Education Development Center, Inc.
Center for Children and Technology
A Cognitive Apprenticeship for Disadvantaged Students
CTE Technical Report Issue No. 10
January 1991
Prepared by:
Allan Collins
Jan Hawkins
Sharon M. Carver
Introduction
Historically there has been a great divide between education for the advantaged
(e.g., Latin and geometry) and training for the disadvantaged (e.g., vocational
education).As education has become universal, we have extended education
for the advantaged to more and more of the population, though with limited
success and in watered-down form. But it is difficult for most students
to understand why they should be reading Macbeth and learning to
multiply fractions when there is no obvious call for such knowledge in any
life they can imagine for themselves. And there is increasing resistance
among students to being force fed an education that seems irrelevant to
their lives.
Our thesis in this paper is that the changing nature of work in society
(e.g., Zuboff, 1988) provides a potential meeting ground where education
for the advantaged and disadvantaged can come together in a curriculum where
the educational tasks reflect the future nature of work in society. Work
is becoming computer based and, at the same time, requires more and more
ability to learn and think. Hence, a curriculum built around tasks that
require learning and thinking in a computer-based environment is a curriculum
that will make sense to both advantaged and disadvantaged students and that
will educate them in ways that make sense for society at large.
Only in the last century, and only in industrialized nations, has formal
schooling emerged as a widespread method of educating the young. Before
schools appeared, apprenticeship was the most common means of learning.
Even today, many complex and important skills, such as those required for
language use and social interaction, are learned informally through apprenticeship-like
methods--that is, methods not involving didactic teaching, but observation,
coaching, and successive approximation.
The differences between formal schooling and apprenticeship methods are
many, but for our purposes, one is most important: in schools skills and
knowledge have become abstracted from their use in the world. In apprenticeship
learning, on the other hand, skills are not only continually in use by skilled
practitioners, but are instrumental to the accomplishment of meaningful
tasks. Said differently, apprenticeship embeds the learning of skills and
knowledge in their social and functional context. This has serious implications
for the design of instruction for students. Specifically, we propose the
development of a new "cognitive apprenticeship" (Collins, Brown,
& Newman, 1989) to teach students the thinking and problem-solving skills
involved in school subjects such as reading, writing, and mathematics.
Traditional Apprenticeship
To foreshadow those methods and why they are likely to be effective, let
us first consider some of the crucial features of traditional apprenticeship
(Lave, 1988). First and foremost, apprenticeship focuses closely on the
specific methods for carrying out tasks in a domain. Apprentices learn these
methods through a combination of what Lave calls observation, coaching,
and practice or what we, from the teacher's point of view, call modeling,
coaching, and fading. In this sequence of activities, the apprentice repeatedly
observes the master and his or her assistants executing (or modeling) the
target process, which usually involves a number of different but interrelated
subskills. The apprentice then attempts to execute the process with guidance
and help from the master (i.e., coaching). A key aspect of coaching is the
provision of scaffolding, which is the support, in the form of reminders
and help, that the apprentice requires to approximate the execution of the
entire composite of skills. Once the learner has a grasp of the target skill,
the master reduces (or fades) participation, providing only limited hints
and feedback to the learner, who practices by successively approximating
smooth execution of the whole skill.
From Traditional to
Cognitive Apprenticeship
Collins, Brown, and Newman (1989) proposed an extension of apprenticeship
for teaching subjects such as reading, writing, and mathematics. We call
this rethinking of learning and teaching in school "cognitive apprenticeship"
to emphasize two issues. First, the method is aimed primarily at teaching
the processes that experts use to handle complex tasks. Where conceptual
and factual knowledge are addressed, cognitive apprenticeship emphasizes
their uses in solving problems and carrying out tasks. That is, in cognitive
apprenticeship, conceptual and factual knowledge are exemplified and practiced
in the contexts of their use. Conceptual and factual knowledge thus are
learned in terms of their uses in a variety of contexts, encouraging both
a deeper understanding of the meaning of the concepts and facts themselves,
and a rich web of memorable associations between them and the problem-solving
contexts. It is this dual focus on expert processes and learning in context
that we expect to help solve current educational problems.
Second, our term, cognitive apprenticeship, refers to the focus of the learning-through-guided
experience in cognitive skills and processes, rather than physical ones.
Although we do not wish to draw a major theoretical distinction between
the learning of physical and cognitive skills, there are differences that
have practical implications for the organization of teaching and learning
activities. Most importantly, traditional apprenticeship has evolved to
teach domains in which the process of carrying out target skills is external,
and thus readily available to both student and teacher for observation,
comment, refinement, and correction, and bears a relatively transparent
relationship to concrete products. The externalization of relevant processes
and methods makes possible such characteristics of apprenticeship as its
reliance on observation as a primary means of building a conceptual model
of a complex target skill. And the relatively transparent relationship,
at all stages of production, between process and product facilitates the
learner's recognition and diagnosis of errors, upon which the early development
of self-correction skill depends.
Applying apprenticeship methods to largely cognitive skills requires the
externalization of processes that are usually carried out internally. Given
the way that most subjects are taught and learned in school, teachers cannot
make fine adjustments in students' application of skill and knowledge to
problems and tasks, because they have no access to the relevant cognitive
processes. By the same token, students do not usually have access to the
cognitive problem solving processes of instructors as a basis for learning
through observation and mimicry. Cognitive research, through such methods
as protocol analysis, has begun to delineate the cognitive processes that
comprise expertise, which heretofore were inaccessible. Cognitive apprenticeship
teaching methods are designed to bring these tacit processes into the open,
where students can observe, enact, and practice them with help from the
teacher and from other students.
In addition to the emphasis on cognitive skills, there are two major differences
between cognitive apprenticeship and traditional apprenticeship. First,
because traditional apprenticeship is set in the workplace, the problems
and tasks that are given to learners arise not from pedagogical concerns,
but from the demands of the workplace. Cognitive apprenticeship, as we envision
it, differs from traditional apprenticeship in that the tasks and problems
are chosen to illustrate the power of certain techniques and methods, to
give students practice in applying these methods in diverse settings, and
to increase the complexity of tasks slowly, so that component skills and
models can be integrated. In short, tasks are sequenced to reflect the changing
demands of learning. Letting the job demands select the tasks for students
to practice is one of the great inefficiencies of traditional apprenticeship.
A second difference between cognitive apprenticeship and traditional apprenticeship
is the emphasis in cognitive apprenticeship on generalizing knowledge so
that it can be used in many different settings. Traditional apprenticeship
emphasizes teaching skills in the context of their use. We propose that
cognitive apprenticeship should extend practice to diverse settings so that
students learn how to apply their skills in varied contexts. Moreover, the
principles underlying the application of knowledge and skills in different
settings should be articulated as fully as possible by the teacher, whenever
they arise in different contexts.
A Framework for Designing Learning Environments
Our introductory discussion of cognitive apprenticeship has raised numerous
pedagogical and theoretical issues that we believe are important to the
design of learning environments generally. To facilitate consideration of
these issues, we have developed a framework consisting of four dimensions
that constitute any learning environment: content, method, sequence, and
sociology. Relevant to each of these dimensions is a set of characteristics
that we believe should be considered in constructing or evaluating learning
environments. These characteristics are summarized in Table 1 and described
in detail below, with examples from reading, writing, and mathematics.
Content
Recent cognitive research has begun to differentiate the types of knowledge
required for expertise. In particular, researchers have begun to distinguish
between the explicit conceptual, factual, and procedural knowledge associated
with expertise and various types of strategic knowledge. We use the term
strategic knowledge to refer to the usually tacit knowledge that underlies
an expert's ability to make use of concepts, facts, and procedures as necessary
to solve problems and accomplish tasks. This sort of expert problem-solving
knowledge involves problem-solving heuristics (or "rules of thumb")
and the strategies that control the problem-solving process. Another type
of strategic knowledge, often overlooked, includes the learning strategies
that experts use to acquire new concepts, facts, and procedures in their
own or another field.
1. Domain knowledge includes the conceptual, factual, and procedural
knowledge explicitly identified with a particular subject matter, which
is generally explicated in school textbooks, class lectures, and demonstrations.
This kind of knowledge, although certainly important, provides insufficient
clues for many students about how to solve problems and accomplish tasks
in a domain. Examples of domain knowledge in reading are vocabulary, syntax,
and phonics rules.
2. Heuristic strategies are generally effective techniques and approaches
for accomplishing tasks that might be regarded as "tricks of the trade";
they don't always work, but when they do they are quite helpful. Most heuristics
are tacitly acquired by experts through the practice of solving problems;
however, there have been noteworthy attempts to address heuristic learning
explicitly (Schoenfeld, 1985). For example, a standard heuristic for writing
is to plan to rewrite the introduction and, therefore, to spend relatively
little time crafting it. In reading, a general strategy for facilitating
both comprehension and critical reading is to develop an overview and set
of expectations and questions about a text before reading line by line.
3. Control strategies, as the name suggests, control the process
of carrying out a task. As students acquire more and more heuristics for
solving problems, they encounter a new management or control problem: how
to select among the possible problem-solving strategies, how to decide when
to change strategies, and so on. Control strategies have monitoring, diagnostic,
and remedial components; decisions about how to proceed in a task generally
depend on an assessment of one's current state relative to one's goals,
on an analysis of current difficulties, and on the strategies available
for dealing with difficulties. For example, a comprehension monitoring strategy
might be to try to state the main point of a section one has just read;
if one cannot do so, then one has not understood the text, and it might
be best to reread parts of the text. In mathematics, a simple control strategy
for solving a complex problem might be to switch to a new part of a problem
if one is stuck.
4. Learning strategies are strategies for learning any of the other
kinds of content described above. Knowledge about how to learn ranges from
general strategies for exploring a new domain to more local strategies for
extending or reconfiguring knowledge as the need arises in solving problems
or carrying out a complex task. For example, if students want to learn to
solve problems better, they need to learn how to relate each step in the
example problems worked in textbooks to the principles discussed in the
text (Chi et al., 1989). If students want to write better, they need to
find people to read their writing who can give helpful critiques and explain
the reasoning underlying the critiques (most people cannot). They also need
to learn to analyze others' texts for strengths and weaknesses.
Method
Teaching methods should be designed to give students the opportunity to
observe, engage in, and invent or discover expert strategies in context.
Such an approach will enable students to see how these strategies combine
with their factual and conceptual knowledge and how they use a variety of
resources in the social and physical environment. The six teaching methods
advocated here fall roughly into three groups: the first three (modeling,
coaching, and scaffolding) are the core of cognitive apprenticeship, designed
to help students acquire an integrated set of skills through processes of
observation and guided practice. The next two (articulation and reflection)
are methods designed to help students both to focus their observations of
expert problem solving and to gain conscious access to (and control of)
their own problem-solving strategies. The final method (exploration) is
aimed at encouraging learner autonomy, not only in carrying out expert problem-solving
processes, but also in defining or formulating the problems to be solved.
1. Modeling involves an expert's performing a task so that the students
can observe and build a conceptual model of the processes that are required
to accomplish it. In cognitive domains, this requires the externalization
of usually internal processes and activities specifically, the heuristics
and control processes by which experts apply their basic conceptual and
procedural knowledge. For example, a teacher might model the reading process
by reading aloud in one voice, while verbalizing her thought processes in
another voice (Collins & Smith, 1982). In mathematics Schoenfeld (see
Collins et al, 1989) models the process of solving problems by having students
bring difficult new problems for him to solve in class.
2. Coaching consists of observing students while they carry out a
task and offering hints, scaffolding, feedback, modeling, reminders, and
new tasks aimed at bringing their performance closer to expert performance.
Coaching may serve to direct students' attention to a previously unnoticed
aspect of the task or simply to remind the student of some aspect of the
task that is known but has been temporarily overlooked. The content of the
coaching interaction is immediately related to specific events or problems
that arise as the student attempts to accomplish the target task. In Palincsar
and Brown's (1984) reciprocal teaching of reading, the teacher coaches students
while they ask questions, clarify their difficulties, generate summaries,
and make predictions.
3. Scaffolding refers to the supports the teacher provides to help
the student carry out the task. These supports can take either the forms
of suggestions or help, as in Palincsar and Brown's (1984) reciprocal teaching,
or they can take the form of physical supports, as with the cue cards used
by Scardamalia, Bereiter, and Steinbach (1984) to facilitate writing, or
the short skis used to teach downhill skiing (Burton, Brown, & Fisher,
1984). When scaffolding is provided by a teacher, it involves the teacher
in executing parts of the task that the student cannot yet manage. Fading
involves the gradual removal of supports until students are on their own.
4. Articulation includes any method of getting students
to articulate their knowledge, reasoning, or problem-solving processes in
a domain. We have identified several different methods of articulation.
First, inquiry teaching (Collins & Stevens, 1982, 1983) is a strategy
of questioning students to lead them to articulate and refine their understanding
of concepts and procedures in different domains. For example, an inquiry
teacher in reading might systematically question students about why one
summary of the text is good but another is poor, to get the students to
formulate an explicit model of a good summary. Second, teachers might encourage
students to articulate their thoughts as they carry out their problem solving
as do Scardamalia et al. (1984). Third, they might have students assume
the critic or monitor role in cooperative activities and thereby lead students
to formulate and articulate their ideas to other students.
5. Reflection involves enabling students to compare their own problem-solving
processes with those of an expert, another student, and ultimately, an internal
cognitive model of expertise. Reflection is enhanced by the use of various
techniques for reproducing or "replaying" the performances of
both expert and novice for comparison. The level of detail for a replay
may vary depending on the student's stage of learning, but usually some
form of "abstracted replay," in which the critical features of
expert and student performance are highlighted, is desirable (Collins &
Brown, 1988). For reading or writing, methods to encourage reflection might
consist of recording students as they think out loud and then replaying
the tape for comparison with the thinking of experts and other students.
6. Exploration involves pushing students into a mode of problem solving
on their own. Forcing them to do exploration is critical if they are to
learn how to frame questions or problems that are interesting and that they
can solve. Exploration as a method of teaching involves setting general
goals for students and then encouraging them to focus on particular subgoals
of interest to them, or even to revise the general goals as they come upon
something more interesting to pursue. For example, in reading, the teacher
might send the students to the library to investigate theories about why
the stock market crashed in 1929. In writing, students might be encouraged
to write an essay defending the most outrageous thesis they can devise.
In mathematics, students might be asked to generate and test hypotheses
about teenage behavior given a database on teenagers detailing their backgrounds
and how they spend their time and money.
Sequencing
Designers need to support both the phases of integration and of generalization
of knowledge and complex skills. We have identified some principles that
should guide the sequencing of learning activities in order to facilitate
the development of robust problem-solving skills.
1. Increasing complexity refers to the construction of a sequence
of tasks such that more and more of the skills and concepts necessary for
expert performance are required (Burton, Burton, & Fisher, 1984; VanLehn
& Brown, 1980; White, 1984). There are two mechanisms for helping students
manage increasing complexity. The first mechanism is to sequence tasks in
order to control task complexity. The second key mechanism is the use of
scaffolding, which enables students to handle at the outset the complex
set of activities needed to accomplish any interesting task. For example,
in reading increasing task complexity might consist of progressing from
relatively short texts, employing straightforward syntax and concrete description,
to texts in which complexly interrelated ideas and the use of abstractions
make interpretation difficult.
2. Increasing diversity refers to the construction of a sequence
of tasks in which a wider and wider variety of strategies or skills are
required. As a skill becomes well learned, it becomes increasingly important
that tasks requiring a diversity of skills and strategies be introduced
so that the student learns to distinguish the conditions under which they
do (and do not) apply. Moreover, as students learn to apply skills to more
diverse problems, their strategies acquire a richer net of contextual associations
and thus are more readily available for use with unfamiliar or novel problems.
For reading, task diversity might be attained by intermixing reading for
pleasure, reading for memory (studying), and reading to find out some particular
information in the context of some other task.
3. Global before local skills. In tailoring (Lave, 1988), apprentices
learn to put together a garment from precut pieces before learning to cut
out the pieces themselves. The chief effect of this sequencing principle
is to allow students to build a conceptual map, so to speak, before attending
to the details of the terrain (Norman, 1973). In general, having students
build a conceptual model of the target skill or process (which is also encouraged
by expert modeling) accomplishes two things: First, even when the learner
is able to accomplish only a portion of a task, having a clear conceptual
model of the overall activity helps him make sense of the portion that he
is carrying out. Second, the presence of a clear conceptual model of the
target task acts as a guide for the learner's performance, thus improving
his ability to monitor his own progress and to develop attendant self-correction
skills. This principle requires some form of scaffolding. In algebra, for
example, students may be relieved of having to carry out low-level computations
in which they lack skill in order to concentrate on the higher order reasoning
and strategies required to solve an interesting problem (Brown, 1985).
Sociology
The final dimension in our framework concerns the sociology of the learning
environment. For example, tailoring apprentices learn their craft not in
a special, segregated learning environment, but in a busy tailoring shop.
They are surrounded both by masters and other apprentices, all engaged in
the target skills at varying levels of expertise. And they are expected,
from the beginning, to engage in activities that contribute directly to
the production of actual garments, advancing quickly toward independent
skilled production. As a result, apprentices learn skills in the context
of their application to realistic problems, within a culture focused on
and defined by expert practice. Furthermore, certain aspects of the social
organization of apprenticeship encourage productive beliefs about the nature
of learning and of expertise that are significant to learners' motivation,
confidence, and most importantly, their orientation toward problems that
they encounter as they learn. From our consideration of these general issues,
we have abstracted critical characteristics affecting the sociology of learning.
1. Situated learning. A critical element in fostering learning is
having students carry out tasks and solve problems in an environment that
reflects the nature of such tasks in the world. Where tasks have become
computer based in the world, it is important to make them computer based
in school. For example, reading and writing instruction might be situated
in the context of students' putting together a book on what they learn about
science. Dewey created a situated learning environment in his experimental
school by having the students design and build a clubhouse (Cuban, 1984),
a task that emphasized arithmetic and planning skills.
2. Community of practice refers to the creation of a learning environment
in which the participants actively communicate about and engage in the skills
involved in expertise, where expertise is understood as the practice of
solving problems and carrying out tasks in a domain. Such a community leads
to a sense of ownership, characterized by personal investment and mutual
dependency. It can't be forced, but it can be fostered by common projects
and shared experiences. Activities designed to engender a community of practice
for reading might engage students and teacher in discussing how they interpret
what they read and use those interpretations for a wide variety of purposes,
including those that arise in other classes or domains.
3. Intrinsic motivation. Related to the issue of situated learning
and the creation of a community of practice is the need to promote intrinsic
motivation for learning. Lepper and Greene (1979) and Malone (1981) discuss
the importance of creating learning environments in which students perform
tasks because they are intrinsically related to an interesting or at least
coherent goal, rather than for some extrinsic reason, like getting a good
grade or pleasing the teacher. In reading and writing, for example, intrinsic
motivation might be achieved by having students communicate with students
in another part of the world by electronic mail (Collins, 1986; Levin, 1982).
4. Exploiting cooperation refers to having students work together
in a way that fosters cooperative problem solving. Learning through cooperative
problem solving is both a powerful motivator and a powerful mechanism for
extending learning resources. In reading, activities to exploit cooperation
might involve having students break up into pairs, where one student articulates
his thinking process while reading, and the other student questions the
first student about why he made different inferences.
Table 1 summarizes the characteristics of each of the four dimensions included
in our framework for designing learning environments. The content and sequencing
dimensions provide a striking contrast to the
focus on isolated mastery of discrete lower-level skills that is characteristic
of compensatory education programs developed in response to Chapter 1 legislation
(Means, Schlager, and Knapp, this volume). On the other hand, our framework
is entirely consistent with the goals of compensatory education, particularly
with respect to the high level of teacher-student interaction that both
the methods and sociology dimensions advocate. Though the cognitive apprenticeship
environment is important for all students, we want to argue that it is particularly
effective for students who are considered disadvantaged or "at risk"
because learning is embedded in a setting that is more like work, where
the tasks have some "authentic" relationship to students' lives
and where there is a community of people working together to accomplish
real-world goals (Brown, Collins, & Duguid, 1989). We contend that disadvantaged
students who learn in an apprenticeship environment will not only learn
the basic reading, writing, and mathematics skills that they have had difficulty
learning either in regular classrooms or in Chapter 1 programs, but also
will develop the more advanced skills characteristic of expertise. The remainder
of this paper is devoted to introducing two apprenticeship learning environments
that are currently being designed and evaluated.
Table 1. Principles for Designing Cognitive Apprenticeship Environments
Content: types of knowledge required for expertise
Domain knowledge subject matter specific concepts, facts, and procedures
Heuristic strategies generally applicable techniques for accomplishing
tasks
Control strategies general approaches for directing one's solution
process
Learning strategies knowledge about how to learn new concepts, facts,
and procedures
Method: ways to promote the development of expertise
Modeling teacher performs a task so students can observe
Coaching teacher observes and facilitates while students perform
a task
Scaffolding teacher provides supports to help the student perform
a task
Articulation teacher encourages students to verbalize their knowledge
and thinking
Reflection teacher enables students to compare their performance
with others
Exploration teacher invites students to pose and solve their own
problems
Sequencing: keys to ordering learning activities
Increasing complexity meaningful tasks gradually increasing in difficulty
Increasing diversity practice in a variety of situations to emphasize
broad application
Global to local skills focus on conceptualizing the whole task before
executing the parts
Sociology: social characteristics of learning environments
Situated learning students learn in the context of working on realistic
tasks
Community of practice communication about different ways to accomplish
meaningful tasks
Intrinsic motivation students set personal goals to seek skills and
solutions
Cooperation students work together to accomplish their goals
Two Examples of Cognitive
Apprenticeship for
Disadvantaged Students
We have been working at two schools during the last year where the majority
of the students might be considered at risk. We will briefly describe how
different forms of a cognitive apprenticeship have been implemented at the
Charlotte Middle School in Rochester, New York and the Central Park East
Secondary School in Harlem to demonstrate alternate approaches to applying
the principles of context, method, sequencing, and sociology outlined above.
Discover Rochester
Charlotte Middle School is an urban school located in a socioeconomically
disadvantaged neighborhood. It has approximately 64% minority students and
provides free or reduced-cost lunches for 56% of its students. Close to
30% of the students have been identified as moderate to high in terms of
being "at risk," which means that they can be characterized by
two or more of the following criteria: multiple suspensions, excessive absences,
repetition of a grade, failure of two or more classes in one year, and California
Achievement Test scores three or more years behind grade level.
A team consisting of two University of Rochester researchers and the eighth-grade
math, science, history, English, and writing teachers conceptualized and
implemented the Discover Rochester project. Generally speaking, the researchers
provided theoretical background and computer training for the teachers,
and the teachers contributed their expertise in curriculum design. All team
members served as leaders and facilitators during actual classroom sessions,
and all contributed to both formal and informal program evaluation and assessment
of student progress.
The goal of this project is to raise the skill levels of urban middle-school
students to reach beyond basic skills to develop sophisticated skills that
will help them succeed at work and in everyday life (Resnick, 1987). It
provides a model for redesigning middle-school learning environments based
on many of the principles advocated above, yet cast within the current constraints
of an urban school system. The aim is to increase student motivation, effort,
and learning by providing a learning environment that is sensitive to individual
needs, interests, and abilities. To accomplish this, students are provided
with computer tools that aid them in learning general thinking and problem-solving
skills as they explore their community and experience ways of applying their
school learning in the
real world.
In a pilot of the Discover Rochester project at the Charlotte Middle School,
"at risk" eighth graders spent one day each week exploring aspects
of the Rochester environment from scientific, mathematical, historical,
cultural, and literary perspectives. They worked in groups to conduct their
own research about topics ranging from weather to industry to theater to
employment, using a variety of strategies including library and archival
research, telephone and face-to-face interviews, field observation, and
experimentation. Based on their research, students developed a HyperCard
exhibit for the Rochester Museum and Science Center, including text, audio,
graphics, maps, and music.
The primary focus of the Discover Rochester curriculum is on explicitly
teaching general strategies while students investigate multiple aspects
of their own community in order to design an interactive learning exhibit.
Thus, students' learning is situated in an exploration of real-world topics
for a real-world purpose. The particular skills targeted by the Discover
Rochester curriculum are both control and heuristic strategies for learning
and communicating information. Students learned to coordinate five types
of skills to complete their exhibit: question posing, data gathering, data
interpretation and representation, presentation, and evaluationan elaborated
version of the Bransford et al. (1986) IDEAL program.
In the context of the interdisciplinary work, students practiced a variety
of heuristics for accomplishing each subtask. Specifically, explicit instruction
was provided in the following heuristic strategies:
- · Question posing: (a) brainstorming techniques for generating
interesting topics and deciding what students want to discover about those
topics, and (b) typical sequences of questions beyond the traditional "who?
what? why? where? when? how?" (e.g., when asking about someone's job,
generally ask for the job title,
responsibilities and risks, necessary
- · Data gathering: (a) reading and listening comprehension skills;
(b) strategies for using indices, headings, tables of contents, etc. for
finding information in texts; (c) interviewing techniques; (d) strategies
for using other nontraditional data sources, such as photographs and museum
exhibits; and (e) various techniques for recording and storing information
(e.g., notes, tapes, photos, and photocopies).
- · Data interpretation and representation: (a) strategies for viewing
data in historical and social contexts; (b) strategies for organizing and
analyzing data (e.g., categorization); and (c) various techniques for representing
information (e.g., expository vs. narrative writing, paragraphs vs. lists
vs. tables, and visual representations such as maps, timelines, and graphs).
- · Presentation: (a) strategies for considering the interests and
abilities of the audience; (b) strategies for clear organization, consistency,
readability; (c) specific skills for designing computer presentations, such
as designing modules, creating options for interactivity; and (d) skills
for verbally describing a nonverbal presentation.
- · Evaluation: (a) strategies for self-evaluation as well as peer
evaluation; (b) techniques for surveying users to get their feedback about
a presentation; and (c) strategies for considering and incorporating suggestions.
In terms of sequence, instruction progressed from global to local and from
less to more complex tasks by starting with an overview of all five skill
areas, highlighting heuristics already possessed by students or easily within
reach. For example, when asked about alternative representations for information,
students readily suggested paragraphs, lists, and drawings. The lesson would
then begin with showing how the same information could be presented in all
three forms and proceed to a discussion of which forms would be best in
which situations. As students began to understand the overall goals, teachers
introduced the more advanced heuristics. For example, once students started
to generate and evaluate alternative representations using text and pictures,
teachers introduced new types, such as timelines, graphs, and maps. Diversity
increased as students worked on more and more aspects of the exhibit. For
example, teachers and students began to discuss diverse types of graphs,
such as line, bar, pie) as a wider variety of graphing situations arose.
Also, the interdisciplinary aspect of the project incorporates domain knowledge
from four subject areas to highlight the use of similar general strategies
in all of them. For example, history concepts of city growth and science
concepts of animal and plant distribution might both be represented using
maps.
The teaching methods employed in the Discover Rochester project exemplify
all six of the principles described above. The lesson sequences began with
explicit descriptions of heuristics for each type of skill and teacher modeling
to demonstrate alternate approaches. Next, students practiced on prepared
materials designed to provide scaffolding in some of the five skill areas
to allow students to focus their attention on particular areas. Finally,
students spent most of their time in individual or small-group practice
in the context of self-directed exploration. As students worked on their
projects, teachers provided additional coaching and scaffolding as needed.
Students also spent a significant amount of time articulating their understanding
and reflecting on their progress as they designed and evaluated their exhibit.
The Discover Rochester learning environment was designed to embody a community
of practice by resembling the natural work environment. Students worked
primarily in one room for a two-period block of time in the morning and
another in the afternoon, rather than switching rooms every 40 minutes.
Students had ready access to computer tools for facilitating their work
(8 Macintosh computers for 20 students). They learned to use MacPaint, MacWrite,
CricketGraph, and HyperCard to the extent that they found the software tools
useful. Students also took an active role in directing their own learning.
By selecting their own topics within Discover Rochester and choosing when
to work independently and when to work collaboratively, they could focus
on their own interests, which increased their motivation for learning.
For example, at the beginning of the project, students and teachers worked
as a group to brainstorm about possible topics for study. They used maps,
phone books, information from the Chamber of Commerce,
etc., to help generate ideas. Students formed groups based on mutual interest.
One group decided to study Rochester's environment. They chose weather as
one subtopic and generated questions about the recent year's precipitation,
temperature, and wind patterns; how those patterns compared to the 30-year
norms; how proximity to Lake Ontario affected the weather. With these questions
in mind, they assigned each group member to research one subtopic and even
planned strategies for finding information (e.g., interview a meteorologist,
gather weather reports from local papers, check the library for information
on climate norms). Data gathering proceeded somewhat independently, but
interpretation, presentation, and evaluation were done more collaboratively
to encourage consistency in the final product. Throughout the process, students
called upon teacher or peer assistance when they needed it. In addition,
explicit lessons in general techniques were interspersed with the ongoing
activity of the group (e.g., effective interviewing techniques), and teachers
sought opportunities to practice subject area skills (e.g., interpreting
graphs).
During the pilot project, we observed impressive improvement in the students'
intrinsic motivation. Initially, students were sluggish, uncooperative,
and unimaginative. Some refused to talk at all. The initial brainstorming
session was more a lesson for the teachers in pulling teeth. As the students
developed new skills (particularly computer skills), they began to participate
more often, and many students took initiative beyond expectations. One student
took two pages of notes from library work done during a free period. Another
contacted administrators and legal counsel about the possibility of conducting
a survey in the school. A third learned how to do animation in HyperCard.
A fourth student made posters for the community showcase day, and about
one third of the group started working voluntarily during their lunch periods.
The students not only developed the five aspects of research and communication
skills, but also generated creative strategies for gathering and presenting
information.
As the students became more engrossed in the project, behavior problems
became almost nonexistent. On the first few days, there was a lot of off-task
behavior in both large- and small-group work, and students were more interested
in what happened in the hall between periods than in what happened in the
classroom. Over time, students started ignoring the activity in the halls
between periods as they pored over their work. Other teachers could not
believe that we would take these "troublemakers" on field trips,
but the students were polite and cooperative on all three trips we took.
On the first day of the project, students in the hall questioned why the
"dummies" got to use the new computers and they didn't. The participating
students initially perceived themselves according to the labels of their
peers. As they became proficient with the computers, they received a lot
of positive attention from both peers and teachers who were curious, envious,
and in awe of what the "dummies" had accomplished. They began
to perceive themselves as more competent than they had before, both in terms
of their current skills and in terms of their future career plans. One girl,
who won the award for the hardest working student, commented in a television
interview that she believed that she could do more things than she had before.
Another has decided to pursue a career that involves computers.
As the students explained their work to others, it was obvious that they
felt a sense of pride in how much they had learned. At the same time, their
standards for "good work" became stricter. Initially, students
approached their work by looking for the quickest and easiest solutions.
Before the students' first version of the HyperCard exhibit went into the
museum, they talked about how good it was and were convinced that there
was nothing they wanted to change. After interviewing students from other
schools who actually used the exhibit and found it boring, they started
reflecting on ways to improve their work. They actually implemented many
of their ideas and started paying more attention to detail and to their
audience as they added to the project; but, more significantly, as they
explained their work to peers and adults on the showcase day, they discussed
what they would like to improve in addition to bragging about what they
had done.
Many of the students involved in the project qualified for Chapter 1 instruction.
Some had been placed in "pull-out" programs for reading and others
received in-class help from the writing resource teacher. Despite the fact
that these students missed their special instruction in order to participate
in the project, their teachers reported that they improved more over the
course of the project than similar students who had received the regular
Chapter 1 instruction.
Though the students and teachers who participated in the Discover Rochester
pilot project spent only one semester working together, they began to develop
new skills, pride in their work, and a sense of community. By sharing experiences,
helping each other conquer difficult problems, and working toward a common
goal, they began to show signs of the investment and mutual dependency that
helps shift distraction to focus, resistance to initiative, and a critical
attitude to a constructive one.
While these informal evaluations of student progress are positive, more
formal evaluation of the project is necessary to determine whether the program
is achieving each of its specific goals, why it is working or not working,
and how the effective parts of the project can be exported to other sites
and other grade levels. Such formal evaluations will be initiated during
the 1990-91 school year. In the meantime, however, there are similarly positive
results emerging from other projects incorporating aspects of the framework
we have provided. For example, Roy Pea (Institute for Research on Learning)
and Richard Lehrer (University of Wisconsin, Madison) have implemented programs
in middle-school science, social studies, and problem-solving classes. Also,
the Genesee River Valley Project is an example of an interdisciplinary curriculum,
like Discover Rochester, that has been developed for third through sixth
grade urban students. For large-scale implementations such as these, the
formal evaluation must unfortunately be postponed until a stable implementation
is achieved, which is often a multi-year process. The Central Park East
example is such a case.
Central Park East Secondary School
For the past 12 years, Central Park East Elementary (CPE) and Secondary
Schools (CPESS) have been creating and refining a learning environment that
successfully challenges prevailing assumptions about the problems that urban
minority students have in achieving higher order learning goals. The secondary
school has 300 to 400 students and serves a primarily minority population
(about 90%), many of whom are eligible for the free lunch program (about
60%). The school's curriculum affirms the central importance of students'
learning how to learn, how to reason, and how to investigate complex issues
that require collaboration, personal responsibility, and a tolerance for
uncertainty.
The secondary school (CPESS) receives slightly over half its students from
three elementary schools based on the Central Park East (CPE) model. In
general, students are selected for the schools on a first-come, first-served
basis, but preferences are given to siblings and, in the secondary school,
to students who are likely to adapt to the culture of the school. Of the
first class that entered CPESS five and a half years ago, approximately
75% are still in the school, 15% changed schools after the eighth grade,
and 10% left because they moved or by mutual agreement. In later classes,
fewer have left the school, and school officials only know of one actual
school dropout. Attendance at the school averages over 90%, and there are
very few suspensions or fights. The students do better than city or state
averages on the Regency Competency Exams, but have not done well on the
PSATs compared to the national norms. The low scores on PSATs could have
many possible bases: (a) cultural bias, (b) a higher percentage of students
taking them at CPESS than nationally, and (c) the irrelevance of a project-based
curriculum to doing well on the PSAT. In any case, the school is remarkably
successful in educating its students by almost any measure.
In every class, students learn to ask and answer these kinds of reflective
questions: (1) From what viewpoint are we seeing, reading, or hearing this?
(2) How do we know what we know? What's the evidence, and how reliable is
it? (3) How are things, events, or people connected? What is the cause and
effect? How do they fit? (4) What if...? Could things be otherwise? What
are or were the alternatives? and (5) So what? Why does it matter? What
does it all mean? Who cares? A core of curriculum is offered to all students,
organized around two major fields: mathematics/science for two hours, and
humanities (art, history, social studies, literature) for two hours. Every
effort is made to integrate academic disciplines, so that students recognize
and understand the relationships among different subjects of study. The
communication skills of writing and public speaking are taught in all subjects
by all staff. The organization and scheduling of the curriculum allows for
maximum flexibility. Each team of teachers offers a variety of styles of
teaching, including group presentations, smaller seminars, one-on-one coaching,
and independent work in the studios, science labs, and library.
At CPESS, the school year is divided into trimesters,
and student work in each interdisciplinary curriculum area (math/science
and humanities) is organized around comprehensive student projects, called
exhibitions. The team of teachers in math/science, for example, collaboratively
generates the curriculum for the trimester and specifies the requirements
for the exhibition. Staff development at the school consists almost entirely
of teachers meeting together in small groups for half a day each week to
plan curriculum, as do the math/science teachers in the ninth and tenth
grades. By the end of the trimester, each student has completed a product
that fulfills the requirements for the exhibition. In addition, each has
done an oral presentation for a teacher in which she explains her exhibition
and demonstrates her understanding of the fundamental ideas.
The exhibitions the teachers assigned were situated in real problems of
the world. For example, in the first trimester of the math/science classrooms
where we have been working, ninth and tenth grade students designed amusement
park rides and specifiedthrough multiple representationsthe physical motion
principles exhibited by their designs. In the second trimester, they focused
on the physics concepts for a projectile motion of their own choosing (e.g.,
a foul shot in basketball, a curve ball in baseball). In the third trimester,
the students worked on exhibitions involving two-body collisions. In the
latter two trimesters, their work involved using a sophisticated simulation
system for the Macintosh called Physics Explorer (there were four Macintoshes
in two of the four ninth/tenth grade math/science classrooms). They created
models reflecting the kinds of motion they were studying and developed graphs
plotting vector components against time. Much of their written work involved
explaining changes in the vector components. Every student in the ninth
and tenth grades at CPESS is working on serious physics problems, whereas,
at most, 10% of students in the rest of the country study physics.
There are three aspects of the way the school is organized that reflect
a cognitive apprenticeship approach to education. First, learning is situated
by having students engage in projects that relate to the world about them
and help them to make sense of that world. Because of their long-term nature,
the projects reflect much more closely the nature of work. Students become
invested in them over time and gain an ownership of the ideas they develop.
For example, in the projectile motion project, one student calculated the
speed and angle necessary for a stunt car driver he admired to jump over
the Grand Canyon (which is not possible). When they work on projects, they
are using a variety of resources: the library, computers, and, importantly,
the adults and other students around them, just as people do when they work.
The teacher assumes the role of coach to help the students attack the problems
that arise as they work on their projects, and so the student has a kind
of autonomy not present in most schooling.
The second aspect of the school that we think critical is the emphasis on
articulation, reflection, and exploration in learning. In presenting their
exhibitions, students are required to make coherent presentations of their
materials and to answer difficult questions on the fly that probe their
understanding of what they have done. The effect of this training showed
up in one tenth grade girl, who on our first visit to the school was asked
by her teacher to explain to us what she had done on a difficult math problem
that she knew she had worked incorrectly (the problem: find the area above
a right triangle inscribed in a circle, given an angle of 30° and the
length of the hypotenuse). As she articulately explained her work, our questions
about why she had done each step helped her find the two errors she had
made. The emphasis on reflection is embedded in the kinds of questions students
are taught to ask, and in the ways that they are forced to think about what
they have done in order to explain and justify their work. The emphasis
on exploration derives from the project-based nature of much of their work
and the autonomy this fosters in students to control their own learning.
The third aspect we think is critical to the school's success is the learning
culture that has arisen among the students and staff of the school. Developing
this culture partly depends on starting in one of the three elementary schools
that feed students to CPESS and which share the same philosophy of caring
about students. Such caring is evident in the fact that there are only about
five fights in the school each year, many fewer than the other schools serving
the same population. But it is most evident in the way the students bond
to teachers, particularly their advisors (one staff member to every 12 or
13 students) and in the community sense that derives from the small size
of the school and the trips they take together. This community feeling in
the school fosters cooperation as students
try to accomplish the difficult tasks they are given.
Conclusion
By giving students long-term projects that deeply engage them and constructing
an environment that bodies the principles described in our framework, these
two schools have gone some way toward fostering cognitive apprenticeship.
Many of the students at the two schools are the kinds of students who are
labeled "at risk" in other environments. But working on difficult
projects that make sense to them and challenge them leads to dramatic increases
in their motivation to learn and think. Instead of treating these students
as failures, the programs succeed by treating them like adult workers.
Most schooling emphasizes the teaching of abstract knowledge, such as arithmetic
algorithms and grammar rules, that have little grounding in what students
see as useful. Schools usually attempt to teach students to apply these
abstractions with word problems and other artificial tasks. Our argument
(Brown, Collins, & Duguid, 1989) is that this is backwards. We need
to engage students in authentic tasks and then show them how to generalize
the knowledge they gain. Instead, educators have usually attempted to give
students who do not master the abstractions more and more practice or simplified
versions of the same kinds of tasks. This approach is a recipe for destroying
anyone's motivation to learn or think.
When education is embedded in authentic tasks, what is taught will be both
useful and useable. It is useful because it reflects the kinds of activities
people encounter in the world. It becomes useable because students learn
to apply the knowledge in accomplishing tasks. What are authentic tasks?
Our argument is that they should reflect the changing nature of work and
life. They include such tasks as: (a) understanding complex systems (e.g.,
computer systems, electronic systems); (b) finding information about different
topics in a large database; (c) writing a report or making an argument about
some topic; (d) analyzing trends in data; (e) investigating a particular
topic to answer some open-ended question; (f) interpreting a difficult text;
and (g) learning about some new domain. Accomplishing such tasks in the
future will depend on using computers and electronic networks. We should
not continue to educate students to communicate and calculate and learn
and think with primitive tools like card catalogues and arithmetic algorithms.
It is like teaching people to drive a car by having them practice riding
a bicycle.
The place to encourage change in education toward a more rational system
is in the education for the so-called disadvantaged students because these
are the students who have not been able to acquire even the basic skills
in regular classrooms, and because the current compensatory programs are
merely "widening the gap in terms of achievement of the more advanced
skills" (Means, Schlager, and Knapp, this volume). We see the beginnings
of an apprenticeship approach at Charlotte and Central Park East, and we
think it is worth a major investment in resources to carefully evaluate
these models and try to replicate them elsewhere in our failing schools.
We suggest that both the design and evaluation of subsequent apprenticeship
environments be based on the four dimensions in the framework we proposed:
- · Focus instruction and assessment on general strategies for accomplishing
tasks, for directing one's own behavior, and for learning new material,
as well as on domain specific concepts, facts, and procedures.
- · Use teaching methods in which students learn by observation and
guided practice in the context of defining and solving problems and in which
discussion and evaluation of developing skills is as important as practicing
them.
- · Sequence lessons so that students begin with a clear sense of
the high-level skills they are seeking and then acquire the component skills
as they work on authentic problems of increasing complexity and diversity.
- · Offer students an environment that reflects the changing nature
of work in society by initiating realistic activities, promoting communication
and collaboration among students and teachers, and providing appropriate
tools for learning.
References
Bransford, J. D., Sherwood, R., Vye, N., & Rieser, J. (1986). Teaching
thinking and problem solving: Research foundations. American Psychologist,
14(10), 1078-1089.
Brown, J. S. (1985). Idea-amplifiers: New kinds of electronic learning.
Educational Horizons, 63, 108-112.
Brown, J. S., Collins, A., & Duguid, P. (1989). Situated cognition and
the culture of learning. Educational Researcher, 18(1), 32-42.
Burton, R., Brown, J. S., & Fisher, G. (1984). Skiing as a model of
instruction. In B. Rogoff & J. Lave (Eds.), Everyday cognition: Its
development and social context. Cambridge, MA: Harvard University Press.
Chi, M. T. H., Bassok, M., Lewis, M. W., Reimann, P., & Glaser, R. (1989).
Self-explanations: How students study and use examples in learning to solve
problems. Cognitive Science,13, 145-182.
Collins, A., Brown, J. S., & Newman, S. E. (1989). Cognitive apprenticeship:
Teaching the craft of reading, writing, and mathematics. In L. B. Resnick
(Ed.), Knowing, learning, and instruction: Essays in honor of Robert
Glaser (pp. 453-494). Hillsdale, NJ: Erlbaum.
Collins, A. (1986). Teaching reading and writing with personal computers.
In J. Orasanu (Ed.), A decade of reading research: Implications for practice.
Hillsdale, NJ: Erlbaum.
Collins, A., & Brown, J. S. (1988). The computer as a tool for learning
through reflection. In H. Mandl & A. Lesgold (Eds.), Learning issues
for intelligent tutoring systems. New York: Springer.
Collins, A., & Smith, E. E. (1982). Teaching the process of reading
comprehension. In D. K. Detterman & R. J. Sternberg (Eds.), How much
and how can intelligence be increased? Norwood, NJ: Ablex.
Collins, A., & Stevens, A. L. (1982). Goals and strategies of inquiry
teachers. In R. Glaser (Ed.), Advance in instructional psychology
(Vol. 2). Hillsdale, NJ: Erlbaum.
Collins, A., & Stevens, A. L. (1983). A cognitive theory of interactive
teaching. In C.M. Reigeluth (Ed.), Instructional design theories and
models: An overview. Hillsdale, NJ: Erlbaum.
Cuban, L. (1984). How teachers taught. New York: Longman.
Lave, J. (1988). The culture of acquisition and the practice of understanding
(Report No. IRL88-0007). Palo Alto, CA: Institute for Research on Learning.
Lepper, M. R., & Greene, D. (1979). The hidden costs of reward.
Hillsdale, NJ: Erlbaum.
Levin, J. A. (1982). Microcomputer communication networks for education.
The Quarterly Newsletter of the Laboratory of Comparative Human Cognition,
4(2).
Malone, R. (1981). Toward a theory of intrinsically motivating instruction.
Cognitive Science, 4, 333-369.
Norman, D. A. (1973). Memory, knowledge, and the answering of questions.
In R. L. Solso (Ed.), Contemporary issues in cognitive psychology: The
Loyola symposium. Washington, DC: Winston.
Palincsar, A. S., & Brown, A. L. (1984). Reciprocal teaching of comprehension-fostering
and monitoring activities. Cognition and Instruction, 1, 117-175.
Resnick, L. B. (1987). Learning in school and out. Educational Researcher,
16(9), 13-20.
Scardamalia, M., Bereiter, C., & Steinbach, R. (1984). Teachability
of reflective processes in written composition. Cognitive Science,
8, 173-190.
Schoenfeld, A. H. (1985). Mathematical problem solving. Orlando,
FL: Academic Press.
VanLehn, K., & Brown, J. S. (1980). Planning nets: A representation
for formalizing analogies and semantic models for procedural skills. In
R. E. Snow, P. A. Federico, & W. E. Montague (Eds.), Aptitude learning
and instruction (Vol. 2): Cognitive process analyses of learning
and problem solving. Hillsdale, NJ: Erlbaum.
White, B. Y. (1984). Designing computer games to help physics students understand
Newton's laws of motion. Cognition and Instruction, 1, 69-108.
Zuboff, S. (1988). In the age of the smart machine: The future of work
and power. New York: Basic Books.
This work was supported by the Center for Technology in Education under
Grant # 1-135562167-A1 from the Office of Educational Research and Improvement,
U.S. Department of Education to Bank Street College of Education.
[ Home | About CCT | Projects | Newsletters | Reports | Staff | Links | EDC Home ]
Last Update: 11/18/96
Comments on the CCT Web site: Webspinner.
©1996 Education Development Center, Inc. All Rights Reserved.