal learning can have strong and durable effects on phone4cs at 9 months of age, and with short‐4me exposure to sta4s4cal regulari4es – 9 months old children can learn to
dis4nguish Mandarin phonemes from exposure to play and interac4on with a Mandarin speaking tutor
• But is sta4s4cal learning enough? – 9 months old children cannot learn
to dis4nguish Mandarin phonemes from a Mandarin speaking TV‐canned /audiotaped tutor
• Social interac4on is required
Social interac4on
• Social interac4on can have an effect on learning through: – Enhancement of a^en4on – Addi4onal informa4on (gaze to object)
– Ac4va4on of mirror systems, and other mechanisms for percep4on‐ac4on linking in the brain
Implicit learning • Implicit learning theories are based
on the capacity of extrac4ng regulari4es, e.g. on grammar: – Reber, 1967, 1989: implicit learning
allows the acquisi4on of complex, abstract knowledge without awareness and effort (extrac4on of abstract rules)
– Pacton & Perruchet, 2006: acquisi4on of the ap4tude to correctly answering to certain situa4ons, without the inten4on of learning (no extrac4on of abstract rules; the learning of rules requires explicit learning)
• the crucial variable is the exposi4on to regulari4es in the environment
• It does not mean one can learn without aRen$on (concurrent a^en4onal tasks lower the capacity of implicit learning)
Implicit & explicit learning • Perruchet & Pacton, 2006: Explicit learning
completes implicit learning with rules • Perruchet & Pacton, 2006: In any case,
explicit learning raises performances in comparison with implicit learning (school instruc4on demands more than above chance performances)
• Reber, 1989: introduc4on of explicit instruc4on is especially useful when informa4on is provided before (rather than during or aker the implicit learning phase), maybe because it helps direc4ng a^en4on on meaningful aspects
• Bransford, Brown, & Cocking, 2000: Judd & Scholckow 1908’s experiment confirms that explicit instruc4on (before training) enhances performances for new situa4ons
Implicit learning of errors
• If implicit learning can happen by repeated exposi4on (with a^en4on), then the repeated exposi4on to errors favors the learning of errors
• Mul4ple choice tests enhance learning of good, and bad, answers (Marsh, et al., 2007, p. 195)
Sta4s4cal learning & Extrac4on of causal structures
• “… specific perceptual features of two objects in a “launching” event (where object A impacts object B, causing it to begin to move) may vary, but spa4o‐temporal dynamics (and therefore causal structure, i.e., the fact that A causes B to move) will vary less. The perceptual “illusion” of causality during launching and other visual events noted by Micho^e (1963) is one example of how perceptual covaria4on can yield causal (Goswami, 2008b, p. 9)
h^p://cogweb.ucla.edu/Discourse/Narra4ve/micho^e‐demo.swf
Early learning mechanisms learning by explana4on & analogy
• “In the field of machine learning, explana4on‐based learning depends on construc4ng causal explana4ons for phenomena on the basis of specific training examples, using prior domain knowledge.
• If infants were merely learning condi4on‐outcome rela4ons, as in associa4ve learning, then they would be unable to make predic4ons about novel events.” (Goswami, 2008, p. 66)
Learning by analogy • “In learning by analogy, “we face a situa4on, we
recall a similar situa4on, we match them up, we reason, and we learn” (Winston, 1980). We may decide whether a dog has a heart by thinking about whether people have hearts (young children use “personifica4on analogies” to learn about biological kinds, see Inagaki & Hatano, 1988), or we may solve a mathema4cal problem about the interac4on of forces by using an analogy to a tug‐of‐war (young children use familiar physical systems to reason about unfamiliar ones, see Pauen, 1996).
• Reasoning by analogy has usually been measured in children aged 3 years or older (see Goswami, 1992, 2001, for reviews), but can also be demonstrated in infancy. However, so far, analogy has not been found in the animal kingdom, sugges4ng that it is especially important for human learning.” (Goswami, 2008b, p.13‐14)
Early learning mechanisms Imita4on
• “Learning by imita4on can be defined as B learns from A some part of the form of a behavior…
• One example is learning the use of a novel tool by imita4ng the ac4ons of another user with that tool. (Goswami, 2008, p. 62‐63)
Meltzoff, 1988
Learning by imita4on is present in the human baby by the age of at least 9 months (Meltzoff, 1988)
Learning by imita4on & TV
• 14 months’ babies can learn the same ac4ons from real experimenters and from experimenters canned in a TV video (on live)
• But they learn less than from live ac4on (video deficit effect) (Zack, et al. 2009, p. 14) – Maybe because the processing of 2D s4muli is
poorer than the processing of 3D s4muli – Or because 2D s4muli are poorly understood and
their rela4on to 3D real objects is not granted – Or because of poor representa4onal flexibility (and
memory requirements) • Is that because of 2D/3D encoding differences?
What happens with 3D models? – An experiments conduced by Zack and coll. shows
that the limit comes from the transfer of informa4on from one dimension to another (live adult demonstra4on)
– Infants do just as well imita4ng 2D/2D than 3D/3D: 2D is not as impoverished as to block imita4on, and 2D does not represent a poorly understood condi4on in comparison with 3D (but live adult demonstra4on could help the understanding)
– Representa4onal flexibility seems to be the problem
Imita4on, social cogni4on & mirror neurons
• Among the studies on social cogni4on, mirror neurons have gained lot of a^en4on
• Mirror neurons are involved in the representa4on of an ac4on
• Mirror neurons are ac4vated when observing an ac4on, independently from the specific motor realiza4on of the ac4on
• Mirror neurons are related to the goal, and the agent
• Mirror neurons could be involved in the understanding of others’ inten4ons and to imita4on
• Specula4vely, in empathy (Iacoboni, et al., 2005)
Human imita4on
• Infants understand and imitate adults’ inten4ons, not only their behaviors
• Learning by imita4on seems to require the understanding of others’ inten4ons (Tomasello, 1990)
Understanding human inten4ons
• Three levels of understanding others’ ac4ons & reading of inten4ons) – Perceiving others as actors
that produce their ac4ons (6 months old children)
– Perceiving others as having goals for their ac4ons (9 months)
– Perceiving others as making plans for reaching their goal, and choosing the most ra4onal ac4on (14 months)
(Tomasello, et al. 2005)
Engaging in shared inten4ons
• 3 levels of engagement in shared inten4ons: – Dyadic engagement: face
to face interac4ons and protoconversa4ons with shared emo4ons
– Tryadic engagement: doing things together, but without assigning roles for the reaching of the goal; sharing percep4on and goals (9‐12 months)
– Collabora4ve engagement = sharing ac4on plans (12‐15 months)
Humanness • At the origin of human culture
and cogni4on stand two capaci4es:
• ‐ mind reading, and in par4cular: the capacity of perceiving and understanding others’ inten4ons
• ‐ a mo4va4on for engaging in shared inten4on ac4vi4es
• So: shared inten4onality is what makes humans special in the animal reign
• (Tomasello, 2005)
Cultural intelligence hypothesis • Cogni4ve, Evolu4onary
anthropology – Baby humans differ from
primates mainly because of social abili4es
– Further differences between humans and primate might derive from these social‐cultural
– Humans have developed special cogni4ve skills as a result of the development of specialized skills for absorbing knowledge and prac4ces of their social group
NATURAL PEDAGOGY: ‐ THE INDUCTION PROBLEM ‐ THE CONDITIONS FOR NATURAL PEDAGOGY
• Induc4on problem: how to compose bits of episodic informa4on into a general knowledge that can then be applied to several, different situa4ons
Natural pedagogy • “… human communica4on is specifically
adapted to fulfil the funciton of transmiFng generic knowledge between individuals.” (Gergely & Csibra, p. 3)
• “A new type of communica4ve learning system based on ostensive‐referen4al demonstra4ons of knowledge … expert user ac4vely guide the novice by selec4vely manifes4ng the informa4on to be acquire and generalized.
• … children … are always novices with respect to the accumulated knowledge of their culture.
• This is why we call the specific aspects of human communica4on that allow and facilitate the transfer of generic knowledge to novices Natural Pedagogy. ” (Gergely & Csibra, p. 4)
• Development of natural pedagogy:
• Development of tools’ making prac4ces represents an evolu4ve pressure
• Because these prac4ces cannot be learned/transmi^ed by other, available mechanisms of learning from imita$on/observa$on*
• Because they represent opaque contents for cogni4on
• Thus, humans have evolved mechanisms that serve the pedagogical func4on of transmiFng cogni4vely opaque contents
• These mechanisms are part of the more general communica4on system
• They consist of demonstra4on acts: ostensive‐referen4al demonstra4ons
Adults/children natural pedagogical system
• “When children are shown an ac4on performed in a par4cular style leading to a clear end state (e.g. a mouse is hopping across the table into a house), they tend to reproduce only the end state (put the mouse into the house), oken ignoring the manner of ac4on (hopping). However, if the relevant informa4on concerning the end state is communicated to them verbally by the actor before the demonstra4on (“the mouse lives in the house”), they reproduce the ac4on style more oken.
• Ostensive communica4on does not only make children pay more a^en4on to the demonstra4on but they also see it as a special opportunity to acquire generalizable knowledge.” (Gergely & Csibra, p. 5)
• “recent studies ...demonstrate this preparadness in the form of three kinds of early perceptual and cogni4ve biases:
• Children observe and imitate adults – Children spontaneously imitate causal ac4ons
that lead to achieve goals, and ignore other components of the global ac4on
– The others components of the ac4on are opaque to children’s cogni4on
– But, when the “teacher” makes it clear that these components of the ac4on are relevant, children do pay a^en4on, and imitate
• Adults use their communica4on system to facilitate children’s learning
• Young children are recep4ve to adult’s ostensive demonstra4on before they are able to use it for learning
• Ostensive signals allow to – Disambiguate the nature of the ac4on
(communica4on, not just using the tool) – Disambiguate the target of the
communica4on (you)
Ostensive signals • 1. preferen4al a^en4on for
the sources of ostensive signals
• Preference for ostensive signals : – Gaze contact
• Newborns preferen4ally look at schema4c face‐like pa^erns with direct gaze vs averted gaze; preference disappears when faces are upside‐down; preference disappears when the typical iris/sclera pa^ers of eyes is inverted
• Same neural ac4va4on for infants and adults in response to direct gaze and common neural ac4va4on for two different ostensive s4muli (direct gaze & eye‐brow raise)
– Motherese – Mo4onese
Referen4al expecta4ons • 2. Referen4al expecta4on
induced by ostensive contexts • Eight‐months olds observed
someone on a computer screen ostensively looking at and gree4ng them before shiking her gaze to llok behind one of two barriers. Following this, an object was revealed either at the targeted or at the other occluded loca4on. Infants’ looking pa^ern suggested that they expected to find an object at the loca4on where the person’s gaze wwas directed at, just like older infants do in similar live situa4ons.” (Gergely & Csibra, p. 5‐8)
– Infants follow the gaze of interac4ng adults to iden4fy what they are looking at, before they can understand language
– Useful for sampling parts of the world that others found interes4ng, and present in other animals
– Human infants followgaze shiks only when these are preceded by ostensive signals (gree4ng, gaze contact)
– Infants expect to find an object at the “end” of a gaze‐following in an ostensive context – 13 months old Infants expect to
find the named object (if its name is part of their vocabulary)
– But not if the gesture and word are emi^ed by different persons
Interpreta4on bias • 3. interpreta4on bias to
preferen4ally encode the content of ostensive‐referen4al communica4on as represen4ng generalizable knowledge”
• “this is what dis4nguishes our hypothesis in the first place from compe4ng proposals, according to which human communica4on originates evolu4onarily and ontogene4cally from a basic mo4ve to cooperate with others to achieve shared goals.” (Gergely & Csibra, p. 5‐9)
– Not only infants are prepared to receive ostensive–referen4al communica4on, but they do expect to learn something generalizable from it (and not just a par4cular instance) = to learn about referent kinds – When infants (18 months old) observe adults expressing
emo4onal valence in rela4onship to an object in a non‐communica4ve context, they infer that person’s par4cular preference (she does not like it). But when the same pa^ern of valence expression is inserted in a communica4ve context, infants a^ach the expressed value to the object and expect that other people will react in the same manner to the object (it is disgus4ng for everybody)
– Infants (9 months old) shik their encoding pa^ern from loca4on to appearance features when the situa4on shiks from non‐communica4ve to communica4ve. – They are more likely to detect change in loca4on in
a non‐communica4ve situa4on, but detect more oken features change in a communica4ve situa4on and neglect loca4on; and this happens even in situa4ons in which loca4on is important, pragma4cally, such as hiding games
– This bias could explain A not‐B task errors: children stop being interested in loca4on and do not mind about the new loca4on, because the communica4ve contexts has made them focus on the features of the object. In fact, once communica4ve cues are removed, the errors diminish.
– Appearance features are be^er candidates for later use and object iden4fica4on, thus for generaliza4on.
– Communica4on has evolved not only for collabora4on‐purposes but also under the pressure of learning/teaching purposes
Social learning mechanisms • “There are many types of social learning
mechanisms in the animal kingdom, and they all involve some form of observa4onal learning, where the observa4on of an adap4ve behavior of another individual makes it more likely that the observer will produce the same or similar behaviors in the future. In this sense, social learning represents transmission of general knowledge or skills from one individual to another.
• Non‐human animals communicate about episodic, non‐generalizable informa4on (that applies only to the here and now), and learn new skills by observa4on or scaffolded individual learning, they do not seem to use communica4on to pass on generalizable knowledge to others.”
• “ This discrepancy between general claims about the absence of teaching and the actual reports is likely to reflect the enormous differences between teaching in Western socie4es and in more tradi4onal cultures. It is not just that Western educa4on relies heavily on formal schooling but also that it aims to provide verbal explana4on and jus4fica4on for what is being taught. … however, Natural Pedagogy … seems to be universal.” (Gergely & Csibra, 2009, p. 12‐14)
• Social learning mechanisms are common to several animal species
• Learning generalizable knowledge from social interac4ons seems to be specific to humans
• Natural pedagogy seems to be universal, thus “natural”
• “Child development is today conceptualized as an essen4ally social process, based on incremental knowledge acquisi4on driven by cultural experience and social context. We have “social” brains.” (Goswami, 2008b, p. 1)
LEVELS OF ANALYSIS
Distributed cogni4on • The unit of analysis
of cogni4ve performances should be extended beyond the individual so as to encompass social and material interac4ons with tools – (Hutchins, 1995)
Extended cogni4on • Performances
typically described as cogni4ve are significantly worst in absence of interac4on with tools, others, or of epistemic ac4ons that have no other aim than favoring a be^er knowledge of the world – (Clark & Chalmers,
1998)
Social neuroscience • Strong accent on
cogni4on as a social phenomenon which produces changes in the brain, as well as changes in the brain produce social phenomena
• importance of mul4level, integra4ve analysis of complex psychological phenomena
“… the brain does not exist in isola4on but rather is a fundamental but interac4ng component of a developing or aging individual who is a mere actor in the larger theater of life. This theater is undeniably social, beginning with prenatal care, mother‐infant a^achment, and early childhood experiences, and ending with loneliness or social support and with familiar or societal decisions about care for the elderly. … Social psychology, with its panoramic focus on the effects of human associa4on and the impact of society on the individual, is therefore a fundamental although some4mes unaknowledged complement to the neurosciences.” (Cacioppo & Berentson, 1992, p. 1020)
Integra4on of levels of analysis
importance of mul$level, integra$ve analysis of complex psychological phenomena
1. Neurochemical events influence social processes; Social processes influence neurochemical events
• Difficulty in the integra4on of neuroscience and social psychology levels of analysis: different scales into which brain and behavior can be represented
• The level of organiza4on of psychological phenomena vary from molecular the organism set into a physical environment and a socio‐cultural context
• Neurosciences generally encompass the lower level of the spectrum, social psychology the higher one
• Integra4on means that analyses at each level of organiza4on can inform, refine or constrain inferences in the other levels
2. The study of the elements of the system can fall short of useful and comprehensive explana4ons • In other sciences, the existence of different levels of explana4on (protons/rocks) does not lead to considering geology as a folk theory when compared with molecular level models.
• Dis4nc4ve levels of analysis are complementary, not alterna4ve
– 3. A set of neural events can be a sufficient cause for producing a psychological phenomenon, without being a necessary one • E.g., lying rubustly produces certain electrodermal responses ; but other condi4ons can produce the same electrodermal responses
• E.g. schizophrenia is reliably associated with elevated dopamine levels (elevated dopamine levels produce schizophrenia‐like symptoms) but excessive levels of dopamine are not necessarily involved in all cases of schizophrenia – However, when other neurochemical mechanisms are iden4fied that
produce schizophrenia‐like symptoms with a different neurochemical basis, it is possible to part the psychological term “schizophrenia” in different pathologies.
• In the case of mul4ple determinants of a certain behavior, studies on the sufficiency of a certain neurophysiological condi4on in causing a certain phenomenological phenomenon are impôrtant but lack generalizing power.
from medicine to educa4on • “… no single level of behavioral organiza4on is best for all psychological ques4ons. • An example can be found in the rela4ve u4lity of specifying the sociocogni4ve versus
the neurophysiological basis of pa4ent delay following the onset of gynecologic cancer. Women can now survive most gynecologic cancers if the disease is diagnosed and treated early. … The form of the representa4on of pa4ent delay offered by neuroscien4fic analyses of pa4ent delay, although perhaps contribu4ng to more complete understanding of the phenomenon, is not op4mal for iden4fying the determinants of pa4ent delay or for developing effec4ve interven4ons to minimize such delay. Huge savings in resources and human suffering are there to be reaped not through a specifica4on of the brain circuits underlying pa4ent delay, but by well‐conceived public health campaings that iden4fy the early signs of cancer… ” (Cacioppo & Berentson, 1992, p. 1022)
• “It follows … that an exclusive focus on a reduc4onis4c (e.g. neurophysiological, molecular, gene4c) level of analysis can mask contribu4ons of other levels of organiza4on to mental order and disorder and thereby constrain theore4cal accounts of psychological phenomena.”
• “Hence, without a^en4on to basic social psychological factors and processes, the decade of the brain may yield some spectacular images and experimental effects but rather limited answers to the problems of mental health.” (Cacioppo & Berentson, 1992, p. 1025)
Affec4ve neuroscience • Importance of emo4ons for ra4onality
• Role of mo4va4on in learning
• Role of reward and punishment
EXAMPLES & ISSUES OF SOCIAL LEARNING ‐ TUTORING
The 2 sigma problem • Bloom, 1984 has compared 3 condi4ons of instruc4on:
– Conven4onal (1:30, periodic tests for marking) – Mastery learning (1:30, forma4ve tests for measuring mastery & immediate
feedback) – Tutoring (1:1 or 1:2 1:3, forma4ve tests and feedback)
• He found that the average student under tutoring was above 98% of the students in the control class = 2 standard devia4ons above the average of the control class
• The average student under mastery learning was about 1 standard devia4on above the average of the control class (above 84% of the students in the control class)
• 90% of the tutored students and 70% of the mastery learning students a^ained levels of achievement that only 20% of the students in the control class had achieved – Tutoring would probably not enable the top 20% of tradi4onal instruc4on group
students to do be^er; but 80% of tradi4onal classrooms do poorly in comparison to tutoring
– Maybe this is because teachers direct their a^en4on to some students, and ignore others
