This document discusses conceptual change in learning, specifically: 1) Conceptual change refers to overcoming prior misconceptions when learning new concepts, which can be difficult and problematic. Certain topics in science especially challenge students. 2) Theories of conceptual change propose that students arrive with preexisting ideas that constrain new learning. Overcoming these requires more than just adding new information but restructuring existing knowledge. 3) Researchers study the nature of conceptual change and how it relates to scientific revolutions, cognitive development theories, and differences between novice and expert understanding. Conceptual change involves qualitative changes in thought.

1. EP3.
Good learning
Elena Pasquinelli
Educa4on, cogni4on, cerveau
Cogmaster 2010‐2011

2. CONCEPTUAL CHANGE
‐ GENERAL FRAMEWORK
‐ THA NATURE OF CHANGE
‐ WHAT CHANGES?
‐ HOW TO PRODUCE A CHANGE?
‐ IMPACT ON EDUCATION AND RESEARCH

3. • “In the broad educa4onal experience, some
topics seem systema4cally to be extremely
difficult for students. Learning and teaching in
these areas are problema4c and present
persistent failures of conven4onal methods of
instruc4on. Many areas in the sciences, from
elementary school through university level, have
this characteris4c, including, in physics: concepts
of maJer and density, Newtonian mechanics,
electricity, and rela4vity; in biology: evolu4on
and gene4cs.” (DiSessa, 2006), p. 1

4. Conceptual change
• “John Clement (1982) was one of the first to
• A problem for study how we reason about the coin problem.
He found that what leads us to choose … is
instruc4on: the misconcep4on that flipping a coin gives it
an impetus. On the upward path, we reason,
some topics the impetus gradually diminishes, un4l it
are especially becomes less than the force of gravity and the
coin falls. According to Newton, however, once
difficult to we toss the coin, it would con4nue on a
straight‐line path indefinitely unless and
learn, in unbalanced force acts on it. The only force
ac4ng on it is gravity. Gravity causes the coin
par4cular in to slow down un4l it reaches the top of its
the science trajectory, and then to speed up as it falls back
on the ground? Clement found that only 12%
domain of students in a first‐year engineering course,
all high school physics graduates, answered
the coin problem correctly.” (Bruer, 1993, p.
130)

5. The tossed coin
• Why are students in difficulty with the tossed coin
problem?
– Because physics is difficult or badly explained (Tabula rasa
hypothesis)
– Because students have prior ideas of “force” and these
naïve ideas must be addressed (Conceptual change
hypothesis)
• Prior ideas are coherent and integrated (must be rejected as a
whole)
– Prior ideas are fragmented (can be disassembled, refined,
and re‐assembled in correct physics)

6. Why the seasons?

7. Theore4cal issues on conceptual
change
• “Strong evidence exists that prior ideas constrain
• Uncontroversial acquisi4on of learning in many areas. The “conceptual” part
learning sciences: of the conceptual change label must be treated
– Conceptual change vs/ tabula
rasa: less literally. Various theories locate the difficulty
– Students arrive to instruc4on insuch en44es as “beliefs,” “theories,” or
with prior ideas “ontologies,” in addi4on to “concepts.” (DiSessa,
– Prior ideas constrain successive 2006, p. 1)
learning • “Conceptual change also engages some of the
• Controversial issues: deepest, most persistent theore4cal issues
– Are prior ideas real “concepts”, concerning learning. What is knowledge in its
“theories”, “beliefs”?
various forms? When and why is it difficult to
– In what consists the change?
acquire? What is deep understanding; how can it
– What is knowledge (learning,
development, history of be fostered? Conceptual change is important not
science)? only to educa4on, but also to developmental
– What is deep understanding? psychology, epistemology, and the history and
– How do experts differ from philosophy of science. In the history of science,
novices? consider: What accounts for the challenges
posed by scien4fic revolu4ons, such as those
engendered by Newton, Copernicus,and
Darwin?” (DiSessa, 2006, p. 1‐2)

8. The nature of change
• “Susan Carey (1991, 1999) was one of the earliest
and most consistent in ci4ng Kuhn’sideas in the
context of children’s conceptual change. She has
systema4cally used the idea of incommensurability
between conceptual systems as a primary index of
conceptual change (“deep restructuring”).
Incommensurability dis4nguishes conceptual change
from “enrichment” (adding new ideas or beliefs) or
even mere change of beliefs.” (diSessa, 2006, p. 7)

9. S. Carey: Belief revision vs
conceptual change
• “The respec4ve literature of science educa4on,
• S. Carey: conceptual change consists of a cogni4ve development, and the history of science
deep reorganiza4on of knowledge are filled with examples of tenaciously held beliefs
that seem bizarre from the standpoint of modern
scien4fic literacy. Examples from cogni4ve
• 2 main influences on Carey’s view of development are cars are alive or air is immaterial.
conceptual change: • It seems unlikely that preschool children who insist
that cars are alive could have the same concept of
• Kuhn: life as the adult and merely be mistaken about
– 1. The structure of conceptual change is cars, and indeed, they do not.
the same as scien4fic revolu4ons • Rather, preschool children have constructed a very
– 2. Knowledge acquisi4on in individuals different theore4cal framework from that held by
parallels knowledge acquisi4on in the adults, in which they have embedded their
history of science
understanding of animals, just as children of
• Piaget has influenced the no4on of elementary school age have constructed a different
conceptual change mainly through the framework theory in which they embed their
no4on of a qualita4ve change in the way understanding of the material world.
children of different ages and adults
think about the world

10. Scien4fic revolu4ons
• Kuhn: • “To many, Kuhn defines the enduring relevance of the history
– Scien4fic revolu4ons: all of science to studies of conceptual change broadly. On the other
changes in the shin from hand, Kuhn had strong opposi4on within the history of science,
a paradigm to another, and there was probably never a 4me when his work represented
including what counts as the consensus view in that field.
good science
– The shin is not just a • Kuhn laid out a different view of progress in science, compared
maJer of ra4onality and to most of his predecessors. Kuhn rejected the idea that science
logic, but involves progresses incrementally. Instead, he claimed that ordinary
sociological reasons, “puzzle solving” periods of science, called “Normal Science,” are
pragma4c opportuni4es, punctuated by revolu4ons, periods of radical change that work
etc. completely differently than Normal Science. In par4cular, the
– Paradigms are en4re disciplinary matrix (referred to ambiguously but famously
reciprocally as a “paradigm” in the earliest edi4on) gets shined in a
incommensurable
revolu4on. What counts as a sensible problem, how proposed
– Science is not a linear, solu4ons are judged, what methods are reliable, which symbolic
incremental path from
ignorance to truth generaliza4ons apply, and so on, all change at once in a
revolu4on. Kuhn famously compared scien4fic revolu4ons to
gestalt switches, where prac44oners of the “old paradigm” and
those of the “new paradigm” simply do not see the same things
in the world. Gestalt switches happen when the coherence of
ideas forces many things to change at once.” ( Di Sessa, 2006, p.
4‐5)

11. Qualita4ve changes in thought
• “Some of Piaget’s theore4cal apparatus penetrated into conceptual
• Piaget: change research. For example, Piaget viewed equilibra4on as a key
mechanism: New experiences disequilibrated prior knowledge, and re‐
– Stages of equilibra4on drives toward beJer, more advanced thinking.
development • … Piaget tried to develop an encompassing, domain independent theory
of intelligence, where changes in conceptualiza4on in mul4ple domains all
– The way children reflected common, core differences in thinking.
• Conceptual change approaches to learning are domain specific, although
think is qualita4ve the mainstream view is that the mechanisms are similar across domains.
different from adults Researchers now generally regard Piaget’s stage theory of intelligence as
perhaps his most famous, but least interes4ng contribu4on.
• From concrete • Piaget established the con4nuing, central thread of construc4vism —the
no4on that new ideas and ways of thinking emerge from old ones. This
to abstract founda4onal dynamic helped see conceptual change work proper. Piaget
also undermined older one‐sided views, including the empiricist view that
thinking knowledge originates either in purely empirical observa4ons (as claimed
by Bri4sh philosophers such as David Hume), as well as the ra4onalist
– Disequilibra4on/re‐ view that knowledge is inherently the product of rigorous thought,
independent of experience (as epitomized by Descartes). Construc4vism
equilibra4on and the astounding revela4on that children systema4cally think in very
different ways than adults cons4tute the most important threads from
– Accomoda4on/ Piage4an studies into conceptual change.” (Di Sessa, 2006, p. 4)
Assimila4on
– Construc4vism: new
ideas are built upon
old ones

12. Construc4on of new knowledge
• Jerome Bruner has developed Piaget’s idea • “The concept of prime numbers appears to
that knowledge is constructed based upon be more readily grasped when the child,
previsous experiences/knowledge and through construc4on, discovers that certain
translated it into an instruc4onal theory handfuls of beans cannot be laid out in
– Students should construct principles by completed rows and columns. Such
themselves from ac4ve explora4on and quan44es have either to be laid out in a
construc4on: single file or in an incomplete row‐column
• Instructors must present experiences they are
ready for, and mo4vated to learn
design in which there is always one extra or
• Structure the body of knowledge in a way that
one too few to fill the paJern. These
can be grasped paJerns, the child learns, happen to be
• Favor the extrac4on of principles called prime. It is easy for the child to go
– Knowledge is comprised in simultaneous from this step to the recogni4on that a
types of representa4ons (no stages of mul4ple table , so called, is a record sheet of
development, as in Piaget): quan44es in completed mul4ple rows and
– Enac4ve columns. Here is factoring, mul4plica4on and
– Iconic primes in a construc4on that can be
– Symbolic visualized.” (Bruner, 1973)
• It is a cogni4ve theory of instruc4on because
it is directly inspired by the study of the
cogni4ve development in infant made by
Piaget

13. What changes?
• “The theory theory is the claim that children or beginning students
have theories in very much the same sense that scien4sts have
them.
• While this may have been inspired by the broader analogy with the
history of science, it has onen been invoked independent of
content or process similarity.
• Carey has consistently advocated a version of the theory theory.
• With respect to another domain, theories of mind, Allison Gopnik
(Gopnik &Wellman, 1994) strongly advocates the theory theory.
• Gopnik is fairly extreme in the parallelism she claims (while s4ll
admiung some differences between scien4sts and children, such as
meta‐cogni4ve awareness); others are more conserva4ve in
allowing such differences as limits in systema4city and breadth of
applica4on (Vosniadou, 2002).” (DiSessa, 2006, p. 7‐8)

14. And how structured is the
knowledge that has to be changed?
• “Michael McCloskey (1983a, b) did a series of studies that became
perhaps the most famous of all misconcep4ons studies. He claimed
that students entered physics with a remarkably coherent and
ar4culate theory that competed directly with Newtonian physics in
instruc4on. The naïve theory, in fact, was very nearly the novice
explana4on of the toss (Figure2).
• Within McCloskey’s theory theory, he also proposed a strong content
connec4on to medieval scien4sts’ ideas, such as those of John
Buridan and early claims of Galileo.
• In contrast to others,however, he made liJle of process‐of‐change
similari4es and, for example, did not refer in anydepth to Kuhn or the
philosophy of science. His autude seemed to be that the content
connec4onto the history of science was empirically evident rather
than theore4cally mo4vated.” (DiSessa, 2006, p. 7‐8)

15. A. Gopnik: Theory theory
• In order to develop their • “…cogni4ve naturalism”, the idea that knowledge can be understood by scien4fic inves4ga4on
knowledge,children use the of the mind. It assumes, of course, some version or other of scien4fic realism. If you think
same devices as adults doing scien4fic inves4ga4on is the right course to find the truth of these ques4ons, you must think
science that scien4fic inves4ga4on is the right course to find the truth, in general.
• They both develop theories : • Suppose we apply the program of cogni4ve naturalism to scien4fic knowledge. If we do, and if
– Observe reality and form we are scien4fic realists, we must believe that there are learning mechanisms that allow
an itnerpreta4ve theory human minds to derive abstract, complex, highly structured, veridical, representa4ons and
– Make predic4ons ocherent rules, namely theories from limited input, namely evidence. They are just the mechanisms we
with the theory use in science? But if we believe this, then it is at least logically possible that those same
– Make experiences to test learning mechanisms are involved in our development of other kinds of knowledge, such as
predic4ons everyday physical, biological, psychological and even linguis4c knowledge. Moreover, recent
– Gather relevant evidence empirical developmental research suggests that this is precisely the case. Within the last ten
– Compare predic4ons with years the idea that there are deep similari4es between scien4fic theory forma4on and
evidence cogni4ve development, an idea we have called “the theory theory” has become, at the least, a
serious developmental hypothesis. The cogni4ve abili4es involved in science do seem to also
– Whether predic4ons and
evidence are in conflict be involved in everyday cogni4ve development.
seek for alterna4ve • The basic idea is that children develop their everyday knowledge of the world using the same
theories that do a beJer cogni4ve devices that adults use in science. In par4cular, children develop abstract, coherent,
job systems of en44es and rules, par4cularly causal en44es and rules.
– Eventually replace the old • That is, they develop theories. These theories enable children to make predic4ons about new
theory for a more powerful evidence, to interpret evidence, and to explain evidence. Children ac4vely experiment with
one and explore the world, tes4ng the predic4ons of the theory and gathering relevant evidence.
Some counter‐evidence to the theory is simply reinterpreted in terms of the theory.
Eventually, however, when many predic4ons of the theory are falsified, the child begins to
seek alterna4ve theories If the alterna4ve does a beJer job of predic4ng and explaining the
evidence it replaces the exis4ng theory.” (Gopnik, 2003, p. 3‐6)

16. S. Vosniadou: Theore4cal
frameworks
• The acquisi4on of • “It is argued that concepts are embedded into larger theore4cal structures
knowledge about the which constrain them.
physical world is • A dis4nc4on is drawn between a naive framework theory of physics, which is
constrained by the built early in infancy and which consists of certain fundamental ontological and
presence of framework epistemological presupposi4ons, and various specific theories which are meant
theories that bias the way to describe the internal structure of the conceptual domain within which
new informa4on is concepts are embedded.
processed and new • It is assumed that conceptual change proceeds through the gradual
concepts acquired modifica4on of one’s mental models of the physical world, achieved either
• Children do not possess through enrichment or through revision. Enrichment involves the addi4on of
theories of the physical informa4on to exis4ng conceptual structures. Revision may involve changes in
world, but rather individual beliefs or presupposi4ons or changes in the rela4onal structure of a
frameworks of theory.
presupposi4ons • Revision may happen at the level of the specific theory or at the level of the
• Change happens through framework theory.
enrichment or through
revision of beliefs and • Revision at the level of the framework theory is considered to be the most
presupposi4ons or difficult type of conceptual change and the one most likely to cause
theories and frameworks misconcep4ons. Misconcep4ons are viewed as students’ aJempts to interpret
scien4fic informa4on within an exis4ng framework theory that contains
• Revision of frameworks is informa4on contradictory to the scien4fic view.” (Visniadou, 1994, p. 46)
the most difficult process
of change

17. M. Chi: Ontologies
• Conceptual change • “many misconcep4ons are not only “in conflict” with the correct scien4fic
concerns those contents concep4ons, but moreover, they are robust in that the misconcep4ons are
of knowledge for which difficult to revise, so conceptual change is not achieved. The robustness of
change is really difficult: misconcep4ons has been demonstrated in literally thousands of studies, about
• No incremental all kinds of science concepts and phenomena, beginning with a book by Novak
informa4on, correc4ons, (1977) and a review by Driver and Easley (1978), both published almost three
tradi4onal instruc4on can decades ago. By 2004, there were over 6,000 publica4ons describing students’
produce change ideas and instruc4onal aJempts to change them (Confrey, 1990; Driver, Squires,
• Misconcep4ons are Rushworth, & Wood‐Robinson, 1994; Duit, 2004; Ram, Nersessian, & Keil,
1997), indica4ng that conceptual understanding in the presence of
robust: they make surface misconcep4ons remains a challenging problem. The daun4ng task of building
in several situa4ons and conceptual understanding in the presence of robust misconcep4ons is
can be abandoned only some4mes referred to as radical conceptual change (Carey, 1985). We propose
with great effort the opera4onal defini4on that certain misconcep4ons are robust because they
• Where the difficulty arises have been mistakenly assigned to an inappropriate lateral category. Our
from? claim, then, is that some false beliefs and flawed mental models are robustly
• Chi proposes that the resistant to change because they have been laterally or ontologically
difficult changes concern miscategorized. That is, if a misconcep4on belongs to one category and the
beliefs that have assigned correct concep4on belongs to another lateral or ontological category, then they
to the erroneous category conflict by defini4on of kind and/or ontology. This means that conceptual
• = misconcep4ons derive change requires a shin across lateral or ontological categories. In order to
from miscategoriza4ons support this claim, we have to characterize the nature of misconcep4ons and
• This fact automa4cally the nature of correct informa4on to see whether they in fact belong to two
produces a conflict categories that differ either in kind or in ontology, thereby are “in
conflict.”” (Chi, 2008, p. 72)

18. J. Minstrell: Facets of par4al, not
structured knowledge
• Children’s (non‐experts, • “In the early 70s, aner a decade of outstanding teaching…
non‐scien4sts) knowledge I Minstrell became concerned about its effec4veness. His
not structured, buJ students couldn’t transfer their formal book and lecture learning
fragmentary and local to the physics of everyday situa4ons.
• Pieces of knowledge used • … students are given two clay balls of equal size. Students agree
to deal with physics are that the two balls weight the same. But if one ball is then
facets flaJened into a pancake, many students will then say that the
• Facets derive from pancake weights more than the ball. … This is not a logical error
everyday experience but a conceptual one.
• Some facets are correct, • Unlike expert scien4sts who want to explain phenomena with a
other false minimum of assump4ons and laws, students are not driven by a
desire for conceptual economy. Their knowledge works well
enough in daily life, but it is fragmentary and local.
• Minstrell calls pieces of knowledge that are used in physics
reasoning facets. Facets are schemas and parts of schemas that
are used to reason about the physical world. Students typically
choose and apply facets in the basis of the most striking surface
features of a problem. They derive their naïve facets from
everyday experience. Such facets are useful in par4cular
situa4ons; however, they are most likely false in general, and for
the most part they are only loosely interrelated. Thus students
can quickly fall into contradic4ons.” (Bruer, 1993, p. 162‐163)

19. diSessa: Knowledge in pieces
• Knowledge is in pieces • “From an instruc4onal perspec4ve, Minstrell (1982, 1989)
• All pieces are not incorrect viewed intui4ve ideas asresources much more than blocks to
• Pieces are not coherently conceptual change in physics, in contrast with thepredominant
structured, but only misconcep4ons point of view. He described intui4ve ideas as
loosely threads that, ratherthan rejec4ng, need reweaving into a
different, stronger, and more norma4ve conceptual fabric.
• Pieces can be highly • Recent work has charted hundreds of “facets”—which are
contextual: be create on elemental and instruc4onally relevan4deas students have upon
the spot entering instruc4on—in many topics in physics instruc4on (Hunt
& Minstrell, 1994).
• Coherent naive theories are nowhere to be seen in this view.In
the same book in which McCloskey provided perhaps his
defini4ve statement of “naïve theories,” diSessa (1983)
introduced the idea that intui4ve physics consisted largely
of hundreds or thousands of elements, called p‐prims, at
roughly the size‐scale of Minstrell’s facets.
• P‐prims are explanatorily primi4ve, provide people with their
sense of which events are natural, which are surprising, and
why. P‐prims are many, loosely organized and some4mes highly
contextual, so that the word “theory” is highly inappropriate. P‐
prims are hypothesized to playmany produc4ve roles in learning
physics.” (DiSessa, 2006, p. 11)

20. How to produce a change?
• “Ra4onal models hold that students, like scien4sts, maintain
current ideas unless there are good(ra4onal) reasons to abandon
them.
• Posner, Strike, Hewson, and Gertzog (1982) established the first
and possibly mos4mportant standard in ra4onal models. They
argued that students and scien4sts change theirconceptual
systems only when several condi4ons are met:
• (1) they became dissa4sfied with their prior concep4ons
(experience a “sea of anomalies” in Kuhn’s terms);
• (2) the new concep4on is intelligible ;
• (3) the new concep4on should be more than intelligible, it should
be plausible ;
• (4) the new concep4on should appear fruiwul for future
pursuits.” (DiSessa, 2006, p. 8‐9)

21. G. Posner: Conflicts and ra4onal
choices
• Children change • “Our central commitment in this study is that learning is a
their views only ra4onal ac4vity. That is, learning is fundamentally coming
when a conflict to comprehend and accept ideas because they are seen as
arises, that is, intelligible and ra4onal. Learning is thus a kind of inquiry.
when they have The student must make judgments on the basis of available
good (ra4onal) evidence. It does not, of course, follow that mo4va‐ 4onal
reasons to change or affec4ve variables are unimportant to the learning
their mind process. The claim that learning is a ra4onal ac4vity is
• And children meant to focus aJen4on on what learning is, not what
change their mind learning depends on. Learning is concerned with ideas,
in accord with the their structure and the evidence for them. It is not simply
most ra4onal the acquisi4on of a set of correct responses, a verbal
hypothesis repertoire or a set of behaviors. We believe it follows that
learning, like inquiry, is best viewed as a process of
conceptual change. The basic ques4on concerns how
students’ concep4ons change under the impact of new
ideas and new evidence.” (Posner, et al., 1982, p. 212)

22. J. Minstrell: Conflict and analogy
• Instructors should help • “… the trick is to iden4fy the students’ correct intui4ons – their
students iden4fying their facets that are consistent with formal science – and then build
facts, correct and on these.
erroneous • …Some facts are anchors for instruc4on; others are target for
• Erroneous facts are put in change.” (Bruer, 1993, p. 162‐163)
conflict with experiences, • “In a benchmark lesson, the teacher and the students dissect
and their limits revealed their qualita4ve reasoning about vivid, everyday physics
• Correct facts are iden4fied problems into facets. They become aware of the limita4ons of
and used to create good each facet, and they iden4fy which facets are useful for
explana4ons understanding a par4cular phenomenon. Minstrell calls two
students to the front to help conduct the crucial experiment.
Such demonstra4ons are drama4c and exci4ng for the students
and allow them to see which predic4on is correct.
• Research also suggests that such experiences have an important
cogni4ve role in inducing conceptual change. They provide an
ini4al experience that places naïve and expert theories in
conflict. As the students try to resolve the conflict, the drama4c
demonstra4on serves as an organizing structures in long‐term
memory (an anchor) around which schemas can be changed and
reorganized (Hunt 1993).” (Bruer, 1993, p. 164‐166)

23. J. Clement: Use correct intui4ons and
analogies
• Analogical teaching • “Within the past decade and a half there has been an increasing
strategy awareness of the detrimental effects (to school learning) of
– Expose misconcep4ons some of students’ prior knowledge. Students come to class with
through appropriate preconcep4ons which inhibit the acquisi4on of content
ques4ons; e.g. no knowledge and are onen quite resistant to remedia4on …
upward force on a book
res4ng on a table • For several years we have been tes4ng an analogical teaching
– Find an analogy (e.g. strategy which aJempts to build on students’ exis4ng valid
hand holding up the physical intui4ons.
book) • … build on students concep4ons in order to change their
concep4ons…
• … we intend to increase the range of applica4on of the useful
intui4ons and decrease the range of applica4on of the
detrimental intui4ons…
• By establishing analogical connec4ons between situa4ons
students ini4ally view as not analogous, students may be able to
extend their valid intui4ons to ini4ally troublesome target
situa4ons. This strategy, called the bridging strategy, has been
used in tutoring, computer tutoring and classroom instruc4on,
with some apparent success…
• The first step in the bridging strategy is to make the
misconcep4on explicit by means of target ques4on….
• The next step is to suggest a case which the instructor views as
analogous … which will appeal to the student’s intui4on. We call
such a situa4on an anchoring example...” (Brown & Clement,
1989, p. 238‐239)

24. di Sessa: analogous mechanisms in new
theory building and conceptual change
• diSessa has proposed an alterna4ve • “A dis4nc4ve characteris4c of the knowledge in pieces perspec4ve is that the reasons
to the idea that the difficulty is for difficulty of change may be the same in cases where a conceptual structure evolves
represented by the change, thus by from scratch, compared to cases where one conceptual system emerges from a
the presence of a previous theory different one (theory change).
– Mechanisms consist in change of • Theory theory views and knowledge I npieces prescribe some strong differences in
theory: coalescence of separate strategy and process (e.g., ra4onal decision‐making vs. a long period of mul4‐context
pieces, dis4nc4on of pieces, etc. accumula4on and coordina4on)”. (diSessa, 2006, p. 14)
• The difficulty is not inherent to
previous structures: collec4ng and
coordina4ng pieces is difficult even • «1. Instruc4on is a complex mixture of design and theory, and good intui4ve design can
in the absence of a compe4tor override the power of theory to prescribe or explain successful methods. Almost all
reported innova4ve interven4ons work; almost none of them lead to improvements
– The same difficul4es can be that dis4nguish them categorically from other good instruc4on.
present when a system is created
from scratch from observa4on • 2. The very general construc4vist heuris4c of paying aJen4on to naïve ideas seems
and when a system requires a powerful, independent of the details of conceptual change theory. Interven4ons that
change merely teach teachers about naïve ideas have been surprisingly successful.
• Different strategies of “remedia4on”, • 3. Researchers of different theore4cal persuasions onen advocate similar instruc4onal
but no evidence about what’s beJer, strategies, if for different reasons. Both adherents of knowledge in pieces and of theory
and why theories advocate student discussion, whether to draw out and reweave elements of
naïve knowledge, or to make students aware of their prior theories in prepara4on for
judgment in comparison to instructed ideas. The use of instruc4onal analogies,
metaphors, and visual models is widespread and not theory‐dis4nc4ve.
• 4. Many or most interven4ons rely primarily on pre/post evalua4ons, which do liJle to
evaluate specific processes of conceptual change. » (diSessa, 2006, p. 14)

25. Educa4onal research, cogni4ve
psychology, and instruc4on
• Posi4ve impact of • “One of the great posi4ve influences of
conceptual change misconcep4ons studies was bringing the importance
studies: of educa4onal research into prac4cal instruc4onal
– Impact of conceptual circles. Educators saw vivid examples of students
change research upon responding to apparently simple, core conceptual
the interest of ques4ons in non‐norma4ve ways. Poor performance
instruc4on for research in response to such basic ques4ons, onen years into
– Undermining of the theinstruc4onal process, could not be dismissed. One
tabula rasa view
– AJen4on for specific
did not need refined theories to understand
contents of learning theapparent cause: entrenched, “deeply held,” but
false prior ideas. The obvious solu4on was veryonen
• But: phrased, as in the quota4on heading this sec4on, in
– Not tested enough terms of “overcoming,” or in terms of convincing
– Confusion on the students to abandon prior concep4ons.” (DiSessa,
no4on of
« conceptual » and of 2006, p. 7)
« theory »

26. What works, and why
• An example of • “In 1986 Minstrell ini4ated a collabora4on with Earl Hunt, a
collabora4on between cogni4ve psychologist … to refine and assess his classroom
educators and cogni4ve method. …
scien4sts • A comparison of students’ scores on pretests and posJests
• A good ques4on: It works, makes it clear that that Minstrell’s method works. The students
but why? learn physics. But why does it work?
• One concern is whether the method’s success depends en4rely
on Jim Minstrell’s pedagogical talents.
• Could someone other than Minstrell use the method
successfully?
• Is the Minstrell’s method beJer than other instruc4onal
methods currently in use?
• Hunt… has begun a research program back in his laboratory to
refine the theory underlying Minstrell’s method. Why are
benchmark lessons so important? How does the transfer
occurs? How do students develop deep representa4ons and
make appropriate generaliza4ons? .” (Bruer, 1993, p. 168‐169)

27. GOOD LEARNING
‐ LEARNING WITH UNDERSTANDING
‐ LEARNING FOR TRANSFER
‐ EXPERTISE
‐ INTELLIGENT NOVICES

28. Learning deep
• “Let us now ask how in our system of educa4on we are to guard
against this mental dryrot. We enunciate two educa4onal
commandments, "Do not teach too many subjects," and again, "What • Good learning implies
you teach, teach thoroughly." the understanding of
• The result of teaching small parts of a large number of subjects is the how it can be used in
passive recep4on of disconnected ideas, not illumined with any spark real life and in different
of vitality. Let the main ideas which are introduced into a child's circumstances
educa4on be few and important, and let them be thrown into every
combinaQon possible. • Understanding is useful
• The child should make them his own, and should understand their • Understanding requires
applica4on here and now in the circumstances of his actual life. deep learning: few
• From the very beginning of his educa4on, the child should experience ideas thrown in every
the joy of discovery. The discovery which he has to make, is that possible combina4on
general ideas give an understanding of that stream of events which
pours through his life, which is his life. By understanding I mean more • Avoid the superficial
than a mere logical analysis, though that is included. instruc4on of
• I mean "understanding' in the sense in which it is used in the French disconnected ideas
proverb, "To understand all, is to forgive all." Pedants sneer at an
educa4on which is useful. But if educa4on is not useful, what is it? Is
it a talent, to be hidden away in a napkin? Of course, educa4on should
be useful, whatever your aim in life. It was useful to Saint Augus4ne
and it was useful to Napoleon. It is useful, because understanding is
useful.” (Whitehead, 1929)

29. Learning as experience
• “The subject‐maJer of educa4on • To imposi4on from above is opposed
consists of bodies of informa4on and expression and cul4va4on of
of skills that have been worked out in individuality;
the past; therefore, the chief business • to external discipline is opposed free
of the school is to transmit them to ac4vity;
the new genera4on. In the past,
there have also been developed • to learning from texts and teachers,
learning through experience,
standards and rules of
conduct...Finally, the general paJern • to acquisi4on of isolated skills and
of school organiza4on (by which I techniques by drill, is opposed
mean the rela4ons of pupils to one acquisi4on of them as means of
another and to the teachers) aJaining ends which make direct vital
cons4tutes the school a kind of appeal;
ins4tu4on sharply marked off from • to prepara4on for a more or less remote
other social ins4tu4ons” (Dewey, future is opposed making the most of
1938) the opportuni4es of present life;
• to sta4c aims and materials is opposed
acquaintance with a changing
world.” (Dewey, 1938‐1997)

30. Good learning
Understanding Transfer
Intelligent
Exper4se
novices
(New science of learning)

31. Learning for understanding
• “One of the hallmarks of the new science of learning • Bransford and colleagues at Vanderbilt University
is its emphasis on learning with understanding. have been inspired by the no4on of learning as
Intui4vely, understanding is good, but it has been experience and by the no4on of learning deep and
difficult to study from a scien4fic perspec4ve. At the have developed the no4on of anchored instruc4on
same 4me, students onen have limited and situated cogni4on
opportuni4es to understand or make sense of topics – E.g. in the Jasper Woodbury adventures series
because many curricula have emphasized memory – The program seems to work
rather than understanding. – But it must face a problem of transfer
• The new science of learning does not deny that facts – Introduc4on of varia4ons
are important for thinking and problem solving. – Varia4ons are not enough
Research on experQse in areas such as chess, – Meta‐cogni4on
history, science, and mathema4cs demonstrate that
experts' abili4es to think and solve problems
depend strongly on a rich body of knowledge about
subject maJer (e.g., Chase and Simon, 1973; Chi et
al., 1981; deGroot, 1965). However, the research
also shows clearly that "usable knowledge" is not
the same as a mere list of disconnected facts.
• Experts' knowledge is connected and organized
around important concepts (e.g., Newton's second
law of mo4on); it is "condi4onalized" to specify the
contexts in which it is applicable; it supports
understanding and transfer (to other contexts)
rather than only the ability to
remember.” (Bransford, et al., 2000)

32. Learning for understanding
• “For example, people who are knowledgeable about veins and arteries know more
than the facts noted above: they also understand why veins and arteries have
par4cular proper4es. They know that blood pumped from the heart exits in spurts
and that the elas4city of the arteries helps accommodate pressure changes. They
know that blood from the heart needs to move upward (to the brain) as well as
downward and that the elas4city of an artery permits it to func4on as a one‐way
valve that closes at the end of each spurt and prevents the blood from flowing
backward. Because they understand rela4onships between the structure and
func4on of veins and arteries, knowledgeable individuals are more likely to be able
to use what they have learned to solve novel problems—to show evidence of
transfer. For example, imagine being asked to design an ar4ficial artery—would it
have to be elas4c? Why or why not? An understanding of reasons for the
proper4es of arteries suggests that elas4city may not be necessary—perhaps the
problem can be solved by crea4ng a conduit that is strong enough to handle the
pressure of spurts from the heart and also func4on as a one‐way valve. An
understanding of veins and arteries does not guarantee an answer to this design
ques4on, but it does support thinking about alterna4ves that are not readily
available if one only memorizes facts (Bransford and Stein, 1993).” (Bransford, et
al., 2000, p. 8)

33. The problem of transfer
• “Imagine that a small, peaceful • Transfer = applying old knowledge to
country is being threatened by a a situa4on or task that is sufficiently
large, belligerent neighbor. The small novel that it also requires learning
country is unprepared historically, new knowledge
temperamentally, and militarily to • The problem of transfer raises the
defend itself; however, it has among problem of which skills transfer
its ci4zens the world’s reigning chess
champion. The prime minister
decides that his country only chance
is to outwit its aggressive neighbor.
Reasoning that the chess champion is
a formidable strategic thinker and a
den tac4cian … the prime minister
asks him to assume responsibility for
defending the country. Can the chess
champion save his country from
invasion? ” (Bruer, 1993, p. 53)

34. The chess player is good at playing
chess
• Transfer from one domain of exper4se to • “In one study, a chess master, a Class A player
another is not automa4c (good but not a master), and a novice were
given 5 seconds to view a chess board
posi4on from the middle of a chess game.
Aner 5 seconds the board was covered, and
each par4cipant aJempted to reconstruct
the board posi4on on another board. This
procedure was repeated for mul4ple trials
un4l everyone received a perfect score. On
the first trial, the master player correctly
placed many more pieces than the Class A
player, who in turn placed more than the
novice: 16, 8, and 4, respec4vely.
• However, these results occurred only when
the chess pieces were arranged in
configura4ons that conformed to meaningful
games of chess. When chess pieces were
randomized and presented for 5 seconds, the
recall of the chess master and Class A player
were the same as the novice—they placed
from 2 to 3 posi4ons correctly.
• ” (Bransford, et al., 2000, p. 23)

35. Can general capaci4es be trained? No: domain‐
specificity of exper4se
• « As computers developed, there was an effort within psychology and
Training and learning cogni4ve science tp produce models of mental processes in the form of
computer programs. A early example was the General Problem Solver
are domain‐specific (Newell, Shaw, & Simon, 1958)
• … demonstrated that rela4vely few basic principles could be used to
produce a program capable of proving a broad range of mathema4cal
theorems. Many followers believed that the GPS simula4on of the human
mind indicated that humans needed to acquire only a few general
principles to solve a wide range of complex problems.
• Instead, it was revealed that a great deal of informa4on about the
specific domain of applica4on was needed for problem solu4on within
that domain.
• When applied to humans, this view led to the concept of exper4se based
on a large amount of domain‐specific learning, acquired with prac4ce and
stored in seman4c memory (Chi, Glaser & Farr, 1988).
• Research on human chess masters led Herbert Simon (1969) to conclude
that their skills were based en4rely on knowledge about chess and not
on any general ability, either innate or learned.
• On the bais of his analyses on chess masters, Siamon reasoned that up to
50000 hours of training was necessary to develop the seman4c memory
of chess that allowed the master to do so well…
• Perhaps, the most persuasive evidence of the power of exper4se was in
the training of several students to exhibit a memory span of up to 100
digits (Ericsson & Chase, 1982) … When they were swithched to
remembering leJers, their memory span fell back to the usual
seven…» (Posner & Rothbart, 2007, p. 14‐15)

36. No far transfer aner training
• Training memory enhances memory on • “Ericsson et al. (1980) worked extensively
trained domains with a college student for well over a year,
increasing his capacity to remember digit
strings (e.g., 982761093 …). As expected, at
the outset he could remember only about
seven numbers. Aner prac4ce, he could
remember 70 or more; see Figure 3.1. How?
Did he develop a general skill analogous to
strengthening a "mental muscle?" No, what
happened was that he learned to use his
specific background knowledge to "chunk"
informa4on into meaningful groups. The
student had extensive knowledge about
winning 4mes for famous track races,
including the 4mes of na4onal and world
records. For example 941003591992100
could be chunked into 94100 (9.41 seconds
for 100 yards). 3591 (3 minutes, 59.1 seconds
for a mile), etc. But it took the student a huge
amount of prac4ce before he could perform
at his final level, and when he was tested
with le#er strings, he was back to
remembering about seven
items.” (Bransford, et al., 2000, p. 40)

37. Time to learn
• Becoming an expert requires 4me • “It has been es4mated that
• Extensive training help world‐class chess masters require
construc4ng paJern recogni4on from 50,000 to 100,000 hours of
skills prac4ce to reach that level of
• PaJern recogni4on skills are exper4se; they rely on a
knowledge base containing some
rela4ve to the specific domain 50,000 familiar chess paJerns to
guide their selec4on of moves
• Time depends on mo4va4on (Chase and Simon, 1973; Simon
and Chase, 1973). Much of this
• But it is not just 4me: 4me must 4me involves the development of
paJern recogni4on skills that
be used well support the fluent iden4fica4on
– Organize the informa4on of meaningful paJerns of
– Train on varia4ons informa4on plus knowledge of
– Use metacogni4ve skills their implica4ons for future
outcomes” (Bransford, et al.
2000, p. 44)

38. Flexible transfer
• “College students were presented with the following passage about a
• But it is not just 4me: 4me must be used well general and a fortress (Gick and Holyoak, 1980:309).
– Organize the informa4on • A general wishes to capture a fortress located in the center of a country.
– Train on varia4ons There are many roads radia4ng outward from the fortress. All have been
– Use metacogni4ve skills mined so that while small groups of men can pass over the roads safely, a
– Provide explicit informa4on about underlying, common features between
large force will detonate the mines. A full‐scale direct aJack is therefore
domains between which,knowledge should be tranfered impossible. The general's solu4on is to divide his army into small groups,
send each group to the head of a different road, and have the groups
converge simultaneously on the fortress.
• Students memorized the informa4on in the passage and were then asked
to try another task, which was to solve the following problem (Gick and
Holyoak, 1980:307–308).
• You are a doctor faced with a pa4ent who has a malignant tumor in his
stomach. It is impossible to operate on the pa4ent, but unless the tumor is
destroyed the pa4ent will die. There is a kind of ray that may be used to
destroy the tumor. If the rays reach the tumor all at once and with
sufficiently high intensity, the tumor will be destroyed, but surrounding
4ssue may be damaged as well. At lower intensi4es the rays are harmless to
healthy 4ssue, but they will not affect the tumor either. What type of
procedure might be used to destroy the tumor with the rays, and at the
same 4me avoid destroying the healthy 4ssue?
• Few college students were able to solve this problem when len to their own
devices. However, over 90 percent were able to solve the tumor problem
when they were explicitly told to use informa4on about the general and the
fortress to help them. These students perceived the analogy between
dividing the troops into small units and using a number of small‐dose rays
that each converge on the same point—the cancerous 4ssue. Each ray is
too weak to harm 4ssue except at the point of convergence. Despite the
relevance of the fortress problem to the tumor problem, the informa4on
was not used spontaneously—the connec4on between the two sets of
informa4on had to be explicitly pointed out.
• ” (Bransford, et al. 2000, p. 52)

39. Exper4se
• “People who have developed exper4se in par4cular
areas are, by defini4on, able to think effec4vely • « learning scien4sts onen
about problems in those areas. conceive the problem of learning
• 1. Experts no4ce features and meaningful paJerns
of informa4on that are not no4ced by novices.
as a problem of transforming
• 2. Experts have acquired a great deal of content novices into experts by
knowledge that is organized in ways that reflect a developing their ability to reflect
deep understanding of their subject maJer.
• 3. Experts' knowledge cannot be reduced to sets of
on their own thinking … »
isolated facts or proposi4ons but, instead, reflects
contexts of applicability: that is, the knowledge is
• « A large body of cogni4ve
''condi4onalized" on a set of circumstances. science research shows that
• 4. Experts are able to flexibly retrieve important exper4se is based on:
aspects of their knowledge with liJle aJen4onal
effort. – A large and complex set of
• 5. Though experts know their disciplines representaQonal structures
thoroughly, this does not guarantee that they are – A large set of procedures and plans
able to teach others.
• 6. Experts have varying levels of flexibility in their – The ability to improvisaQonally
approach to new situa4ons.” (Bransford, et al., apply and adapt those plans to
2000, p. 19) each situaQon’s unique demands
– The ability to reflect on one’s own
cogniQve processes while they are
occurring. » (Sawyer, 2009, p. 7)

40. Adap4ve exper4se
• The concept of adap4ve exper4se (Hatano, 1990) • Intelligent novices are novices capable of becoming
provides an important model of successful learning. experts in a new domain quickly and effec4vely (in
Adap4ve experts are able to approach new comparison with other novices)
situa4ons flexibly and to learn throughout their • Meta‐cogni4ve skills and self‐regula4on seem to
life4mes. They not only use what they have learned, play a role in becoming “ready to become experts”
they are metacogni4ve and con4nually ques4on
their current levels of exper4se and aJempt to • But no shortcuts: domain knowledge remains
move beyond them. They don't simply aJempt to essen4al
do the same things more efficiently; they aJempt to
do things beJer. A major challenge for theories of
learning is to understand how par4cular kinds of
learning experiences develop adap4ve exper4se or
"virtuosos.”
• …"metacogni4on"—the ability to monitor one's
current level of understanding and decide when it is
not adequate. The concept of metacogni4on was
originally introduced in the context of studying
young children (e.g., Brown, 1980; Flavell, 1985,
1991). For example, young children onen
erroneously believe that they can remember
informa4on and hence fail to use effec4ve
strategies, such as rehearsal. The ability to recognize
the limits of one's current knowledge, then take
steps to remedy the situa4on, is extremely
important for learners at all ages.

41. Can general capaci4es be trained with
formal disciplines?
• Training of formal disciplines • « At the turn of the 20th century,
… The basic idea was that the
brain’s general capacity could be
exercised like a healthy muscle,
and that certain areas of learning,
such as logic, mathema4cs, La4n,
and Greek, were beter sources of
brain exercise than were other
areas.
• Thorndike’s ideas on associa4on
of ideas (Thorndike &
Woodworth, 1901) were used as
jus4fica4on for turning away from
the no4on that formal discipline
training would transfer to all
other school subjects » (Posner &
Rothbart, 2007, p. 13‐14)

42. Can general capaci4es be trained? Yes:
aJen4on
• « Everywhere in cogni4ve neuroscience, specific brain
networks seem to underly performance. However,
• AJen4on training some of those networks have the important property
of being able to modify the ac4vity in other networks.
For exemple, …
• .. AJen4on involves specific networks of the brain
that mature from incancy … well into childhood…
However, aJen4on also involves regula4on of the
ac4vity of other networks, thus improving the
prospects of acquiring an unlimited number of skills.
AJen4onal networks interact with other brain systems
to establish priori4es in percep4on and ac4on. This
ability to regulate brain func4on makes aJen4on
relevant to all domains of learning…
• …increases in aJen4onal efficiency can influence
progress in a wide range of school subjects. ...
• In this sense, aJen4on serves as a different kind of
formal discipline that can influence the efficiency of
opera4ons of a wide range of cogni4ve and emo4onal
networks. » (Posner & Rothbart, 2007, p. 16)

43. Self‐regula4on
• “Dis4nc4ve age‐dependent differences in how the brain reasons and learns are • We learn the same way
not found, which is why Piaget’s theory that children think and reason in through all life, but our
qualita4vely different ways at different ages is no longer accepted. However, capacity to regulate our
execu4ve func4on and self‐regulatory skills do show marked differences with behavior, including the
age during the primary school years, with par4cular developmental changes acquisi4on of informa4on and
between the ages of 3 and 7 years (e.g. Hughes, 1998; Carlson & Moses, 2001). learning, changes with the
Skills such as aJen4onal flexibility, inhibi4on (of thoughts, emo4onal development of self‐
responses, or ac4ons) and metacogni4on (insight into your own cogni4ve regula4ng func4ons
performance) become very important in explaining individual differences in • A slow development
children’s cogni4ve development. Gaining self‐regulatory skills and reflec4ve (adolescence)
awareness of one’s own cogni4on are major developmental achievements, and • Inclusive of execu4ve
are s4ll unfolding during adolescence.
func4ons (aJen4on,
• The development of self‐regula4on or “execu4ve func4on” is usually measured inhibi4on, working memory)
by tasks such as delaying the gra4fica4on of a desire, or inhibi4ng responding • And of meta‐cogni4ve abili4es
to a very salient s4mulus (Carlson & Moses, 2001). For example, Kochanska,
Murray, Jacques, Koenig and Vandegeest (1996) inves4gated 33‐ month‐old
and 46‐month‐old children’s ability to delay gra4fica4on of a desire in a
longitudinal study. In various experiments, the children were tempted to
violate par4cular standards of behaviour (e.g. they were required to hold a
sweet on their tongues for up to 30 seconds before ea4ng it). The various
tasks used formed an “inhibi4on control” baJery. Girls were found to
outperform boys at both toddler and preschool ages, and older children were
found to have beJer inhibitory control than younger children. A typical
inhibitory task involving conflict between salient responses is the “day/night”
task. Here children are shown cards depic4ng either the sun or the moon.
When they see a picture of the sun, they have to say “night”. When they see a
picture of the moon, they have to say “day”. Performance in such “conflict”
measures of inhibitory control also improves from 3 to 7 years. Efficient
inhibitory control is obviously required for effec4ve self‐regula4on.
” (Goswami, 2008b, p. 33)