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Education and Learning to Think

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Education and Learning to Think
Committee on Research in Mathematics, Science, and
Technology Education
Committee on Mathematics, Science, and Technology Education
Commission on Behavioral and Social Sciences and Education
National Research Council
Washington, D.C. 1987
Education and Learning to Think
National Academy Press2101 Constitution Avenue, NW Washington, DC 20418
NOTICE: The project that is the subject of this report was approved by the Governing Board of the
National Research Council, whose members are drawn from the councils of the National Academy
of Sciences, the National Academy of Engineering, and the Institute of Medicine. The members of
the committee responsible for the report were chosen for their special competences and with regard
for appropriate balance.
This report has been reviewed by a group other than the author according to procedures
approved by a Report Review Committee consisting of members of the National Academy of Sci-
ences, the National Academy of Engineering, and the Institute of Medicine.
The National Academy of Sciences is a private, nonprofit, self-perpetuating society of distin-
guished scholars engaged in scientific and engineering research, dedicated to the furtherance of
science and technology and to their use for the general welfare. Upon the authority of the charter
granted to it by the Congress in 1863, the Academy has a mandate that requires it to advise the fed-
eral government on scientific and technical matters. Dr. Frank Press is president of the National
Academy of Sciences.
The National Academy of Engineering was established in 1964, under the charter of the
National Academy of Sciences, as a parallel organization of outstanding engineers. It is autonomous
in its administration and in the selection of its members, sharing with the National Academy of Sci-
ences the responsibility for advising the federal government. The National Academy of Engineering
also sponsors engineering programs aimed at meeting national needs, encourages education and
research, and recognizes the superior achievements of engineers. Dr. Robert M. White is president
of the National Academy of Engineering.
The Institute of Medicine was established in 1970 by the National Academy of Sciences to
secure the services of eminent members of appropriate professions in the examination of policy mat-
ters pertaining to the health of the public. The Institute acts under the responsibility given to the
National Academy of Sciences by its congressional charter to be an adviser to the federal govern-
ment and, upon its own initiative, to identify issues of medical care, research, and education. Dr.
Samuel O. Thier is president of the Institute of Medicine.
The National Research Council was organized by the National Academy of Sciences in 1916 to
associate the broad community of science and technology with the Academy's purposes of further-
ing knowledge and advising the federal government. Functioning in accordance with general poli-
cies determined by the Academy, the Council has become the principal operating agency of both the
National Academy of Sciences and the National Academy of Engineering in providing services to
the government, the public, and the scientific and engineering communities. The Council is adminis-
tered jointly by both Academies and the Institute of Medicine. Dr. Frank Press and Dr. Robert M.
White are chairman and vice chairman, respectively, of the National Research Council.
Library of Congress Catalog Card Number 87-43107
ISBN 0-309-03785-9
First Printing, October 1987
Second Printing, January 1989
Third Printing, May 1989
Fourth Printing, November 1989
Fifth Printing, January 1991
Sixth Printing, July 1991
Seventh Printing, January 1992
Eighth Printing, July 1992
Printed in the United States of America
Education and Learning to Think
JAMES G. MARCH (Chair), Stanford University (political science)
ARNOLD B. ARONS, University of Washington (physics)
W. O. BAKER, Bell Telephone Laboratories, Inc., retired (chemistry)
MICHAEL COLE, University of California, San Diego (psychology)
MARGARET B. DAVIS, University of Minnesota (biology)
FREDERICK ERICKSON, University of Pennsylvania (anthropology)
ROBERT GLASER, University of Pittsburgh (education, psychology)
ANDREW M. GLEASON, Harvard University (mathematics)
MICHAEL A. GUILLEN, Harvard University (mathematical physics)
JILL H. LARKIN, Carnegie-Mellon University (psychology and educational
CORA B. MARRETT, University of Wisconsin (sociology)
SAMUEL J. MESSICK, Educational Testing Service, Inc., Princeton, N.J.
PAUL E. PETERSON, Brookings Institution, Washington, D.C. (political
MARE TAAGERERA, University of California, Irvine (chemistry)
DAVID E. WILEY, Northwestern University (education)
SENTA A. RAIZEN, Study Director
ROLF K. BLANK, Research Associate
Education and Learning to Think
Education and Learning to Think
The Committee on Research in Mathematics, Science, and Education was
established in the Commission on Behavioral and Social Sciences and
Education of the National Research Council in 1984 in response to a request
from the U.S. Department of Education. Its initial tasks, for that department and
the National Science Foundation, were to develop a set of research priorities
and to consider the role of multidisciplinary research for science, mathematics,
and technology education. That work resulted in two reports, Mathematics,
Science, and Technology Education: A Research Agenda (National Academy
Press, 1985) and Interdisciplinary Research in Science, Mathematics, and
Technology Education (National Academy Press, 1987).
While preparing the first report, the committee became interested in
exploring in more depth two issues: how the school environment can be
manipulated to maximize opportunities for children to succeed in learning
science and mathematics, and how children learn reasoning and other complex
thinking skills. Work on the first issue was carried out by Michael Cole, Peg
Griffen, and their colleagues at the Laboratory of Comparative Human
Cognition at the University of California at San Diego; their monograph
Contextual Factors in Education: Improving Science and Mathematics
Education for Minorities and Women was published by and is available from
the Wisconsin Center for Education Research, Madison, Wisconsin. Work on
the second issue was undertaken by Lauren Resnick at the Learning Research
and Development Center of the University of Pittsburgh and resulted in this
special monograph. Carnegie Corporation of New York is generously
supporting the distribution of both volumes.
Education and Learning to Think
Education and Learning to Think
This paper addresses the question of what American schools can do to
more effectively teach what have come to be called higher order skills.
Unlike most National Research Council documents, it is not so much a report as
the result of extended reflection upon a set of questions raised by and about the
nation's educational system. This reflection has received the guidance and
critique of a splendid working group of psychologists, educators, computer
scientists, and philosophers:
Carl Bereiter, Department of Applied Cognitive Science, Ontario Institute
for Studies in Education
John Bransford, Department of Psychology and Director, Learning
Technology Center, Vanderbilt University
Ann L. Brown, Center for the Study of Reading, University of Illinois
Jerome S. Bruner, Department of Psychology, New School for Social
Susan Carey, Department of Psychology, Massachusetts Institute of
Allan Collins, Bolt Beranek and Newman, Inc., Cambridge, Mass.
Robert H. Ennis, College of Education, University of Illinois
David Perkins, Graduate School of Education, Harvard University and
Roger Schank, Department of Computer Science, Yale University.
The working group exchanged written statements and participated in a two-
day meeting in Washington, D.C., in the fall of 1984, during which the issues
raised in the written statements were discussed at length. Members of the group
also provided guidance in
Education and Learning to Think
finding and interpreting information relevant to its concerns. Most important,
members of the working group responded to drafts of this paper; these
responses have been of great value in shaping the final version. However, what
follows is not a group report, but a personal distillation of the working group's
wisdom and advice. It should be read and used with that understanding.
Several individuals in addition to members of the working group have
been generous with their time and ideas. I would like to mention two in
particular, Carol Dweck of the University of Illinois and Mark Lepper of
Stanford University. Thanks are also due to the many who sent materials about
their own and others' work on the teaching of higher order skills and who were
willing to talk with me and, in many cases, to comment on an early draft of this
paper. A list of the individuals who responded to requests for information and
ideas appears in the appendix.
Finally, special thanks are due to Senta Raizen, study director of the
Committee on Research in Mathematics, Science, and Technology Education,
for her organization of the initial working group and overall management of the
project. Not least among her contributions was securing support for this effort
from the Carnegie Corporation of New York, whose contribution is hereby
thankfully acknowledged.
Learning Research and Development Center
University of Pittsburgh
Education and Learning to Think
Reading as a Higher Order Skill 8
Meaning Construction in Mathematics 12
Past Research 16
Current Programs for Teaching Higher Order Skills 19
Problem Solving in the Disciplines 20
General Problem-Solving Skills 21
Reading and Study Strategies 23
Self-Monitoring Skills 25
Components of Intelligence 27
Informal Logic and Critical Thinking 30
Problems of Assessment: Some General Comments 32
Embedding Thinking Skills in Academic Disciplines 35
Higher Order Approaches to the Enabling Disciplines 37
What Are Higher Order Skills? 44
Can Higher Order Thinking Be Directly Taught? 46
How Should Instruction in Higher Order Thinking Be Organized? 48
Education and Learning to Think
Education and Learning to Think
Education and Learning to Think
The question of whether schools can do a better job of teaching American
children higher order skills is very much in the air. It arises in Congressional
hearings, where calls are heard for school graduates better able to take on work
that requires responsibility and judgment. It is reflected in public concern that
changing employment demands are not being met, students' preparation for
college is less than satisfactory, and general problem-solving abilities remain
low. Yet beyond the agreement that our schools ought to be doing better than
they are at building the intellectual capabilities of American young people, it is
extremely difficult to discern what really should and can be done.
The first difficulties arise with the very question of what is meant by the
term higher order skills. Many candidate definitions are available.
Philosophers promote critical thinking and logical reasoning skills,
developmental psychologists point to metacognition, and cognitive scientists
study cognitive strategies and heuristics. Educators advocate training in study
skills and problem solving. How should we make sense of these many labels?
Do critical thinking, metacognition, cognitive strategies, and study skills refer
to the same kinds of capabilities? And how are they related to the problem-
solving abilities that mathematicians, scientists, and engineers try to teach their
students? Are intelligence tests and scholastic aptitude tests good indicators of
higher order skills, and if so, should we be
Education and Learning to Think
teaching students the kinds of things that appear on these tests? What about
artistic creativity and interpretive skill, and the ability to find and refine
problems as well as to solve those others have set? And, perhaps most troubling
of all, do any of these intellectuals' concerns really have much to do with
what the vast majority of students will do in their work and personal lives after
school? Do the higher order skills needed on the job or in the exercise of one's
rights and duties as a citizen really depend on the kinds of abilities educators
and the academic community are discussing?
Mingled with the difficulty of defining higher order skills is the troubling
sense that there may, in fact, be little new to say about the topic. Inevitably, we
hear the question: Is there really anything new about schools' trying to teach
higher order skills? Haven't schools always hoped to teach students to think
critically, to reason, to solve problems, to interpret, to refine ideas and to apply
them in creative ways? Most of us can remember a teacher who inspired us
personally in these directions, and schools everywhere include such aspirations
in their statements of goals. Nevertheless, we seem to agree that students do not
adequately learn these higher order abilities. Perhaps the fact that our schools
have been less than successful at meeting these goals means that we have
simply given up the old truths in education. Perhaps if we went back to old-
fashioned courses and old-fashioned methods, the problem of teaching higher
order skills would be solved without further special attention. Or, more
pessimistically, perhaps we should conclude that decades of trying
unsuccessfully to teach higher order skills in school show that such goals are
not reachable; perhaps higher order abilities develop elsewhere than in school,
and it would be wisest for schools to concentrate on the basics, letting higher
order abilities emerge later or under other auspices. To consider these
fundamental questions, we need a working definition of higher order skills and
an understanding of their historical role in American schools.
Thinking skills resist the precise forms of definition we have come to
associate with the setting of specified objectives for schooling. Nevertheless, it
is relatively easy to list some key features of higher order thinking. When we do
this, we become aware that, although
Education and Learning to Think
we cannot define it exactly, we can recognize higher order thinking when it
occurs. Consider the following:
Higher order thinking is nonalgorithmic. That is, the path of action is
not fully specified in advance.
Higher order thinking tends to be complex. The total path is not
visible (mentally speaking) from any single vantage point.
Higher order thinking often yields multiple solutions, each with costs
and benefits, rather than unique solutions.
Higher order thinking involves nuanced judgment and interpretation.
Higher order thinking involves the application of multiple criteria,
which sometimes conflict with one another.
Higher order thinking often involves uncertainty. Not everything that
bears on the task at hand is known.
Higher order thinking involves self-regulation of the thinking process.
We do not recognize higher order thinking in an individual when
someone else calls the plays at every step.
Higher order thinking involves imposing meaning, finding structure in
apparent disorder.
Higher order thinking is effortful. There is considerable mental work
involved in the kinds of elaborations and judgments required.
This broad characterization of higher order thinking points to a historical
fact that is often overlooked when considering the school curriculum, a fact that
helps to resolve the question of what is new about our current concerns.
American schools, like public schools in other industrialized countries, have
inherited two quite distinct educational traditionsone concerned with elite
education, the other concerned with mass education. These traditions conceived
of schooling differently, had different clienteles, and held different goals for
their students. Only in the last sixty years or so have the two traditions merged,
at least to the extent that most students now attend comprehensive schools in
which several educational programs and student groups coexist. Yet a case can
be made that the continuing and as yet unresolved tension between the goals
and methods of elite and mass education produces our current concern
regarding the teaching of higher order skills.
If we examine the educational institutions aimed at the elite in the
population, today's higher order goals are nothing new. They represent what
might be called the high literacy strand in the history of education (Resnick
and Resnick, 1977). Since there have
Education and Learning to Think
been books and writing, there also have been schools and related institutions
established to train an intellectual elite, drawn largely from privileged social
strata, in capabilities of reasoning, rhetoric, mathematical and scientific thought,
and other skills that today carry the higher order label. These were state, private,
and religious institutions with, over the centuries, extremely varied ideas of how
to go about the educational task. All were highly selective institutions. A
minority of the population attended them, and this minority was selected at least
in part on the basis of a taste for academic learning and the ability to perform
well in a very special kind of institution.
In America, various academies, some private and some public, carried
on this tradition through the nineteenth century and into the twentieth. Until
they began to be transformed early in this century, even public high schools
were in the academy mold. Only a minority of young people attended or even
thought of attending them. There were entrance examinations. The curriculum
was quite strictly academic. Extensive writing, textual criticism, and the like
were expected. Although today we might not recognize nineteenth-century
academy curricula as promoting creative thinking or independent problem
solving, the elite academies expected to produce, and to a considerable extent
succeeded in producing, intellectual performance beyond the ordinary.
Historically, it must be stressed, the academies did not treat education of
the full population of young people as within their purview. Schools for the
masses arose from different roots and are a much more recent phenomenon in
the history of education. Mass education derives from a low literacy tradition
(Resnick and Resnick, 1977) aimed at producing minimal levels of competence
in the general population. It originated in Europe in Reformation and counter-
Reformation efforts to produce a literate, catechism-and bible-reading
population. During the nineteenth century, mass schooling was adopted as part
of a new national agenda in countries that were just beginning to form citizen
armies and to impose common language and culture on their populations. In the
United States, village and township schools were established early, probably
reflecting radical Protestant traditions as well as new definitions of citizenship
appropriate to the new nation. Throughout the nineteenth century, this nation
knew levels of school attendance and literacy ahead of most other countries,
despite the continuing flow of poor and poorly educated immigrants. As cities
began to grow,
Education and Learning to Think
massive urban school systems grew as well. Only racial minorities were
systematically excluded or separated within the schools.
The mass education system that evolved under these circumstances
focused largely on elementary schooling, and rather sharp divisions between
elementary and secondary education persisted. This distinction was apparent
both in who went to school and in what was taught. Almost everyone went to
elementary school, although a limited number finished the entire eight-year
course. Only a few went to high school or its equivalent. The elementary
schools served the masses and concerned themselves with basic skills of
reading and computation, with health and citizenship training, and the like.
Routinized performance rather than creative and independent thought was
stressed. Mass education was, from its inception, concerned with inculcating
routine abilities: simple computation, reading predictable texts, reciting
religious or civic codes. It did not take as goals for its students the ability to
interpret unfamiliar texts, create material others would want and need to read,
construct convincing arguments, develop original solutions to technical or
social problems. The political conditions under which mass education
developed encouraged instead the routinization of basic skills as well as the
standardization of teaching and education institutions. Standardization was a
means of ensuring that at least minimal curriculum standards would be met, that
teachers would be hired on the basis of competency for the job rather than
political or familial affiliation, and that those responsible for the expenditure of
public funds could exercise orderly oversight over the educational process.
Standardized testing was one of the methods developed to exercise oversight
and centralized control of the schools (Resnick, 1980).
Early in the twentieth century, the institutional division between routine-
oriented elementary schools and secondary academies in the high literacy
tradition began to dissolve. Responding to changing economic and social
conditions, more and more young people began to seek high school education,
and educators gradually began to treat secondary education of a much larger
and more varied population as being their proper concern. The secondary
schools were over the next decades to become the mass institutions the
elementary schools had been. The growth of this new secondary school
population marked the beginning of a debate that continues even today. This
debate concerns what the appropriate curriculum ought to be for secondary
schools designed to serve everyone. The terms of the debate were set,
Education and Learning to Think
in great part, by a National Education Association (NEA) commission report
entitled The Cardinal Principles of Secondary Education (Bureau of Education,
1918). The report provided a theory and ideology for the place of a vocationally
oriented curriculum in the high school as part of a diversified secondary
program adapted to different types of students. This represented a clear
challenge to the older ideology that organized the high school curriculum
around a common core of the traditional liberal disciplines.
The tension between vocationalism and traditional disciplines as the center
of the high school program has never been resolved. Responding to post-World
War II manpower needs, the 1950s and early 1960s saw a greater emphasis on
traditional disciplines, especially mathematics and science. Yet political and
social pressures from many quarters sustained the demand for vocational
training and other programs designed to keep students in school as long as
possible. Other developments in the later 1960s and 1970s led to a near-
complete abandonment of the traditional core curriculum, even for students who
had been its traditional consumers. Schools continued to require academic
courses, but the requirements were often minimal and course content focused
increasingly on application and practical topicsoften replacing more
traditional, demanding material. Written composition and other activities that
engaged higher order skills all but disappeared from the curriculum.
The effect of all of this has been to reduce, and sometimes to drive out of
existence, the high literacy goals that had been the focus of the academies and
their preparatory institutions. Yet the taste for such goals has survived and can
be seen in recent efforts to revive interest in higher order skills teaching. This
revival, however, takes place in an educational and social context that dictates
an extension of high literacy goals to a much broader segment of the population
than has ever before been considered capable of such learning. Today, we are
committed to educating all Americans in the secondary schools and a large
proportion (higher than in any other country in the world) in some form of
postsecondary institution. These students' educational needs cannot be met by
traditional vocational programs that no longer prepare students for productive
participation in an increasingly diversified economic environment. Employers
today complain that they cannot count on schools and colleges to produce
young people who can move easily into more complex kinds of work. They
seem to be seeking general skills such as the ability to write and speak
effectively, the ability to learn easily on the job, the ability to use
Education and Learning to Think
quantitative skills needed to apply various tools of production and management,
the ability to read complex material, and the ability to build and evaluate
arguments. These abilities go well beyond the routinized skills of the old mass
curriculum. In fact, they are much like the abilities demanded for college-bound
students in the College Board's book, Academic Preparation for College
(College Entrance Examination Board, 1983). Yet teaching such competencies
to the mass of students remains a considerable challenge.
This, then, is part of what is new about the current drive for teaching
higher order skills. The goals of increasing thinking and reasoning ability are
old ones for educators. Such abilities have been the goals of some schools at
least since the time of Plato. But these goals were part of the high literacy
tradition; they did not, by and large, apply to the more recent schools for the
masses. Although it is not new to include thinking, problem solving, and
reasoning in someone's school curriculum, it is new to include it in everyone's
curriculum. It is new to take seriously the aspiration of making thinking and
problem solving a regular part of a school program for all of the population,
even minorities, even non-English speakers, even the poor. It is a new challenge
to develop educational programs that assume that all individuals, not just an
elite, can become competent thinkers.
This challenge comes at a time when we also have new knowledge about
the nature of thinking and strong hints about how thinking abilities are learned.
In the last decade or two, cognitive science research has allowed us to look into
the thinking mind, figuratively at least, and to specify more precisely the
reasoning processes of both successful and less successful thinkers (Newell and
Estes, 1983). More recently, researchers have begun to investigate how the
ability and the propensity to think well are acquired and maintained. These two
bodies of researchon the nature of human thinking and on the acquisition of
thinking and learning skillsare beginning to make explicit what we mean by
higher order skills and what means of cultivating such skills are most likely to
be successful. This process of making explicit the abilities formerly left to the
intuitions of gifted learners and teachers is precisely what we need to establish a
Education and Learning to Think
foundation for the new agenda of extending thinking and reasoning abilities to
all segments of the population.
The most important single message of modern research on the nature of
thinking is that the kinds of activities traditionally associated with thinking are
not limited to advanced levels of development. Instead, these activities are an
intimate part of even elementary levels of reading, mathematics, and other
branches of learningwhen learning is proceeding well. In fact, the term
higher order skills is probably itself fundamentally misleading, for it suggests
that another set of skills, presumably called lower order, needs to come first.
This assumptionthat there is a sequence from lower level activities that do not
require much independent thinking or judgment to higher level ones that do
colors much educational theory and practice. Implicitly at least, it justifies long
years of drill on the basics before thinking and problem solving are
demanded. Cognitive research on the nature of basic skills such as reading and
mathematics provides a fundamental challenge to this assumption. Indeed,
research suggests that failure to cultivate aspects of thinking such as those listed
in our working definition of higher order skills may be the source of major
learning difficulties even in elementary school.
The process of understanding a written text, as it emerges in current
psychological and artificial intelligence accounts, is one in which a reader uses
a combination of what is written, what he or she already knows, and various
general processes (e.g., making inferences, noting connections, checking and
organizing) to construct a plausible representation of what the author
presumably had in mind (e.g., Just and Carpenter, 1980; Perfetti, 1985; vanDijk
and Kintsch, 1983). The mental representation constructed by the reader does
not match the text itself, nor does the reader even try to match it, except under
special circumstances. Instead, the reader tries to represent the situation the
author had in mind or the argument the author hoped to build. The reader's
representation omits details that do not seem central to the message. It also adds
information needed to make the message coherent and sensible. The written
text, then, is a vehicle that permits a partially common representation of some
situation or argument to be constructed by two separate mindsthe writer's and
the reader's.
Education and Learning to Think
By their nature, normal, well-written texts are incomplete expressions of
the author's mental representation. They leave out some things essential to the
representation on the assumption that readers will fill them in. If this
assumption is not met, comprehension failseven if every word and every
sentence has been individually understood. Usually, this process of filling in is
so automatic that skilled readers are quite unaware they are doing it. Only when
the flow of comprehension breaks down do competent readers become aware of
their inferential and interpretive processes. Yet our models of skilled
comprehension suggest that inferences are being drawn and interpretations are
being made throughout. And studies of eye movements during silent reading, of
pause patterns as texts are read aloud, and of disruptions in comprehension
caused by minor modifications at key points in the text provide convincing
evidence of the reader's inferential work even for quite simple texts.
Four kinds of knowledge are called upon as readers construct meanings for
texts. The first is linguistic knowledge: knowledge about how sentences are
formed, rules of forward and backward reference, and the like. This knowledge
is often only implicit, but readers depend on it to find common referents, to link
agent to action to object, and to otherwise construct a representation of a
coherent set of events and relationships. The second kind of knowledge is
topical knowledge, that is, knowledge about the text's subject matter. Like
linguistic knowledge, topical knowledge is often used so automatically that
readers are unaware of its contribution. Third, readers invoke knowledge about
rules of inference. This knowledge, too, is likely to be implicit for the skilled
reader. Finally, knowledge of conventional rhetorical structures often aids the
process of text interpretation.
An example drawn from the work of Walter Kintsch (1979) demonstrates
the role of the first three kinds of knowledge in reading comprehension and
shows how interactive they are:
The Swazi tribe was at war with a neighboring tribe because of a dispute over
some cattle. Among the warriors were two unmarried men named Kakra and
his younger brother Gum. Kakra was killed in battle. According to tribal
custom, Kakra was married subsequently to the woman Ami.
The first three sentences of this short passage are understood so
effortlessly that the reader does not notice the special linguistic work required to
build a coherent representation. Yet some inference is required. Note that the
term warriors in the second sentence has not
Education and Learning to Think
appeared before. However, the definite article the that precedes the term
implies that warriors have been referred to previously. The skilled individual
knows this linguistic rule, even if only implicitly. What is more, such a reader
infers the required referent by using topical knowledge: namely, that a war
(which is referred to in the preceding sentence) is likely to involve warriors.
Greater difficulty is encountered when the fourth sentence is reached. The
sentence is puzzling. It seems anomalous, and even contradictory, in the context
of the preceding sentences. To know that the final sentence is anomalous, the
reader must bring topical knowledge and rules of inference to bear. The reader
knows, for example, that someone killed in battle is no longer alive. In addition,
he or she is likely to assume that marriage requires a living bridegroom. This
leads to the inference that it is impossible for Kakra to be married after the
battle. Topical knowledge and rules of inference thus lead to the sense that the
passage is incomprehensible. Yet topical knowledge can also provide the basis
for resolving the comprehension problem. The knowledge needed relates to
ghost marriage, a tribal custom in which, when the oldest son of a family dies
without heirs, his spirit is nevertheless married as planned, and his younger
brother takes his place in the marriage bed until an heir is produced.
In longer texts, knowledge about rhetorical structures also interacts with
linguistic, topical, and inference rule knowledge. Narrative stories, for example,
frequently conform to a prototypical structure in which, after a setting is
described, an initiating event sets up a situation in which a character responds
by setting a goal. In successive episodes the character attempts to attain the
goal, each attempt producing an outcome and a response to the outcome.
Extensive research on story grammars (see Stein and Trabasso, 1982) has
shown that people depend on this prototypical structure to understand and
interpret stories. Readers are sensitive to the order in which categories of
information are presented. They have difficulty recalling stories when
information is given in an order other than that specified in the idealized story
schema, andmost important as evidence that this story schema plays a key
role in understandingpeople tend to recall story information in the order
predicted by the schema even if the version of the story they read or heard uses
a nonstandard order. Expository texts, too, follow certain standard rhetorical
forms. Structures such as compare/contrast, cause/effect, or problem/solution
provide frameworks that support and sustain communication between author
and reader. When an author uses
Education and Learning to Think
a familiar text structure, it serves as a kind of scaffolding for the reader's
interpretive work. For example, structural markers like on the other hand and
furthermore are used to signal rhetorical functions.
This broad analysis of comprehension as a meaning-imposing process that
depends on the reader's knowledge of text structure as well as linguistic, topical,
and inferential knowledge is common to all current cognitive theories of
reading. Furthermore, when studies compare successful and less successful
readers, the former always turn out both to possess more of these kinds of
knowledge and to be more likely to use that knowledge spontaneously.
Although there are important differences among theories with respect to
specific aspects of these processestheir timing, the kinds of cues that set them
in motion, the ways in which knowledge is organizedthere are no
disagreements regarding the general characterization of comprehension.
Research still does not provide a clear answer about the extent to which
meaning imposition proceeds strategically, in a deliberate, self-conscious
fashion rather than automatically and unconsciously. Much evidence suggests
that, for a skilled reader not totally new to the text's topic, most of the work to
build a text representation proceeds quite unconsciously through processes of
automatic activation. The process slows down, requires deliberate attention, and
becomes accessible to conscious awareness under special conditions: when
there is an anomaly in the text or some unusual linguistic construction; when
the topical domain is so unfamiliar that the reader lacks necessary prior
knowledge for interpretation; when a particularly complicated chain of
reasoning is presented; or when the reader wants to study and remember the text
rather than just understand it (see chapters in Mandl et al., 1984, for a
discussion of many of these issues). Some psychologists (e.g., Collins and
Smith, 1982) believe that the same processes of self-questioning, summarizing,
and the like go on in highly skilled reading as in more self-conscious reading,
but at a much faster rate. Other research (e.g., Neves and Anderson, 1981;
Newell and Rosenbloom, 1981) suggests that as readers develop automatic
skills the nature of the process actually changes and certain steps drop out. In
any case, it is evident that educators ought to aim to produce both kinds of
reading comprehension abilities among students: the ability to understand
written texts automatically and with little effort, and the capacity to apply
deliberate strategies for interpreting and remembering when the need arises.
It is striking that the processes identified in cognitive research on
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reading comprehension are related to the techniques of textual exegesis and
analysis commonly taught in high-level courses in literature, philosophy, and
other disciplines in which multiple interpretations of texts are discussed as part
of instruction. Cognitive theory, in other words, suggests that processes
traditionally reserved for advanced studentsthat is, for a minority who have
developed skill and taste for interpretive mental workmight be taught to all
readers, including young children and, perhaps especially, those who learn with
difficulty. Cognitive research suggests that these processes are what we mean
by reading comprehension. Not to teach them is to ignore the most important
aspects of reading. This convergence of cognitive research on reading with
traditional high literacy concerns offers some promise that the goal of extending
high literacy standards to the mass educational system can be achieved.
A higher order interpretation of the basic mathematics curriculum is less
straightforward than we have been able to propose for reading. Nevertheless, a
close consideration of recent research on mathematical cognition suggests that
in mathematics, as in reading, successful learners understand the task to be one
of constructing meaning, of doing interpretive work rather than routine
manipulations. In mathematics, the problem of imposing meaning takes a
special form: making sense of formal symbols and rules that are often taught as
if they were arbitrary conventions rather than expressions of fundamental
regularities and relationships among quantities and physical entities.
Recent research on mathematics learning points to an apparent paradox.
We have abundant evidence that young childreneven before attending school
develop rather robust, although simple, mathematical concepts and that they
are able to apply these concepts in a variety of practical situations. Yet school
mathematics is decidedly difficult to learn for many children. Children's first
and best-developed mathematical competence is counting (Gelman and
Gallistel, 1978). Several investigations have shown that young children are able
to use counting to solve informally a wide variety of arithmetic problems,
including problems that they have difficulty solving in school (Carraher et al.,
1985; Ginsburg, 1977). Furthermore, an examination of shortcut procedures
invented by children
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suggests an implicit understanding of several basic arithmetic principles. For
example, the min procedure (first documented by Groen and Parkman, 1972) is
an addition strategy that involves setting a mental counter at the larger of the
two addends, regardless of whether it is the first or second, and then
incrementing by the smaller. The child's use of such a procedure requires
acknowledgment, at least implicitly, of the commutativity principle of addition.
Several studies (e.g., Svenson and Hedenborg, 1979; Woods et al., 1975) have
shown that children, starting at about age seven, solve subtraction problems by
either counting down from the larger number or counting up from the smaller
number, whichever will require the fewest counts. This procedure reveals
implicit knowledge of the complementarity of addition and subtraction, which
in turn depends on thinking of the minuend (top number) as a whole, with a
decomposition into the subtrahend and the difference. These examples and
many others suggest that an intuitive understanding of many basic mathematical
principles develops early and finds expression in various kinds of practical
problem-solving tasks.
There is substantial evidence that children's difficulty in learning school
mathematics derives in large part from their failure to recognize and apply the
relations between formal rules taught in school and their own independently
developed mathematical intuitions. Part of the evidence lies in close analysis of
the kinds of errors that children typically make in the course of learning
arithmetic and, eventually, algebra. To an important degree, calculation errors
derive not from random or careless slips but from systematically applying
incorrect procedures. These incorrect rules, of course, are not taught. Children
invent them, as they do the shortcut strategies. By analyzing their incorrect rules
we can understand what children are and are not attending to as they learn
arithmetic. The most carefully studied domain of arithmetic errors is
subtraction. The kinds of errors (called bugs from their similarity to
minicomputer programs with bugs in them) that children make have been
carefully documented; these bugs serve as the basis for an artificial intelligence
program (Brown and Van Lehn, 1980) that invents the same subtraction bugs
children invent but does not invent the many other logically possible bugs not
observed in children. Because the program's performance largely matches
children's performance, its processes and knowledge base provide a theory of
what children probably know and do that leads them to buggy inventions.
According to the Brown and Van Lehn theory, children invent
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buggy procedures when they encounter problems for which they have no
complete algorithm available. This may occur because they have not yet been
taught what to do in special cases (for example, how does one borrow from a
zero?) or because they have forgotten certain steps in procedures already taught.
To respond, children engage in a form of problem solving: generating possible
actions and testing them against a list of constraints. Although this is an
intelligent problem-solving process, it produces errors because certain key
constraints are missing from the test list. The missing constraints have to do
with the meaning of the symbols; constraints regarding how the symbols ought
to look on the page (e.g., only one digit per column, borrow marks in
appropriate places) are largely obeyed. What is more, the program has no
representation at all of the quantities that are involved; it only has rules for
manipulating symbols. This suggests that children, like the program, solve
arithmetic problems by manipulating symbols while ignoring their meaning
(Resnick, 1987).
We can reach the same conclusion from an analysis of the characteristic
errors made by students learning decimal fractions (Hiebert and Wearne, 1985)
and algebra (Matz, 1982; Resnick et al., 1987; Sleeman, 1983). Research on
algebra learning shows that when thinking about transformation rules, students
rarely refer either to quantitative relationships or to problem situations that
could give meaning to algebra expressions. Not surprisingly, students are not
very skillful at the process of mathematizing, that is, at constructing links
between formal algebraic expressions and the actual situations to which they
refer (e.g., Clement, 1982). All of this points to a conclusion that current
mathematics education does not adequately engage students' interpretive and
meaning-construction capacities. This conclusion is supported by data from
national assessments (e.g., National Assessment of Educational Progress, 1983)
showing declines in students' mathematics problem-solving skills even as
calculation abilities rise. In short, most students learn mathematics as a routine
skill; they do not develop higher order capacities for organizing and interpreting
It seems likely that a less routinized approach to mathematics could
produce substantial improvements in learning. Although the evidence is limited,
it suggests that successful math learners engage in more metacognitive
behaviors (e.g., checking their own understanding of procedures, monitoring for
consistency, trying to relate new material to prior knowledge) during math
learning; they are also less likely to practice symbol manipulation rules without
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to the meaning of the symbols (Peterson et al., 1984; Resnick, 1987). Strong
math learners also engage in more task analysis (Dweck, in press); that is, they
figure out alternative strategies for attacking problems and generating solvable
subproblems. These sense-making and knowledge-extending activities parallel
those that are so well documented for high levels of reading skill. They are also
activities generally viewed as characteristic of high levels of mathematics
thinking and problem solving. Thus, we again see a convergence between the
processes identified by cognitive research and those associated with traditional
elite mathematics education.
Mathematics and reading are not unique in the extent to which high-level
performance depends on processes of monitoring one's understanding, imposing
meaning and structure, and raising questions about presented material. Much
the same story can be told about all the subject matter in the school curriculum
and about all but the most routine job performances. Recent research in science
problem solving, for example, shows that experts do not respond to problems as
they are presentedwriting equations for every relationship described and then
using routine procedures for manipulating equations. Instead, they reinterpret
the problems, recasting them in terms of general scientific principles until the
solutions become almost self-evident (Larkin et al., 1980). Expert writers treat
the process of composing an essay as a complex task of shaping a
communication that will appeal to and convince an intended audience rather
than as a simple task of writing down everything they know about a topic
(Bereiter and Scardamalia, 1982; Flower and Hayes, 1980). In the social
sciences, trained thinkers call upon a wide range of knowledge relevant to a
topic to construct proposals for action and to build justifications for those
proposals that conform to many of the classical principles of rhetorical
argumentation (Voss et al., 1983). Skilled technicians repairing equipment do
not just proceed through routine checklists; instead, they construct mental
models of complex systems and use these to reason about possible causes of
observed breakdowns and potential repairs (e.g., de Kleer and Brown, 1980).
In all of these cases, certain kinds of higher order thinking recur: experts
elaborate and reconstruct problems into new forms; they look for consistencies
and inconsistencies in proposed solutions; they
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pursue implications of initial ideas and make modifications rather than seeking
quick solutions and sticking with initial ideas; they reason by analogy to other,
similar situations. These similarities, long noted in discussions of intelligence
(see Journal of Educational Psychology, 1921; Simon, 1976; Sternberg and
Detterman, 1979) and problem solving (Tuma and Reif, 1980), lead naturally to
the question of whether there might not be some general thinking skills that
would produce improved ability to learn across many traditional curriculum
areas. If such skills exist and if we can find effective ways to teach them, we
can imagine an important increase in educational efficiency, forit would seem
a relatively narrow instructional effort might produce wide learning results.
The search for general learning skills is not a new one. both educators and
psychologists have long sought to identify and to characterize such skills, the
former because of the educational efficiency such skills could help them realize,
the latter in search of unifying characteristics of human thought. Psychological
research gives us reason to believe in the reality of general skills for learning as
well as reason to maintain a degree of skepticism. In the next section we will
review recent efforts to teach higher order skills. These efforts provide the
newest body of evidence on the question of whether such skills are teachable.
Before proceeding to that review, however, we should first consider what the
body of past research would suggest.
Psychometric research provides the best-established evidence for the
existence of cognitive skills that play a role in diverse kinds of learning. When
two or more cognitive abilities are tested, there is almost always a positive
correlation between the measures. People who do well on one ability test are, on
the average, likely to do well on the others. Virtually the only conditions under
which such a correlation is not found are those in which tests have been
specifically designed not to correlate. For example, investigators have built tests
of creativity explicitly designed to be psychometrically independent of IQ.
Tests that correlate positively are presumed to share underlying processes. The
fact that most intelligence tests do correlate strongly and that a general factor
can always be identified through statistical methods such as factor analysis
suggests that all tests have some processes in common. These common
processes are, presumably, general abilities.
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Of course, such findings only raise new questions. How do we characterize
these common processes? Is there reason to think they are teachable? When
cognitive scientists do information-processing analyses of complex skills, they
find the same kinds of basic problem-solving processes used in task after task
(Simon, 1976). For example, one of the earliest uses of computers to explore
processes of human reasoning resulted in the construction of a program that
solved symbolic logic problems. This program was called the General Problem
Solver (GPS) in the belief that its processes would play a role in solving many
kinds of problems, not just those of symbolic logic. This has turned out to be
partly true. Although GPS itself can solve only a limited range of problems, the
kinds of processes used by GPS appear over and over again in simulations of
human performance of complex tasks. Processes such as meansends analysis
(comparing one's final goal with results that would be produced by procedures
currently available), subgoal formation (forming a new goal that is easier to
solve and that is en route to the final goal), generate-and-test routines
(generating actions and testing them against constraints), and other general
problem-solving routines are used in tasks as varied as inventing buggy
arithmetic routines, planning compositions, constructing geometry proofs, and
troubleshooting electronic devices. The reason that a single artificial
intelligence program cannot solve a wide variety of problems is not that the
fundamental processes it applies are widely different across domains, but rather
that the program must apply these processes to very specific, organized bodies
of knowledge. Each simulation must build in the relevant knowledge, and so it
becomes specific to its knowledge base (see Dehn and Schank, 1982).
Other processes that appear repeatedly in analyses of complex task
performance play a kind of executive or self-regulatory role in thinking.
People use these processes to keep track of their own understanding, to initiate
review or rehearsal activities when needed, and to deliberately organize their
attention and other resources in order to learn something. These activities have
been shown to be characteristic of effective learners, good readers and writers,
and strong problem solvers. The same processes are relatively absent in younger
or less intelligent individuals. These skills are sometimes called metacognitive
skills (see Brown et al., 1983) because they operate on an individual's own
cognitive processes. They have been suggested frequently as processes that
could be taught and that would enhance learning and thinking in a wide range of
specific situations.
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The problem-solving skills identified in cognitive simulation research and
the metacognitive skills identified in developmental psychology research have
both been proposed as candidates for teaching. The hope is held out that if we
can improve specific skills through some form of direct teaching, then people's
ability to perform various kinds of learning, thinking, and problem-solving tasks
in which such skills have been observed will also improve.
On the other hand, the very body of research that has helped to identify the
candidate general skills also provides reason for questioning their educational
importance. Cognitive research yields repeated demonstrations that specific
content area knowledge plays a central role in reasoning, thinking, and learning
of all kinds. I have already alluded to several examples of the importance of
specific knowledge. Specific knowledge about a text's topic affects processes of
language comprehension, for example. Skilled science problem solvers rely on
their knowledge of scientific principles to recast problems into more elegant
and easily solvable forms. Political scientists' argumentation becomes degraded
when they know little about the particular problem or the particular part of the
world under discussion (Voss et al., 1983). Even on the tasks used to assess
general intelligence or scholastic aptitude, recent analyses have made it clear
that much depends on specific knowledge: of vocabulary, of particular number
relationships, of possible transformations of visual displays, and the like (cf.
Glaser, 1984). General skills such as breaking down a problem into simpler
problems or checking to see whether one has captured the main idea of a
passage may be impossible to apply if one does not have a store of knowledge
about similar problemsor know enough about the topic to be able to
recognize its central ideas. Of course, to appreciate the dependence of general
skills application on specific knowledge is not to deny that such general skills
exist. Yet such an understanding raises questions about the wisdom of
attempting to develop thinking skills outside the context of specific knowledge
domains. It suggests that a more promising route may be to teach thinking skills
within specific disciplines and perhaps hope for some transfer to other
disciplines as relevant knowledge is acquired.
On first consideration the hope for transfer of thinking abilities across
disciplines seems misplaced. A long history of research exists on transfer
among school subjects. Over the decades, educators have espoused a recurring
belief that certain school subject matters discipline the mind and therefore
should be taught not so much for
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their inherent value as for their efficacy in facilitating other learning. Latin was
defended for many years in these terms; mathematics and logic are often so
defended today. Most recently, computer programming has been proposed as a
way to develop general problem-solving and reasoning abilities (e.g., Papert,
1980). The view that we can expect strong transfer from learning in one area to
improvements across the board has never been well supported empirically. At
the turn of the century, Thorndike and Woodworth (1901) studied transfer
among school subjects and found that it was more efficient to study the subject
of interest (English vocabulary, for example) than to study some other subject
(e.g., Latin) that prepared one's mind. Subsequent reviews of research on
transfer of school subject matter generally have reconfirmed Thorndike and
Woodworth's finding.
Nevertheless, the history of transfer research need not be totally
discouraging; most of this research does not directly address the questions of
most concern to those whose goal is the improvement of general thinking and
learning abilities. First, the subject matter teaching in these studies has rarely
been aimed at developing transferable skill and knowledge. We thus do not
know what leverage there might be in instruction explicitly aimed at producing
general skills in the context of a particular discipline. Second, evaluations of
learning outcomes have rested mainly on what knowledge was acquired in the
transfer discipline, rather than on whether skills for acquiring knowledge in that
discipline have been enhanced. The issue of transferability of thinking and
learning skills, then, is still open.
Recently, a variety of courses and programs claiming to teach reasoning
and problem-solving abilities have emerged (see Nickerson et al., 1985; Segal
et al., 1985). These represent the newest wave of optimism concerning the
teachability of general higher order cognitive skills. Some programs focus on
problem solving and reasoning in particular disciplines. But most are aimed at
enhancing general skills or at using a combination of both approaches. Recent
programs thus offer an opportunity to update the empirical record concerning
the effects of various kinds of training in thinking and reasoning skills. In the
course of this study, nominations have been sought of programs aimed at
teaching various aspects of higher order thinking.
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A large number of programs and reports have been examined. They are
discussed here in several broad categories.
Problem Solving in the Disciplines
Faculty members in a number of disciplines have developed courses or
course-adjuncts designed to improve the problem-solving ability of students in
their disciplines. These are generally college-level programs aimed at the full
range of students in the discipline. The majority of such courses have been
developed in the physical sciences (e.g., Reif and St. John, 1979), engineering
(e.g., Fuller, 1978; Rubinstein, 1980; Woods, 1983; Woods et al., 1984), and
mathematics (e.g., Schoenfeld, 1982, 1983, 1985). Wales and Stager (1977; see
also Wales and Nardi, 1985) have proposed a general strategy, which they call
Guided Design, for teaching problem solving and decision making within the
context of a variety of subject matters. Guided Design courses have been
offered in high schools as well as colleges and in the humanities and social
sciences as well as in the physical sciences and engineering.
Problem-solving courses and programs vary considerably in scope and in
style, ranging from individual courses or laboratory programs to a multicourse
sequence spread over several years of college. The reported programs are
probably representative of similar programs being used on many campuses that
have not been formally described. Some of the programs are highly structured,
with printed materials, special lab notebooks, standard exercises, and regular
evaluations. Others are essentially suggestions to instructors, including
guidance in how to conduct classroom discussions to favor the development of
problem-solving skills.
Central to all programs is extensive practice in solving problems or in
designing and carrying out experiments. Supportive help is offered, and
problem complexity gradually increases. Some programs also teach students to
use particular heuristic strategies including special forms of problem
representation. For example, Fuller's chemical engineering course requires
students to prepare special graphical representations (Polya maps) that show a
problem's structure. Reif's laboratory requires lab reports in which students
organize hierarchically the important aspects of an experiment.
Various forms of social interaction are used, both to make visible normally
covert aspects of the problem-solving process and to increase students' self-
conscious monitoring and management of their
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thought processes. These include having the instructor think aloud while
solving problems set by students, having students work in pairs or larger teams,
and having students justify solutions to one another and evaluate each other's
solutions. Particular attention is often paid to the uncertainties of problem
solving and to the process of making and correctingrather than avoiding or
Formal evaluation of problem-solving programs is rare. The most
extensive quantitative evaluation data are presented by Wales (1979) for
freshmen for the first six years of the Guided Design program in engineering at
West Virginia University. Wales found definite rises in both freshman and four-
year grade point averages (GPAs) even after controlling for grade inflation that
occurred during the study period. Before the introduction of Guided Design,
engineering students' average freshman GPAs were below the university
average; after Guided Design, their GPAs were well above the average.
Students who had participated in the Guided Design program as freshmen also
had higher four-year GPAs than (transfer) students who had not participated.
During the same period, entering students' ACT (American College Testing
Program Assessment) scores remained roughly constant. The percentage of
students completing the four-year course also increases; thus, the grade increase
cannot be attributed to a more selective university policy. Other Guided Design
users have reported similar results.
Other problem-solving programs have not reported this kind of extensive
quantitative data, but several document favorable student evaluations of their
programs and describe examples of improved problem solving displayed by
individual students (e.g., Fuller, 1975; Reif and St. John, 1979; Woods et al.,
1984). In general, most program authors cited here can point to long-term use of
their courses on their campuses, attesting to both faculty and student
enthusiasm. Further, because these programs are designed, by and large, to
teach skills that are directly desired in their disciplines, the question of transfer
is not as relevant as for some of the other programs to be discussed.
Nevertheless, more attention to evaluation issuesand especially the use of
more informative measures than overall grade averageswould strengthen the
case for these types of courses.
General Problem-Solving Skills
Another group of programs aims to teach general problem-solving abilities
that will be applicable in many different settings.
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The CoRT Thinking Program (de Bono, 1976, 1985) and the Productive
Thinking Program (Covington, 1985, in press) represent two visible and useful
examples of this kind of program.
CoRT grows out of a tradition of training executives and designers to
increase fluency and creativity in practical problem solving (see de Bono,
1970). A version of the program suitable for schoolchildren recently has been
produced and commercially marketed. It is probably the most widely used
thinking skills program, having been translated into several languages and
officially adopted for school use in several countries. CoRT focuses on
mastering a set of attention-directing tools that, when applied, lead one to
consider multiple sides of an issue, to consider consequences, to select
objectives and weigh factors involved in a situation, to generate and evaluate
evidence, and the like. Lessons are as content-free as possiblethat is, they use
familiar situations and very short presentations to establish contexts in which
the tools can be used. A great premium is placed on quick use of taught
strategies and on the number and variety of ideas generated. De Bono refers to
this as perceptual rather than logical thinking and is more concerned with
effective real-life thinking than with improving school performance.
The Productive Thinking Program was designed specifically for upper
elementary schoolchildren. It, too, teaches a variety of strategies for planning,
managing, and monitoring one's own thinking. Although stated in quite
different language and embedded in more complex (though still nonacademic)
problem settings, the strategies taught appear similar in intent to those of the
CoRT program. Both programs seem to teach versions of the planning and
metacognitive strategies that have been identified in information-processing
research on problem solving (cf. Polson and Jeffries, 1985) along with the kind
of fluency in idea generation associated with certain definitions of creativity.
Covington's theory and program also emphasize motivation and self-concept,
helping students to think of themselves as problem solvers and to resist
immobilization caused by fear of failure.
The Productive Thinking Program has been evaluated quite extensively
over a number of years (see Covington, in press, for the most recent reports).
There is evidence that students in the program become good at generating ideas
and questions and increase their use of the planning strategies in the kinds of
problem situations on which training is given. Furthermore, trained students'
advantages last for some months. Most important, students seem to apply the
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program's planning strategies (e.g., analyzing the task, outlining an action plan)
to school tasks such as preparing a report or exhibit. However, the latter
assessments consisted of self-reports; therefore, we do not know if students
actually apply these skills in practice.
The CoRT program has been evaluated less often than its widespread
adoption might suggest. Nickerson et al. (1985, pp. 217220; see also Edwards
et al., 1984) summarize several studies; these show that students taking the
course tend to become substantially more fluent in producing ideas, may make
some progress toward higher levels of abstraction, and may take a more
balanced view of problems. Changes also often occur in students' conceptions
of themselves as learners. However, these findings come from performances on
problems very similar to those used in the CoRT training. The only assessments
of transfer to practical or school problem solving come from students who
report using the strategies in their everyday lives. Thus, judgments of CoRT's
educational value must depend on the importance one attaches to the strategies
directly taught and to ideational fluency as such. We do not have empirical
evidence of the kind of effects these have on school learning or on success in
practical problem solving, although many people feel that the CoRT program
has helped them or their children in both.
Reading and Study Strategies
Perhaps the largest set of training approaches and programs is directed at
teaching strategies for reading and studying from texts (e.g., Dansereau, 1985;
Jones et al., 1985; Jones et al., 1984; Paris et al., 1984; Weinstein and
Underwood, 1985). Programs for enhancing reading and studying skills have
been developed for virtually every educational level from elementary school to
the university. Some authors stress the study skill aspect of their programs;
others emphasize the reading skill aspect. In fact, however, it is often difficult to
distinguish between the two. Programs and research studies use different labels
to describe a common set of strategies including skimming, using context to
figure out words and meaning, self-testing to check one's understanding, and
generating summaries as one reads. The strategies taught in these programs are
all based on cognitive research in reading; they involve various kinds of
elaborations the reader can make on the basis of the text. The strategies taught
are those that have been observed in expert readers and in strong students but
that are often found to be lacking in weaker readers. They
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are also strategies that accord well with theories of reading expertise and with
cognitive science models of the reading process.
Some techniques are reminiscent of older study skill techniques. These
include special forms of notetaking intended to highlight relations among
different parts of the text's content and to help readers organize their knowledge
(Dansereau, 1985; Jones et al., 1985). In some cases, the study skills and
reading strategies are embedded in fairly extensive programs that also help
students plan their time, manage study activities, control anxiety and mood, and
apply deliberate learning strategies in typical academic study situations (e.g.,
Dansereau, 1985; Weinstein and Underwood, 1985).
Considerable effort has gone into quantitative evaluations of these strategy
training programs. Evaluation results reveal the theoretical and practical
complexities of these research efforts. Paris and his colleagues, for example,
have studied carefully the effects of training elementary schoolchildren in
strategies such as skimming, using context to figure out unfamiliar words, and
taking notes (Paris and Jacobs, 1984; Paris et al., 1984). In a series of studies,
they have shown that students became more aware of comprehension strategies
and report using them more often. On the other hand, the effect of these
improvements on general reading skill is slight when measured by traditional
comprehension measures, which typically require answering questions about
short passages. The trained children do excel in tasks that evoke deliberate
attention to the structure and meaning of the text, such as detecting errors and
filling in missing words. Because good performance on such tasks is known to
correlate well with reading comprehension, one might expect transfer to the
more commonly used passage comprehension measures. Determining why such
transfer does not occur or what additional training features might produce
transfer is likely to occupy investigators in the field for some time.
Weinstein has reported that her college-level study skills course has
positive effects on reading performance, using a general reading test. She also
documents lowered test anxiety and improvements in student-reported study
habits. Dansereau has shown similar results, using more direct study measures
in which students were given an hour to study 3,000-word passages and were
tested a week later; these tests included essay questions as well as more
standard test items. As with other programs, some evaluation problems did
exist. In both program evaluations it was difficult to establish optimal control
groups. Furthermore, the effect of a total study skills program, rather
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than the effect of a particular study strategy or teaching method, was under
scrutiny. However, Dansereau has also conducted a number of separate studies
of particular component strategies. This mixture of global evaluation with
detailed analyses of the effects of specific component strategies, pursued in a
cumulative fashion and extended so that long-term effects and transfer can be
evaluated, is precisely what we need to establish which elements of complex
programs are important to their overall effects.
Self-Monitoring Skills
Direct strategy training may be only partially helpful in increasing
performance because many individuals primarily lack good judgment regarding
when strategies should be applied. Extensive research supports this prediction.
For example, research with retarded individuals shows that it is relatively easy
to improve memory task performance by simply instructing people to rehearse
or to engage in verbal elaboration and other mnemonic activities. Typically, the
improvement comes almost immediately, suggesting that the strategies are, in
some sense, already known. However, in these studies there was almost
complete lack of transfer, even to tasks that were only slightly modified. This
meant that retarded individuals' difficulty was in not knowing when memory
strategies were called for rather than in being unable to use the strategies.
Recent training studies that focused on appropriate application of strategies
have shown more promising results (see Brown et al., 1983, for a review of this
Overuse of deliberate strategies can also be maladaptive. Reading would
be neither pleasurable nor efficient if one continuously did the kinds of
deliberate processing taught in the study skill experiments just described. These
strategies are useful when automatic processing breaks down, but they can be
very intrusive and disruptive when applied unnecessarily. The more skilled the
reader, the more likely he or she will know when to apply the strategiesand
when to avoid them. Weak readers tend to apply strategies indiscriminately,
thus disrupting comprehension, or tend to drop them entirely when there is no
longer a teacher present to insist on their use and demonstration.
Because of these observations, some investigators have suggested that
readersparticularly weak readersmight profit more from developing self-
monitoring skills than from practicing specific text
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interpretation strategies. Palincsar and Brown's (1984) work represents the most
striking advance in this direction. Working with middle-school children who
had extremely weak reading comprehension skills, they introduced a process of
reciprocal teaching in which children worked cooperatively to develop an
interpretation of a text. To facilitate interpretation, children took turns posing
questions about and summarizing the texts. Sometimes they also made
predictions about what would be said in a following section of text or asked for
clarification. The teacher modeled these processes for the children in think-
aloud form. Other group members commented on the quality of questions or
summaries and tried to help improve them. There was no practice in answering
questions or in any particular strategies for using context, analyzing words, or
the like.
Reciprocal teaching sessions were conducted daily for several weeks.
During this training period the children's skill at answering questions about
passages that they read privately also began to rise. They maintained improved
reading test performance even after an eight-week period without reciprocal
teaching sessions. Furthermore, scores on science and social studies
comprehension tests, given in the classroom rather than in the special reciprocal
teaching laboratory, also rose significantly. Comparisons with groups of
children who engaged in intensive reading practice without the reciprocal
teaching support establish the importance of reciprocal teaching in producing
these results. These levels of retention and transfer are rare in educational
intervention studies. More important, accumulating evidence demonstrates that
variants of reciprocal teaching can be effectively carried out by regular
classroom teachers as part of their normal instruction.
Other studies focusing on self-monitoring and meaning construction skills
have also shown promising although not as dramatic results as Palincsar and
Brown's (e.g., Bereiter and Bird, 1985; Collins et al., 1981; Day, 1980). In all of
these studies, learning proceeded in a social setting in which tutor and students
shared responsibility for text interpretation. The tutor modeled certain
interpretive processes; these were then taken over by students. There was some
attention to building students' awareness of their own level of understanding as
well. Schoenfeld (1985) has used a similar approach in teaching mathematics
problem solving.
The findings on reciprocal teaching and its cousins point to a promising
educational intervention. However, they also highlight how little we know
about exactly how such training produces its
Education and Learning to Think
effects. How can instruction focused on overt, self-conscious strategies that may
not be actual components of skilled performance improve normally automatic
processes? Some cognitive scientists believe that question asking and
summarizing become automated in the course of learning and are present in
skilled reading in abbreviated, fast, and therefore largely invisible form. Others
suggest that these abilities are not actively invoked during the course of
automatic comprehensionalthough they may well be used during studying
and when smooth comprehension breaks down. In that case, the monitoring
strategies taught and children's subsequent skilled reading performance would
be only indirectly related. Perhaps practice in deliberate, mindful, or
intentional reading activates certain powerful knowledge structures that can
be applied in subsequent reading. Perhaps practice mitigates emotional
difficulties associated with years of perceiving oneself as a poor reader. At
present, many explanations seem possible, but the actual learning mechanisms
have not been identified. Research has located a psychological space in which
educationally powerful effects seem to occur, but it has not yet adequately
explained what happens in the space to produce the effects. Until we can
provide a more substantial theoretical explanation, we can probably expect
mixed results from both laboratory and classroom experiments aimed at training
self-monitoring skills and strategies because it will be difficult to determine in
advance the essential components of a training approach.
Components of Intelligence
A number of programs aim to improve general intelligence through special
training. Among the best known of these are Whimbey and Lochhead's (1982,
1984) program for high school and college students, Feuerstein's Instrumental
Enrichment Program (Feuerstein et al., 1985), the Venezuela Project
Intelligence program (Bolt Beranek and Newman, 1983), and Sternberg's
(1986) program for developing practical intelligence.
The program of actually defining intelligence is addressed only indirectly
by most of these program developers. Their programs provide practice and
feedback on the kinds of tasks that usually appear in intelligence and aptitude
tests. These include vocabulary-building activities, exercises involving
synonyms and antonyms, analogies, spatial reasoning items, and certain kinds
of logic tasks of a more or
Education and Learning to Think
less puzzlelike nature. By including such tasks, the program developers
implicitly accept the validity of established tests as indicators of intelligence.
However, the history of the field (e.g., Journal of Educational Psychology,
1921; Sternberg and Detterman, 1979) shows that psychologists have never
arrived at a fully satisfactory definition of intelligence.
Recognizing this limitation, two of the programs extend their reach
substantially beyond the usual testlike tasks. Sternberg's program aims to teach
problem-solving techniques drawn from cognitive research, strategies for
memorizing and reading, various practical skills (e.g., interviewing and clinical
reasoning), and methods for overcoming emotional blocks. The program text,
intended for high school or college courses, assumes that students' performance
will improve when they receive information about psychological theories. In
this sense, it can be seen as the most recent in a series of self-improvement
courses designed by psychologists to reflect cognitive research on thinking and
problem solving (cf. Hayes, 1981; Wickelgren, 1974). The Venezuela Project
Intelligence course also includes tasks that go beyond intelligence test types of
exercises. These include lessons on the structure of language and the analysis of
arguments that are similar to material taught in the informal logic and critical
thinking programs discussed in the next section of this essay. Other lessons
cover the use of graphic, tabular, and simulation representations. A range of
problem-solving, decision-making, and design activities, similar to those
included in programs on problem solving in the disciplines, is also included. By
contrast, several programs marketed under the titles of critical thinking,
reasoning, or thinking skills are actually composed mainly of testlike
Two intelligence training programs, Whimbey and Lochhead's and
Feuerstein's, particularly stress social mediation in learning cognitive skills.
Whimbey and Lochhead suggest that their exercises be used in a pair problem-
solving process in which students alternate the roles of problem-solver
(thinking aloud) and listener-critic. The intent, as in some of the mathematics
and engineering problem-solving programs described earlier, is to make the
problem-solving process overt and to give students practice in analyzing
problems and working through errors rather than avoiding them. Feuerstein's
Instrumental Enrichment Program is intended for functionally backward
students. It tries to provide, in condensed form, the kind of
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help in explicitly analyzing tasks, formulating strategies, and evaluating
outcomes that is provided incidentally in normal development through
interaction with parents and other caretakers. In Instrumental Enrichment
training, studentteacher interaction, together with specially structured group
discussions following the completion of individual exercises, plays this
mediating role.
Adequate program evaluation is sparse, except in the case of the Venezuela
program. That program has been subjected to a fairly extensive evaluation
involving experimental and control classes in the seventh grade (students aged
1117) in barrio (impoverished urban district) schools. Evaluation
demonstrated a clear effect of the course on a verbal IQ measure and on several
general ability tests, including reading. Experimental students performed better
than control students on several measures of the skills directly taught in the
course. In addition, a smaller student sample also took special oral and written
posttests assessing qualitative aspects of thinking such as appropriateness of a
design, clarity of expression, and use of supporting reasons. Here, too, the
experimental group outperformed the control.
The special posttest in the Venezuela evaluation is important because it
examines transfer of the skills taught to educationally and practically relevant
tasks. Researchers must establish this kind of transfer whenever teaching
focuses on activities that are valued because of their association with socially
valued competence, rather than valued for their own worth. This is clearly the
case for IQ tests. These tests are used in evaluation studies because the tests are
quite good at predicting school performance. But students trained to do well on
the tests themselves will not necessarily do better in school. IQ tests probably
correlate with school performance mainly because doing well on both the IQ
tasks and school tasks depends on learning abilities and strategies not directly
observed in either. Therefore, specialized, targeted training on IQ-like tasks
may not generalize. Direct assessment of transfer is needed. Unfortunately,
apart from the promising but limited evidence from the Venezuela program,
such assessments have not been made. Performance on particular types of items
or on IQ tests as a whole has been shown to improve with training (e.g.,
Feuerstein et al., 1985; Sternberg, 1986). However, evidence that improved test
scores predict improved performance on problem solving or learning tasks
closer to those of school or real life is rare (see Lochhead, 1985, for a
perspicacious discussion of the difficulties of evaluations that include this kind
of transfer criterion).
Education and Learning to Think
Informal Logic and Critical Thinking
The final approach to the teaching of higher order skills to be considered
here emerges from a philosophical rather than a psychological tradition. In the
past several years philosophers at a number of universities have turned their
attention to problems of teaching general reasoning and argumentation skills.
Their work is rooted in ancient traditions of rhetoric and in recent work on the
logic of argumentation (see, e.g., Toulmin et al., 1979). The current focus on the
analysis of extended discourse on complex topics, usually social issues,
represents a new thrust within philosophy, offering an alternative to the
traditions of mathematical logic and formal proof. The new approaches
maintain the normative stance of philosophy; they prescribe acceptable forms of
thinking based on standards of logic. This contrasts with psychologists' efforts
to discover and then to teach students the actual processes used by good
thinkers. Philosophers promote an approach designed to discipline thinking and
to guard against the propensities of humans to accept fallacious arguments and
draw inappropriate conclusions. Indeed, the scholarly heart of the informal logic
movement is the analysis of fallacies common in undisciplined reasoning.
Most efforts to teach informal logic have focused on college-level courses.
Although organized programs at this level are uncommon, certain textbooks
that are frequently used for informal logic courses provide a reasonable sense of
the field (see Johnson, 1981, and Johnson and Blair, 1980, for reviews and
analyses of several of these texts). The books typically contain examples of
texts for analysis and often present techniques for displaying the relationships
among various segments of an argument. In most cases, the texts emphasize
identification of particular reasoning fallacies and include technical vocabulary
for describing argument structures and their associated fallacies. In addition to
philosophers, a small number of people from other disciplines are linked to the
informal logic movement. For example, rhetoric has become a major element in
many English departments; in these programs, courses in writing and
composition often concentrate on principles of argument construction (see
Lazere, 1982, for one such approach). Some social scientists (e.g., Browne and
Keeley, 1981; Hursh et al., 1983) have developed courses and textbooks in
critical thinking that share the concerns of the informal logic movement,
although not always the particular analytic vocabulary.
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Extensive attention to informal logic at the elementary and secondary
school levels is quite recent. It has been spurred by the recent press for critical
thinking in the schools and by the inclusion of critical thinking components in
some states' competency testing programs (e.g., California, Connecticut, and
New Jersey). The only fully developed and extensively assessed program for
precollege students is Matthew Lipman's Philosophy for Children. Philosophy
for Children's basic teaching method is extensive discussion organized around
issues raised in the course of storylike texts. These texts pose traditional
philosophical problemsproblems of meaning, truth, aesthetics, reality and
imagination, ethics, and the like. In this context, a variety of informal logic skills
all focused on logical relations as expressed in ordinary languageare
expected to be developed. The oldest and most widely used text, Harry
Stottlemeier's Discovery (Lipman, 1974/1982), is aimed at fifth- and sixth-grade
students. Texts exist for younger and older students as well.
This brief consideration cannot do justice to the variety of practice and
range of opinion in the critical thinking and informal logic movement. For
example, some programs focus largely on identifying and correctly labeling
reasoning fallacies; others concentrate more on developing skills of
argumentation in extended discourse, without extensive formal analysis. An
important debate in the field exactly parallels psychologists' discussions of
whether general cognitive skills or specific knowledge is most central to
intellectual competence. Most informal logic philosophers believe that general
reasoning capacity can be shaped and that it transcends specific knowledge
domains (e.g., Ennis, 1980, 1985). In an even stronger claim, Paul (1982, in
press) argues that we should seek to develop in students a broadly rational
personality rather than any set of technical reasoning skills. This view usually,
but not always, supports calls for independent critical thinking courses.
However, a competing view, most strongly stated by McPeck (1981), argues
that no general reasoning skill is possible and that all instruction in thinking
should be situated in particular disciplines. Despite their parallel concerns,
psychologists studying the teachability of cognitive skills and philosophers
promoting critical thinking instruction have communicated very little with one
another. That is beginning to change, with each group expressing more interest
in the other's work (e.g., Norris, 1985; Perkins, 1982), and more mutual
influence is probable in the future.
The college-level courses discussed here have enjoyed little or no formal
assessment apart from regular course examinations. There is
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an implicit claim that the kinds of analysis taught in informal logic courses can
and should permeate performance throughout the university curriculum,
although this has not been tested empirically. As in the case of science, math,
and engineering problem-solving courses, then, judgments of the educational
importance of university-level informal logic courses must depend for the
moment on the extent to which the forms of argument analysis taught are
judged to be valuable aspects of learning in their own right. Several evaluations
of Philosophy for Children, most of which were conducted by evaluators not
directly connected with program development or implementation, provide
evidence that the programwhen well implemented and given adequate time in
the instructional calendarcan produce rather general gains on tests, including
improvement on reading comprehension and IQ scores (Lipman, 1985). This
program, then, more than most, has been subjected to evaluations on a transfer
criterion and has fared quite well.
Before summarizing the evidence on the teachability of general thinking
skills, it is important to reflect on the question of what constitutes appropriate
evaluation of programs designed to teach problem-solving and reasoning skills.
The most common evaluation reported for the programs we have considered is
mastery performance (Arbitman-Smith et al., 1984), that is, performance on
exercises similar to those included in the program itself. In other words,
evaluation provides evidence that students who have used a program learn to do
the things the program teaches. This is a necessary first evaluation step, a
minimal test that the program in question is worthwhile. Although necessary,
such evidence is rarely sufficient to establish the program's educational value. If
the program teaches skills that are in themselves considered valuable, then clear
evidence that students learn and maintain those skills is adequate. But if a
program is meant to teach skills that facilitate other learning but are not valued
in themselves, then more is needed than merely tests of the performances
directly taught. In these cases, assessments of transfer beyond the course or
program itself must be included. Various measures of such transfer can be used,
including standardized test scores, subsequent grade point averages, measures
of course retention, or advanced program placement. What matters is that the
ultimate measures assess socially valued performances.
Education and Learning to Think
There are strong theoretical and practical reasons for this. Even when two
measures have been correlated repeatedlyfor example, Scholastic Aptitude
Test (SAT) scores and college gradesnothing guarantees that the correlation
will still exist if conditions leading to high scores in either measure are changed.
Under normal learning conditions it is safe and practical to treat SAT scores as
an indicator of probable college grades. But if special, targeted training
produces an increase in SAT scores, one cannot safely assume that college
grades will also go up. The correlation was established under particular learning
conditions; if those conditions change, the correlation must be reestablished by
verifying empirically that the program producing increased SAT scores also
produces increased college grades. The same is true for metacognitive skills
associated with reading. We know that students who perform well on
standardized reading tests usually exhibit more metacognitive behaviors such as
elaborating on what the text says, summarizing as they read, and raising
questions. But this does not necessarily mean that if we teach students to
elaborate, to summarize, and to ask questions, their reading test scores will go
up. Useful evaluations of higher order skill training programs require that the
educational outcomes of interest be directly assessed. We cannot afford to rely
on evidence that certain performances traditionally associated with strong
educational outcomes have improved.
On this criterion, even reading tests, probably the most frequently used
measure in the studies reviewed, are somewhat problematic. These tests
examine abilities that are themselves valued. They are thus better for evaluation
purposes than intelligence tests. However, many of the higher order training
programs aspire to types and levels of cognitive functioning to which
standardized reading tests are not likely to be adequately sensitive. How, for
example, should we assess whether skills of argument analysis have permeated
students' study of the social sciences or their reading of the daily newspapers?
How can we determine whether the problem-solving skills taught in a high
school or freshman college course have altered performance in science courses
or on-the-job creativity? A crude (and not infrequently used) indicator of
academic improvement is course grades. But even grades are only indirect
indicators of changed cognitive abilities. They do not reveal the quality of
thinking, and they offer no indications of transfer beyond purely academic
Clearly, a most important challenge facing the movement for increasing
higher order skill learning in the schools is the development
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of appropriate evaluation strategies. Part of the problem is our penchant for
testing. American pressures for standardized testing, especially at the
elementary and secondary school levels, make it difficult for curriculum
reforms that do not produce test score gains to survive. But most current tests
favor students who have acquired lots of factual knowledge and do little to
assess either the coherence and utility of that knowledge or the students' ability
to use it to reason, solve problems, and the like. To the extent that educators are
motivated to produce high test scores, such tests can have the effect of
suppressing efforts to expand higher order skill teaching. As interest in thinking
and reasoning skills has increased, there has been growing effort to include
thinking and reasoning in the batteries of tests given to students. Several states
now have or will soon have such tests as part of their state competency testing
programs. So far, however, these tests appear to be very limited vehicles for
assessing or promoting the kinds of higher order thinking discussed here. They
consist mostly of isolated items that test students' critical thinking and reasoning
knowledge. But they do not provide the scope or the opportunity for students to
carry out extended analyses, to solve open-ended problems, or to display
command of complex relationships, although these abilities are at the heart of
higher order competence. It seems likely that assessments of forms of thinking
that we recognize to involve nuance, judgment, and weighing of alternatives
rather than fixed answers will require techniques that themselves depend on
judgment and that are open to alternative interpretations.
How can we summarize the evidence reviewed in the preceding section,
and what does it suggest to educators wishing to improve their students'
thinking abilities? It is clear that if we were to demand solid empirical evidence
supporting a particular approach to higher order skill development before
implementing educational programs, we would be condemned at this time to
inaction. There is far less empirical evidence of any kind available than we
might have imagined and the evidence we have is often of limited utility. In
most cases, the evidence amounts mainly to data showing that students who
have taken particular courses are more likely to perform well on the tasks
directly taught in the courses than students who have not taken those courses.
Only a few studies have assessed the key
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question of generalization to other parts of the school curriculum or out-of-
school performance.
Although we cannot offer a seal of approval for any particular approach,
the cumulative evidence justifies cautious optimism for the venture as a whole.
Thinking and problem-solving programs within the academic disciplines seem
to meet their internal goals and perhaps even boost performance more generally.
It seems possible to raise reading competence by a variety of methods, ranging
from study skill training through the reciprocal teaching methods of Brown and
Palincsar to the discussions of philosophical texts in Lipman's program. On the
other hand, general improvements in problem-solving, rhetoric, or other general
thinking abilities have rarely been demonstrated, perhaps because few
evaluators have included convincing assessments of these abilities in their
Most programs reviewed here represent efforts to improve thinking skills
through the addition of special courses or course units rather than through the
modification of the mainline curriculum.* They thus offer a reasonable current
estimate of how effective we can expect separate thinking and reasoning
courses to be. As we have seen, although the available evidence does not
establish that such courses can produce broad transfer of learning, neither does
it allow us to strongly reject the separate course as an element in an educational
reform program aimed at improving higher order abilities in students. Based on
present evidence, general course effectiveness seems to depend on the extent to
which it is accompanied by parallel efforts across the curriculum.
In this view, prudent educational practice should seek to embed efforts to
teach cognitive skills into one or anotherpreferably allof the traditional
school disciplines, and it should do this regardless of what may also be done in
the way of special courses in thinking or learning skills. This discipline-
embedded approach has several advantages. First, it provides a natural
knowledge base and environment in which to practice and develop higher order
skills. As we have shown earlier, cognitive research has established the very
* Some of the discipline-based problem-solving programs and some of the
reading and self-monitoring programs represent important exceptions. The
implications of these programs will be discussed further in subsequent sections.
Education and Learning to Think
important role of knowledge in reasoning and thinking. One cannot reason in
the abstract; one must reason about something. Each school discipline provides
extensive reasoning and problem-solving material by incorporating problem-
solving or critical thinking training into the disciplines; the problem of empty
thinking”—thinking about nothingis solved. As knowledge in the discipline
develops, the base on which effective problem solving can operate is naturally
Second, embedding higher order skill training within school disciplines
provides criteria for what constitutes good thinking and reasoning within the
disciplinary tradition. Each discipline has characteristic ways of reasoning, and
a complete higher order education would seek to expose students to all of these.
Reasoning and problem solving in the physical sciences, for example, are
shaped by particular combinations of inductive and deductive reasoning, by
appeal to mathematical tests, and by an extensive body of agreed upon fact for
which new theories must account. In the social sciences, good reasoning and
problem solving are much more heavily influenced by traditions of rhetorical
argument, of weighing alternatives, and of building a case for a proposed
solution. Mathematics insists on formal proofsa criterion absent in most other
disciplines. Each style of reasoning (and several others that could be elaborated)
is worth learning. However, only if higher order skills are taught within each
discipline are they likely to be learned.
Finally, teaching higher order skills within the disciplines will ensure that
something worthwhile will have been learned even if wide transfer proves
unattainable. This point is profoundly important. It amounts to saying that no
special, separate brief for teaching higher order skills need be made. Rather, it
proposes that if a subject matter is worth teaching in school it is worth teaching
at a high levelto everyone. A decision to pursue such an approach would
transform the whole curriculum in fundamental ways. It would treat higher
order skills development as the paramount goal of all schooling. Paradoxically,
then, dropping the quest for general skills might, in the end, be the most
powerful means of cultivating generally higher levels of cognitive functioning.
Saying that thinking skills should be incorporated into existing or planned
disciplinary courses is by no means suggesting an easy path. We know less than
we need to about how to do this job. Traditional formulations of the issue
largely interfere with the kind of inventive educational thought and
experimentation that will be needed to turn
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classes in mathematics, history, physics, or English into arenas for teaching
thinking and reasoning abilities. For example, the classic distinction between
knowledge as something one reasons about and skills as something one reasons
with has, in practice, placed process skills and knowledge in competition for
limited instructional time. The idea that certain forms of knowledge can be
powerful tools for learning and problem solving, or that processes and
procedures are an expression of principled knowledge, is something that
scholars and educators can agree on but have not really found ways to act on.
(See Bransford, in press, for a particularly perspicacious analysis of this
problem.) Instead, we have had reactive pendulum swings of attention either to
process skills (doing science, doing history, etc.) or to building large bodies
of knowledge. Research and experimentation focusing on how to truly combine
these are badly needed.
A particularly powerful way to begin transforming the school program is
to concentrate on those parts of the traditional curriculum that enable learning
and thinking in many fields. Reading is such an enabling discipline. So is
writing, along with, perhaps, skills for effective oral communication.
Mathematics is another candidate. Math is involved in many other disciplines,
and skills of mathematization, that is, the construction of formal
representations and arguments, could be broadly enabling. The 3-Rs, then,
come off rather well on this enabling criterion, although the reading, 'riting, and
'rithmetic curriculum called for in this higher order perspective will look quite
different from the traditional hickory stick curriculum. Furthermore, it seems
appropriate to add a fourth R”—reasoningto our list of potential enabling
disciplines. Let us consider each of these briefly.
We have already discussed some current research that points to
possibilities for changing the ways in which reading is taught. Thus far the
research has shown mainly how very weak readers can be brought up to at least
average performance levels. It is important to engage these students in meaning
construction activities based on text in settings that incorporate modeling of
good performance, lots of feedback, and opportunities to do small bits of the
task in the context of seeing the whole job accomplished. However, we do not
know for certain that these same methods are all that are needed to raise average
performance levels to true high literacy levels. Finding
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out what is needed to meet this goal is one important agenda for future research.
Cognitive researchers about to embark on studies of this important topic would
do well to examine the instruction in the high literacy academy tradition for
strong hypotheses about the kinds of teaching likely to succeed.
The school curriculum has neglected writing for some time. Its potential
role as a cultivator and an enabler of higher order thinking is very great,
especially if we consider writing as an occasion to think through arguments and
to master forms of reasoning and persuasion that are valued in various
disciplines. Existing research clearly shows that children'sand perhaps many
teachers'conceptions of writing do not match what both skilled writers and
cognitive research on writing tell us about the process. Children, and unskilled
writers generally, tend to view composition as a matter of writing down what
they know; Scardamalia and Bereiter (1985) call this the knowledge telling
strategy of writing. Children are not aware of the role, or even of the existence,
of the various discourse conventions and structures good writers use and readers
expect (see Stein, 1986, for a review). Finally, they do not think of writing as a
problem-solving process (cf. Flower and Hayes, 1980) in which plans must be
made for communicating an organized point of view to an audience, and they
do not understand that revision is integral to effective writing. Considerable
research on the learning and teaching of writing is now underway, some of it
focused on writing as a general tool for constructing and expressing arguments.
Although the approaches being tried are extremely varied, most reflect a general
point of view similar to the one underlying the successful approaches to
teaching reading as a higher order skill. They treat writing as an intentional
process, one in which the writer manages a variety of mental resources
linguistic knowledge, topical knowledge, knowledge of rhetorical forms,
processes of attention and judgmentto construct a message that will have a
desired impact on a reader. We now need research that focuses explicitly on
cultivating and assessing these broad skills of meaning construction and
interpretation. As in the case of reading, examination of traditional instruction
in rhetoric and related fields should provide a profitable point of departure.
Mathematics must be discussed in somewhat different terms than reading
and writing. It is not only an enabling skill, widely called on in a number of
other disciplines, but also a discipline in its own right whose particular
knowledge structures must be learned. Mathematics also poses special
problems, derived from its heavy dependence
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on formal notations. This has the effect of making it difficult for students to use
their informal and intuitive knowledge of mathematical concepts to support
school mathematics learning and to advance their mathematical competence. As
we noted earlier, good evidence suggests that much school mathematics
learning proceeds as a matter of memorizing rules for formal symbol
manipulation without much understanding of why the rules work as they do or
what the symbols stand for. If education were concerned only with the
calculation skills needed to get by in routine jobs and family obligations, this
would not cause much concern. But a high literacy approach to mathematics
teaching cannot afford to let this separation between symbols and meaning,
between calculation and mathematical reasoning, survive. Although many
mathematics educators have sought ways of making particular concepts and
procedures more understandable to children, to date no research has directly
addressed the question of how a broad meaning-construction approach to
mathematics learning can be promoted among all studentsso that students
themselves come to seek the connections between formal notations and their
justifying concepts. This remains a major agenda for research leading to a
higher order approach to mathematics teaching.
Reasoning has never had an explicit place in the mass education
curriculum. Philosophy has no regular position in the standard American high
school curriculum, nor is reasoning specified as part of the elementary school
syllabus in the way reading, writing, and mathematics are. By contrast, both
have been cornerstones of the elite, academy education tradition. Thus,
incorporating reasoning into the regular educational program would extend the
high literacy tradition to the entire school system. However, it is not clear
whether reasoning should be treated as a separate discipline or suffused through
the curriculum. Most philosophers working within the informal logic movement
want to see critical thinking or reasoning courses included in the curriculum.
Their argument is partly practical: reasoning skills will be passed over or
trivialized if they are spread through the curriculum and not given formal
recognition. But there is also a theoretical argument for treating reasoning as a
separate enabling discipline; this is that principles of logical reasoning are
unitary, not specific to particular domains of knowledge (see Paul, in press,
responding to a contrary argument by McPeck, 1981). Currently, we have no
empirical evidence to support the idea that teaching people to recognize and
analyze reasoning fallaciesa core element in most critical thinking and
informal logic curriculain fact leads them to
Education and Learning to Think
avoid such fallacies in their own thinking. Without careful attention to this
problem, informal logic could become just another body of knowledge
perhaps judged valuable in its own right but without claim to a special role in
the general development of higher order thinking and learning capabilities. We
need, then, substantial new research, requiring the collaboration of philosophers
and cognitive scientists, to identify approaches to teaching reasoning that
actually improve reasoning performance either in academic disciplines or in
practical situations.
It has been convenient to examine teaching programs in several distinct
categories. Yet there are striking points of similarity among those programs that
have shown some promising results. Many such programs rely on a social
setting and social interaction for much of teaching and practice. Although one
can imagine individually worked exercises designed to improve aspects of
thinking skill, very few programs in fact propose such activities. Instead,
students are encouraged to work problems in pairs or in small groups.
Instructors may also orchestrate special discussion and practice sessions. When
investigators of different theoretical orientations and disciplinary backgrounds
converge on a common prescription in this way, we should consider what
shared intuition may be at work. What roles might social interaction be playing
in the development of thinking? The authors cited in the preceding pages
mention several possibilities.
First, the social setting provides occasions for modeling effective thinking
strategies. Skilled thinkers (often the instructor but sometimes more advanced
fellow students) can demonstrate desirable ways of attacking problems,
analyzing texts, and constructing arguments. This process opens normally
hidden mental activities to inspection. Through observing others, students can
become aware of mental processes that might otherwise have remained entirely
implicit. Research suggests, however, that modeling alone does not produce
very powerful results. If students only watched more skilled thinkers perform,
they would not substantially improve their own thinking.
Apparently there is more to learning in a social setting than watching
others perform. Thinking aloud in a social setting allows
Education and Learning to Think
otherspeers or an instructorto critique and shape one's performance,
something that cannot be done effectively if only the results but not the
processes of thought are visible. The social setting may also provide a kind of
scaffolding for an individual learner's initially limited performance. Instead of
practicing small bits of thinking in isolation with no sense of each bit's
significance to the task as a whole, a group solves a problem, or writes a
composition, or analyzes an argument together. Within the group, extreme
novices can participate in performing complex tasks. If things go well, they can
eventually take over most or all of the work themselves, with a developed
appreciation of how individual elements in the process contribute to the whole.
This theory, adapted from Vygotsky (1978), is embodied explicitly in the
reciprocal teaching of Palincsar and Brown, and variants of it have been
proposed by a number of other investigators (e.g., Collins et al., in press).
The social setting may also function to motivate students. Students are
encouraged to try new, more active approaches, and they receive social support
even for partially successful efforts. Through this process, students come to
think of themselves as capable of engaging in independent thinking and of
exercising control over their learning processes. The public setting also lends
social status and validation to what can perhaps best be called the disposition to
higher order thinking. The term disposition should not be taken to imply a
biological or inherited trait. As used here, it is more akin to a habit of thought,
one that can be learned and, therefore, taught. Engaging in higher order thinking
with others seems likely to teach students that they have the ability, the
permission, and even the obligation to engage in a kind of critical analysis that
does not always accept problem formulations as presented or that may
challenge an accepted position.
We have good reason to believe that shaping this disposition to critical
thought is central to developing higher order cognitive abilities in students.
Research on strategy training shows that, if instruction is to work at all, it often
works very quicklyin just a few lessons or sometimes with little more than
directions to use some strategy. However, people induced to use a particular
learning strategy will often do so on the immediate occasion but will fail to
apply the same strategy on subsequent occasions. Both of these recurrent
findings serve to remind us that much of learning to be a good thinker is
learning to recognize and even search for opportunities to apply one's mental
capacities (cf. Belmont et al., 1982).
Education and Learning to Think
This suggests that the task for those who would raise the intellectual
performance levels in children is not just to teach children new cognitive
processes but to get them to use those processes widely and frequently. The
kind of higher order thinking we have discussed requires elaborating, adding
complexity, and going beyond the given to construct new formulations of
issues. It also involves weighing multiple alternatives and sometimes accepting
uncertainty. As such, higher order thinking requires effort on the part of the
individual and may involve some social riskof disagreeing with others
perceived to be more powerful, of not arriving at the expected answers, of not
always responding instantly. To overcome these difficulties, educational
institutions must cultivate not only skills for thinking but also the disposition to
use them.
A widely shared set of implicit assumptions exists about how dispositions
for higher order thinking might develop. They center on the role of a social
community in establishing norms of behavior, providing opportunity for
practice, and providing occasions for learning particular skills. The fundamental
theme is that such dispositions are cultivated by participation in social
communities that value thinking and independent judgment. Such communities
communicate these values by making available many occasions for such
activity and responding encouragingly to expressions of questioning and
judgment. The process of learning is further aided when there are many
opportunities to observe others engaging in such thinking activities. Finally,
dispositions for higher order thinking require sustained long-term cultivation;
they do not emerge from short-term, quick-fix interventions.
This set of beliefs, although highly plausible, has received little empirical
investigation. On the whole, research on the development of cognitive abilities
has proceeded quite separately from research on social and personality
development. For example, the extensive body of childhood socialization
research (Hetherington, 1983) says much about the emergence of traits such as
aggressiveness, dependency, conformity, or gender identification, but it says
little about how intellectual tendencies develop. An interesting new research
project (Caplan, 1985) on the development of intellectual curiosity in young
children appears to be a first link between research on child socialization and
our present concern for shaping higher order thinking dispositions.
Cognitive styles (e.g., Messick, 1976) such as reflectivity are known to
be related to school performance, and efforts have been
Education and Learning to Think
made to shape reflectivity (e.g., Meichenbaum, 1985). But this research has not
generally attended to the qualitative aspects of intellectual performance, and it
is impossible to know whether higher order thinking was in fact improved.
Other research on improving persistence (e.g., Turkewitz et al., 1975) has
tended to measure how much work students do but not whether they engage in
complex cognitive activities. Some recent research on intrinsic motivation may
help tie motivation to the quality as well as the quantity of educational work
(see Lepper, 1981, 1983; Nicholls, 1983). When people work to gain praise,
grades, or material benefits, they are externally motivated. When they work to
master a task, they are intrinsically motivated. Apparently some correlation
exists between the kinds of motivations that keep people working and several
qualitative features of their work: for example, the complexity of the tasks they
choose to work on, the range of material to which they attend, and the extent to
which they are able to shift direction (break set) to pursue a new, more
fruitful approach (Condry and Chambers, 1981; Kruglanski, 1981; Lepper and
Greene, 1981; McGraw, 1981).
A promising link between quality of thinking and persistence is being
forged by investigators studying differences in people's conceptions of ability.
For example, Dweck and her colleagues (Dweck, in press; Dweck and Elliot,
1983) have shown that individuals differ fundamentally in their conceptions of
intelligence and that these conceptions mediate very different ways of attacking
problems. A distinction is made between two competing conceptions of ability,
or theories of intelligence, that people may hold. One, called the entity
conception, treats ability as a global, stable quality. The second, called the
incremental conception, treats ability as a repertoire of skills that can be
expanded through efforts to learn. Entity conceptions orient children toward
performing well so that they can display their intelligence and toward not
revealing lack of ability by giving wrong responses. Incremental conceptions
orient children toward learning well so that they can acquire new knowledge or
skill. Most relevant to the present argument, incremental conceptions of ability
and associated learning goals lead children to analyze tasks and to formulate
strategies for overcoming difficulties. We can easily recognize these as close
cousins to the kinds of higher order thinking discussed in this essay. In a related
analysis, Covington (1983) suggests that people who view ability as created
through strategic
Education and Learning to Think
self-management (of study time, of types of elaboration, of ways of attacking
tasks) will be better able to compensate for self-attributions of low initial ability.
A key question, of course, is whether these differences in type of
motivation or theory of intelligence can be deliberately shaped by the way in
which school activity is organized. Evidence suggests that the nature of the
environment in which one works makes a difference in whether one invokes
internal or external motivations for one's work. However, research has not
examined whether personal traits favoring internal motivation can be developed
by deliberately altering institutional or social patterns. Very recent work by
Dweck and her colleagues is examining ways of helping students to acquire and
apply incremental conceptions of intelligence, but more extensive research is
required before clear conclusions can be drawn. In any case, these lines of
motivation research highlight the possibilities for an important convergence
between efforts aimed at teaching higher order cognitive skills and those aimed
at cultivating dispositions to apply those skills.
Higher order thinking is difficult to define but easy to recognize when it occurs.
Higher order thinking involves a cluster of elaborative mental activities
requiring nuanced judgment and analysis of complex situations according to
multiple criteria. Higher order thinking is effortful and depends on self-
regulation. The path of action or correct answers are not fully specified in
advance. The thinker's task is to construct meaning and impose structure on
situations rather than to expect to find them already apparent.
Higher order thinking has always been a major goal of elite educational
institutions. The current challenge is to find ways to teach higher order thinking
within institutions committed to educating the entire population.
In its origins, the mass educational system was concerned with routine
competencies such as simple computation, reading familiar
Education and Learning to Think
and predictable texts, and acquiring well-defined vocational competencies. It
was not considered necessary or possible for all students to learn to interpret
complex texts, write extended arguments, or develop original solutions to
problems. However, changing economic and social conditions are now creating
a demand for these abilities in all citizens, and schools are seeking ways to
cultivate thinking skills in all students. No educational system has ever been
built on the assumption that everyone, not just an elite, can become a competent
thinker. We must view this new challenge as an invitation to inventive and very
demanding educational reform.
Higher order thinking is the hallmark of successful learning at all levels—not
only the more advanced.
The challenge to reform comes at a time when cognitive research provides
an important reconceptualization of the nature of thinking and learning that can
inform and guide educational work. The most important single message of this
body of research is that complex thinking processeselaborating the given
material, making inferences beyond what is explicitly presented, building
adequate representations, analyzing and constructing relationshipsare
involved in even the most apparently elementary mental activities. Children
cannot understand what they read without making inferences and using
information that goes beyond what is written in the text. They cannot become
good writers without engaging in complex problem-solving-like processes.
Basic mathematics will not be effectively learned if children only try to
memorize rules for manipulating written numerical symbols. All of this implies
that basic and higher order skills cannot be clearly separated.
Good thinking depends on specific knowledge, but many aspects of powerful
thinking are shared across disciplines and situations.
A central issue, both for educational practice and for research that can
guide that practice, is whether thinking and learning abilities are generalthat
is, applicable in all domains of thinkingor specific to a particular domain. The
evidence shows clearly that thinking is driven by and supported by knowledge,
in the form of both specific facts and organizing principles. This knowledge,
together with the automated recognition and performance that come
Education and Learning to Think
with extended practice, allows experts in any field to engage in more
sophisticated thinking than people new to the field. At the same time, many
aspects of thinking are shared across fields of expertise. These include a wide
range of oral and written communication skills, mathematization and
representational abilities, principles of reasoning, and skills of argument
construction and evaluation. These can be thought of as enabling skills for
learning and thinking. Generally speaking, people rely on powerful but only
narrowly applicable thinking methods in domains in which they are expert and
use broadly applicable but weak methods for learning and thinking in fields
they know little about. Good thinkers need both the powerful but specific and
the general but weak kinds of skills.
Elements of thinking are clearly teachable.
The programs reviewed here show that many components of thinking can
be effectively taught. That is, there is evidence that the particular performances
taught in the programs are in fact learned by students. The kinds of components
that have been successfully taught include generating multiple ideas and
alternative viewpoints on a particular topic, generating summaries, skimming,
figuring out word meanings from context, solving analogies and logical puzzles,
and detecting logical reasoning fallacies.
However, an integrated ability to learn, think, and reason and a broad
disposition to engage in higher order thinking are not necessarily ensured by
acquiring particular components of thinking.
We need direct assessments of the kinds of complex reasoning and
problem-solving skills that constitute higher order thinking. Most evaluations
have not made such assessments. They have relied instead on assessments of
particular elements that are taught or on indicator testssuch as IQ or SAT
scoresthat are normally correlated with successful learning and thinking.
However, under changed instruction and learning conditions, these traditional
indicators may no longer be valid. Thus, we have less evidence than would be
desirable, and less than the proliferation of programs would
Education and Learning to Think
suggest, on whether and how thinking abilities that are integrated and usable
can actually be cultivated.
Only a few programs provide convincing evidence that broadly applicable and
integrated abilities have been acquired.
In the most convincing cases, improvements due to instruction have been
demonstrated for reading comprehension, general grade averages, and essay
writing. Some programs also demonstrate improved problem-solving or
laboratory performance in specific disciplines, especially in mathematics and
science, thus meeting their own goalsalthough not demonstrating (and not
necessarily seeking) transfer to other disciplines or to practical life. A larger
number of programs point to student claims that they now use the kinds of
abilities taught. However, these claims are difficult to evaluate; they show that
students generally feel better about their thinking and learning abilities after the
course, but they do not tell us whether these improved self-assessments are in
fact warranted.
Current testing practices in American education do not provide very powerful
tools for assessing the effects of efforts to teach thinking and reasoning. Testing
practices may in fact interfere with cultivation of the kind of higher order skills
that are desired.
In general, the tests used in assessing educational efforts involve multiple
choice or other short, precoded answers. These tests can measure the
accumulation of knowledge and can be used to examine specific components of
reasoning or thinking. However, they are ill suited to assessing the kinds of
integrated thinking that we call higher order. If progress is to be made in
converting American schools to the higher order thinking agenda, we must
develop forms of assessment that are more suited to the nature of the abilities
we seek to teach.
Education and Learning to Think
A broad disposition to higher order thinkingmust be cultivated.
Isolated instruction in thinking skills, no matter how elegant the training
provided, is unlikely to produce broadly used thinking ability. Thinking well
requires more than knowing a selected set of strategies or techniques for
problem solving and learning. It also requires knowing when these strategies are
appropriate, and it requires the motivation to apply them, even though they may
involve more effort than routine performances as well as some risk of social
controversy. This implies that higher order skills must suffuse the school
program from kindergarten on and in every subject matter. Training in general
skills must be supplemented and supported by application throughout the
curriculum. Various subject matters in the school program should be taught
with an eye to developing the powerful thinking methods used by experts in
those disciplines. Students must come to think of themselves as able and
obligated to engage in critical analysis and problem solving throughout
schooling. The following are promising directions that educational
experimentation might take.
Embedding instruction in thinking skillswithin the academic disciplines of the
school curriculum has several advantages.
It ensures that there is something solid to reason about. It supplies criteria
from within the disciplinary traditions for what constitutes good reasoning and
thinking. It ensures that something worthwhile will have been taught and
learned even if wide transfer proves impossible. However, there is a caveat for
those who seek to embed higher order skills teaching in the existing school
program. Thinking skills tend to be driven out of the curriculum by
evergrowing demands for teaching larger and larger bodies of knowledge. The
idea that knowledge must be acquired first and that its application to reasoning
and problem solving can be delayed is a persistent one in educational thinking.
Hierarchies of educational objectives, although intended to promote attention
to higher order skills, paradoxically feed this belief by suggesting that
knowledge acquisition is a first stage in a sequence of educational goals. The
relative ease of
Education and Learning to Think
assessing people's knowledge, as opposed to their thought processes, further
feeds this tendency in educational practice.
Periodically, educators resist this pressure by proposing that various forms
of process- or skill-oriented teaching replace knowledge-oriented instruction. In
the past, this has often led to a severe deemphasis of basic subject matter
knowledge. This, in turn, has had the effect of alienating many subject matter
specialists, creating pendulum swings of educational opinion in which
knowledge-oriented and process-oriented programs periodically displace each
other, and delaying any serious resolution of the knowledgeprocess paradox.
We cannot allow these pendulum swings to continue. Cognitive research shows
the intimate relationship of subject matter knowledge and reasoning processes.
We need both practical experimentation in schools and more controlled
instructional experimentation in laboratories to discover ways of incorporating
our new understanding of the knowledgereasoning connection into instruction.
Reorienting instruction in the 3-Rs (the enabling disciplines) so that they
incorporate more of the higher order processes seems a particularly promising
approach to improving thinking skills.
The 3-Rs of the traditional basic school curriculum can become the
environment for higher order education. Effective reading, writing, and
mathematics learning depend on elaboration, explication, and various forms of
meaning construction. Reorienting basic instruction in these curricula to focus
on intentional, self-managed learning and strategies for meaning construction,
rather than on routinized performances, will result in more effective basic skill
instruction while providing a strong base for higher order skill development in
other disciplines.
A fourth R”—reasoningmight be considered a candidate for a new enabling
discipline in the school curriculum.
Many philosophers argue that principles of logical reasoning are unitary
and not specific to particular domains of knowledge. The study of reasoning,
they claim, can enable effective thinking across disciplines. Although there has
been little empirical investigation of this claim, the hypothesis is a reasonable
one and should be
Education and Learning to Think
investigated carefully. A potential pitfall is that learning to identify reasoning
fallaciesa core element of most programs in informal logic and critical
thinkingmay not in fact help people improve their own reasoning. This
question needs careful attention, with appropriate evaluation of the extent to
which students in reasoning courses learn to produce, as well as analyze,
reasoned arguments.
Links between thinking skills and motivation for thinking must be developed.
Everyone agrees that successful educational achievement requires both
motivation and appropriate cognitive activity. Yet our theories implicitly treat
motivation and cognition as if they worked independently to determine the
nature and extent of learning. In fact, these traditionally separate factors appear
far more intimately related than most current research helps us to appreciate.*
However, recent research linking children's conceptions of their own and others'
intelligence to the ways in which they analyze learning tasks offers a promising
new connection, as does research on intrinsic motivation for learning. Active
experimentation on what kinds of school activity organization cultivate
motivation for particular kinds of complex and strategic learning is needed. The
two concerns must be merged as this work proceeds; efforts to develop more
intellectually functional motivational patterns should not become substitutes for
efforts to establish specific cognitive competencies. Motivation for learning will
be empty if substantive cognitive abilities are not developed, and the cognitive
abilities will remain unused if the disposition to thinking is not developed.
*The monograph by Cole and Griffen (1987) explores this question extensively
from another angle, focusing on the social context for thinking. The present
monograph and Cole and Griffen's study provide complementary vantage points
for addressing this key set of issues.
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Education and Learning to Think
Education and Learning to Think
The following individuals were kind enough to discuss their work or
provide materials for study during the course of this project:
Ann Arbor, Mich.
Department of Physics
University of Washington
Department of Philosophy
University of Windsor
Professor of Physics
Director, Educational
Technology Center
University of California, Irvine
Department of Economics
Bowling Green State University
Graduate School of Education
Harvard University
Laboratory of Comparative Human
University of California, San Diego
Department of Psychology
University of California, Berkeley
Department of Psychology
Texas Christian University
Norfolk, England
Education and Learning to Think
Center for Educational Technology
Florida State University
Hadassah-WIZO-Canada Research
Bar Ilan University
Urban Institute
Washington, D.C.
Department of Chemical Engineering
McGill University
Department of Physics and Director,
The ADAPT Program
University of Nebraska
College of Education
University of Maryland
Department of Educational Psychology
Texas A&M University
Department of Economics
Bowling Green State University
Midwest Publications Co., Inc.
Pacific Grove, Calif.
The Franklin Institute Press
Department of Philosophy
University of Windsor
Chicago Public Schools
Department of Psychology
Bowling Green State University
Graduate School of Education
Harvard University
Department of Psychology
Carnegie-Mellon University
Department of English
California Polytechnic State University
Department of Psychology
Stanford University
Institute for the Advancement of
Philosophy for Children
Montclair State College
Department of Physics and Astronomy
University of Massachusetts
Department of Philosophy
University of Western Ontario
Graduate School of Education
Harvard University
Education and Learning to Think
National Center on Effective
Secondary Schools
University of Wisconsin
Director, Information Science Division
Bolt Beranek and Newman, Inc.
Cambridge, Mass.
Institute for Educational Research and
Memorial University of Newfoundland
Director, Center for Research on
Learning and Schooling
University of Michigan
Department of Philosophy
Sonoma State College
Department of Physics
University of California, Berkeley
School of Engineering and Applied
University of California, Los Angeles
Center for Applied Cognitive Science
Ontario Institute for Studies in
School of Education
University of California, Berkeley
Department of Education
University of Western Australia
Senior Researcher
Educational Testing Service
Princeton, N.J.
Department of Mathematics Education
University of Georgia
Department of Psychology
Yale University
Chief Scientist
Bolt Beranek and Newman, Inc.
Cambridge, Mass.
Department of Philosophy
University of Chicago
College of Engineering
Center for Guided Design
University of West Virginia
Department of Philosophy
Sacramento State University
Department of Educational Psychology
University of Texas at Austin
Lakeworth, Fla.
Department of Education
University of California, Los Angeles
Education and Learning to Think
Department of Chemical Engineering
McMaster University
... In a didactic perspective, this is also termed postproblem reflection: "As the students evaluate their own performance and that of their peers, they reflect on the effectiveness of their self-directed learning and collaborative problem solving. Such assessment is important for developing higher order thinking skills" (Resnick, 1987;Hmelo and Ferrari, 1997). ...
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In this article, we argue that game jam formats are uniquely suited to engage participants in learning about artificial intelligence (AI) as a design material because of four factors which are characteristic of game jams: 1) Game jams provide an opportunity for hands-on, interactive prototyping, 2) Game jams encourage playful participation, 3) Game jams encourage creative combinations of AI and game development, and 4) Game jams offer understandable goals and evaluation metrics for AI. We support the argument with an interview study conducted with three AI experts who had all organized game jams with a focus on using AI in game development. Based on a thematic analysis of the expert interviews and a theoretical background of Schön's work on educating the reflective practitioner, we identified the four abovementioned factors as well as four recommendations for structuring and planning an AI-focused game jam: 1) Aligning repertoires, 2) Supporting playful participation, 3) Supporting ideation, and 4) Facilitating evaluation and reflection. Our contribution is motivated by the recent discourse on general challenges and recommendations of teaching AI identified by related literature, here under the long and intertwined history of games and AI in general. The article presents an initial discussion of the value of game jam formats for learning about AI and which factors need to be considered in regard to this specific learning goal.
... Penerapan keterampilan berpikir kritis melalui kegiatan pembelajaran di kelas, termasuk dalam pembelajaran bahasa Inggris sebagai bahasa asing, mendorong siswa belajar menemukan solusi atas problem-problem kehidupan, sehingga guru diharapkan mampu memfasilitasi pembelajaran yang diberikan dengan pengalaman belajar atau kegiatan belajar yang berbasis pada pengembangan keterampilan berpikir tingkat tinggi (HOTS) dimana kemampuan berpikir kritis adalah bagian dari HOTS tersebut. Banyak upaya yang telah dilakukan dalam mengintegrasikan pengembangan HOTS maupun keterampilan berpikir kritis ke dalam pembelajaran di dalam kelas (Resnick, 1987;Osman & Kassim, 2015;Li, 2016), namun kebanyakan masih diperuntukkan bagi pembelajar dewasa untuk pengembangan keterampilan membaca dan menulis (Afshar & Rahimi, 2016). Untuk pembelajar bahasa anak maupun pembelajar muda sampai dengan tingkat SMP, disarankan agar guru memanfaatkan berbagai metode dan materi ajar, termasuk salah satunya adalah penggunaan storytelling (Hardy, 1978;Setyarini dkk., 2018). ...
This community service activity aims to introduce innovative English teaching methods Storytelling in English learning to prospective English teacher students in the FKIP UNCEN English Language Study Program to be better prepared and trained in developing English learning that is able to integrate the three aspects of educational taxonomy, namely cognitive, affective, and psychomotor. In learning using Storytelling conditions, storytellers have to be more creative using the language focus in telling stories they read to students and at the same time asking questions that are able to stimulate students to think critically using the target language correctly in order to create the meaningful interaction and natural learning environment between both the storytellers and their listeners. The specific purpose of this activity is to introduce the use of Storytelling in teaching and learning English classroom in the context of the foreign language teaching and learning, and how it is managed to build a learning atmosphere to support the development of target language skills as well as learners’ critical thinking skills through classroom interaction in the form of dialogue and questions given by speakers. This community service activity involved students of the VII semester English language study program who take the Curriculum and Material Development course, conduct for about six month including the selection and deepening of the story that will be used for storytelling, a list of questions that have the potential to stimulate critical thinking skills, enrichment story material, implementation of community service activities, and seminars as a result of community service activities. This activity is useful for the readiness of prospective English teacher students in the English Education Study Program FKIP UNCEN in applying their knowledge and knowledge after completing their studies. Keywords: Critical Thinking Skills; Storytelling; Prospective English Teacher
... The relevance of learning environments for learning in general-and SRL in particular-has been widely demonstrated (Biggs, 1989(Biggs, , 1993Boekaerts, 1992Boekaerts, , 1996De Corte, 1996;Entwistle, 1991;Vermunt, 1995;Vermunt & Donche, 2017;Zimmerman, 1989). In the school context, various instructional approaches have been developed since the 1980s, such as cognitive apprenticeship (Collins et al., 1989), situated learning (Greeno, 2006;Resnick, 1987), and problem-based learning (Barrows & Tamblyn, 1980). To promote SRL in school, some models explicitly include the learning environment. ...
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Self-regulated learning (SRL) provides the foundation for building sustainable knowledge and is therefore important for schools, classrooms, and lifelong learning in general. Especially in vocational education and training, the concept of SRL remains fundamental as it relates to preparing future employees. However, further research is needed on how vocational students situationally regulate their learning process and the extent to which this may be related to a dispositional change in their SRL. In this study, we analyzed longitudinal questionnaire data from 159 students who attended either SRL-conducive or regular vocational classes. We refer to Perry and colleagues' (2018) framework of an SRL-conducive learning environment, which focuses on (meta)cognitive, motivational, and emotional aspects of learning. Using multilevel analysis, we found differences in the development of (meta)cognitive components of learning, whereas no clear differences could be identified for motivational and emotional components. The results support the assumption that process analyses can be used to draw a more differentiated picture of SRL in vocational schools. Moreover, indirect approaches to promoting SRL should be designed to include all SRL-relevant aspects.
... Mathematical reasoning is one of the critical skills by which the students become capable of making use of other skills of mathematics. According to Resnick (1987), in mathematics, logical reasoning helps the students to recognize the understanding and sense of mathematics as they learn to opt for appropriate strategies for solving the problem, describe as well as develop a solution, evaluate the situation, and draw logical conclusions. The study of Abishev et al. (2016) discovered that Kazakhstani students within higher education need to develop certain reasoning, creativity, and intuition in choosing mathematical tools in order to effectively understand the concepts and problems. ...
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Mathematical learning in many developing nations is below average due to which students face difficulties in solving the equations and problems of mathematics as a result of limited understanding of the main concepts and reliance upon intuition as well as memorization. This study is focused on analyzing the effectiveness of senior graders’ education based on the development of mathematical intuition and logic in the context of Kazakhstan’s educational system. The quantitative research method and primary data sources were used for this research with a 147 sample size, which was selected by using a random strategy of sampling. With the use of IBM SPSS STATISTICS for data analysis, it was concluded that mathematical intuition and logic have a positive influence on the effectiveness of a student’s education. Effective strategies, such as rote learning instructions, problem-based learning, RME approach, mathematical reasoning, etc., are essential for enhancing the capabilities of studies in learning mathematics. It is found that there is a significant and positive association between student effectiveness and the logical reasoning abilities of students. Additionally, a positive and moderate relationship is noticed between the critical thinking of students, problem-solving abilities of students, and student effectiveness. Nevertheless, the main limitation of this study is that with small sample size, the findings of the study cannot be generalized; therefore, a large sample size would increase the reliability of the results in the future research. However, in the context of Kazakhstan, this study potentially contributes to the existing literature by presenting conclusive findings in the context of mathematical logic and intuition and student effectiveness.
... HOT and metacognition Resnick (1987) characterize key features of HOT, arguing that it is non-algorithmic, it tends to be complex, it often yields multiple criteria and solutions and it often involves uncertainty. In general, the concept HOT is used to present cognitive activities that are beyond the stage of recall and comprehension/understanding according to Bloom's taxonomy (Bloom, 1956) and according to more recent, revised models (e.g., Crompton et al., 2019;Krathwohl, 2002;Leighton, 2011). ...
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Metacognition is an invaluable part of instruction of higher order thinking (HOT). The goal of this article is to review previous studies about teachers’ knowledge and professional development (PD) in the area of metacognitive instruction in the context of teaching HOT. Part A of the article reviews 25 empirical studies assembled through a scoping review. Although each individual study consists of significant findings, our analysis indicates that, as a field, the study of teachers’ and pre-service teachers’ knowledge in this area is still rather preliminary and exploratory. The review draws several conclusions regarding the nature of the research in this area. However, lack of a common conceptual framework and research instruments precludes the possibility of drawing meaningful general conclusions from the findings of the 25 studies. Part B centers on 8 empirical and theoretical studies addressing the same conceptual framework centering on meta-strategic knowledge (MSK). The findings demonstrate the significance of metacognition in general, and MSK in particular for teachers’ ability to teach HOT, showing that it can be developed in both pre-service and in-service teachers’ education and PD. The findings highlight several specific characteristics of teachers’ knowledge and learning processes in this area. Yet, the findings also show that metacognition is rarely addressed in a satisfactory manner in large-scale efforts to teach HOT and that MSK is mostly neglected in PD programs for teaching inquiry learning. The implications for research and practice of HOT and metacognition are discussed.
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This study was premised on the Community of Inquiry model and a qualitative method approach was used with an online individual semi-structured interview protocol as the data collection instrument to collect and analyse data gathered from the respondents’ individual interviews. A case study design was used with six participants (3 lecturers and 3 students) being sampled. The participants comprising three (3) Mathematics education lecturers, and three (3) Mathematics education students (preservice teachers) either in the first, second or third year of study in Mathematics education. Interviews were conducted online with the participants through Skype and Zoom. A thematic analysis was used to identify themes and patterns. The findings of the study revealed that the participants, understanding the use of social media, have transformed their teaching and learning in higher education institutions. Apart from making the shift from face-to-face teaching to teaching online using a technology-based independent mode to continue teaching in the Covid-era, lecturers have experienced academic well-being through a change in their pedagogy and teaching approaches as Mathematics lecturers. This change has ensured that students are exposed to a more student-centred approach through the use of social media platforms which has enhanced students’ learning of Mathematics. Recommendations are made.
One curriculum policy in countries, including Indonesia, is to provide students with higher-order thinking skills (HOTS) to meet the challenges of the 21st century, and success in doing so is closely related to the competence of teachers in integrating HOTS in the learning process. This study investigated HOTS implementation in Islamic Education (PAI) in primary schools in Indonesia. This study employed a case study design involving 58 PAI teachers in primary schools from several West Java, Indonesia regencies. The data were collected by distributing questionnaires with short answers followed by semi-structured interviews of 10 participants. Inductive and thematic data analysis was carried out to identify, evaluate, and create themes expressed by participants with the assistance of NVivo 12. Triangulation and expert review methods were used for instrument and data validation. This study explored five findings: teacher understanding, teaching resource support, instructional strategies, and student knowledge levels. This research contributes to improving the quality of PAI learning in HOTS-oriented primary schools, and policymakers can use its findings in determining the direction of the HOTS-based PAI curriculum. Policymakers should stress the importance of increasing teacher competence in mastering the HOTS concept comprehensively in planning, implementation, and evaluation. Support from various parties in optimizing HOTS-oriented PAI learning is a necessity for teachers.
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This edited collection, one of the first to be written chiefly by Vietnamese scholars, explores innovation in Vietnamese education under the impact of the Fourth Industrial Revolution. Vietnam is considered a booming country with its continued economic rise, and the contributors explore one of Vietnam’s strategies to achieve further economic growth, which is the innovation – and modernization – of its education system. The content is split into two parts, the first focusing on innovations in educational policy and management and the second looking at innovation in teaching theories and methods. It shows the vitality and innovation coming from developing countries like Vietnam, where necessity breeds fast adoption of education technology and development. This insightful edited volume will help researchers in comparative education, educational development, and Asian studies understand the achievements and challenges of Vietnamese general education and higher education in the Fourth Industrial Revolution.
The main goal of the field of augmented cognition is to research and develop adaptive systems capable of extending the information management capacity of individuals through computing technologies. Augmented cognition research and development is therefore focused on accelerating the production of novel concepts in human-system integration and includes the study of methods for addressing cognitive bottlenecks (e.g., limitations in attention, memory, learning, comprehension, visualization abilities, and decision making) via technologies that assess the user’s cognitive status in real time. A computational interaction employing such novel system concepts monitors the state of the user, through behavioral, psychophysiological, and neurophysiological data acquired from the user in real time, and then adapts or augments the computational interface to significantly improve their performance on the task at hand. The International Conference on Augmented Cognition (AC), an affiliated conference of the HCI International (HCII) conference, arrived at its 16th edition and encouraged papers from academics, researchers, industry, and professionals, on a broad range of theoretical and applied issues related to augmented cognition and its applications. The field of augmented cognition has matured over the years to solve enduring issues such as portable, wearable neurosensing technologies and data fusion strategies in operational environments. These innovations coupled with better understanding of brain and behavior, improved measures of brain state change, and improved artificial intelligence algorithms have helped expand the augmented cognition focus areas to rehabilitation, brain-computer interfaces, and training and education. The burgeoning field of human-machine interfaces such as drones and autonomous agents are also benefitting from augmented cognition research. This volume of the HCII 2022 proceedings is dedicated to this year’s edition of the AC conference and focuses on topics related to understanding human cognition and behavior, brain activity measurement and electroencephalography, human and machine learning, and augmented cognition in extended reality. Papers of this one volume are included for publication after a minimum of two single-blind reviews from the members of the AC Program Board or, in some cases, from members of the Program Boards of other affiliated conferences. We would like to thank all of them for their invaluable contribution, support, and efforts.