Written Contributions to the EHR Advisory Committee
Social Sciences Workshop
________________________________________________________________________________

Convened February 22, 1996
at the National Science Foundation
Arlington, VA


                Participants in the Social Sciences Workshop
                          Convened February 22,1997


Listed alphabetically.  Titles indicate the speakers' positions at the time of
the Workshop.

Andrew Abbott                                   Maureen Hallinan
Master, Social Sciences Collegiate Division     Department of Sociology
The University of Chicago                       University of Notre Dame
Harper Box 76                                   Notre Dame, IN 46556-5644
1116 East 59th Street
Chicago, OL 60637

John Dovidio                                    Jill Larkin
Department of Psychology                        Department of Psychology
Colgate University                              Carnegie Mellon University
Hamilton, NY 13346                              Baker Hall
                                                Pittsburgh, PA 15213

Jacquelynne E. Eccles                           Nora Newcombe
Institute for Social Research                   Department of Psychology
P.O. Box 1248                                   Temple University
University of Michigan                          Weiss Hall, 6th Floor
Ann Arbor, MI                                   Philadelphia, PA 19122
 
Ronald G. Ehrenberg                             Neil Stillings
Vice President for Academic Programs,           School of Communication and
Planning, and Budgeting                         Cognitive Science
433 Day Hall                                    Hampshire College
Cornell University                              Amherst, MA 01002
Ithaca, NY 14853

Rochel Gelman
Department of Psychology
New York University
6 Washington Place, Room 307
New York, NY 10003


    Contributions of the Social Sciences to the National Science Foundation
                      Review of Undergraduate Education


Overview

On February 22, 1996, a group of eight invited scholars from the social and
behavioral sciences met to discuss the improvement of undergraduate education. 
Joining them were members of the Advisory Committee for Education and Human
Resources at NSF, the Assistant NSF Director for Education etc. (Luther S.
Williams), the Assistant NSF Director for Social and Behavioral Sciences (Cora
Marrett), representatives from several education and policy associations in
Washington DC, and NSF professional staff concerned about undergraduate
education.   Over 50 people participated in this workshop during the course of
the day.  The discussions were joined by most that were present at the workshop.

The workshop was designed as part of the extensive review of undergraduate
education being conducted by a Subcommittee of the Advisory Committee for
Education and Human Resources, which began the previous spring.  This review is
examining the status, conditions, and needs of undergraduate education in the
broad disciplines of the sciences, mathematics, engineering and technology.

The invited participants were asked to prepare short statements prior to the
workshop in response to a set of questions that focused on the contributions of
the social and behavioral sciences to improving our understanding of how to
improve undergraduate education.  The questions were:

     o  What has social and behavioral science research contributed to our
        understanding of how students learn?
        
     o  What are the obstacles to implementing change in curriculum and 
        instruction in undergraduate education?  How do we overcome them?
          
     o  What are the unanswered questions about student learning that research
        needs to address?  

     o  How does knowledge of the social sciences and of technology prepare 
        students for the next century? 

The following is a summary of the key points made during the workshop.  The
comments can be organized around four major themes: the undergraduate learner,
the teacher, the curriculum, and the institutional context.  To maintain a sense
of authenticity, direct quotes from participants have been included in a number
of places.  

The Undergraduate Learner

How the student learns, as well as individual and group characteristics of the
learners, are important factors to be considered.  At the beginning of the
workshop, participants agreed to a basic principle: the mind is active. 
Research in cognitive psychology indicates that "the mind always interprets,"
and is not simply "a passive receiver of information that is broadcast to it"
(Rochel Gelman, Department of Psychology, New York University).  Thus, the
presentation of new and interesting information in the classroom is not enough;
we must also understand how the minds of students interpret and manipulate that
information.

The processing of information by students is a vital point of concern.  Students
rarely realize the applicability of information and knowledge from one context
to another, and often view information as facts to be memorized and mechanically
reproduced in an exam.  In a rapidly changing world, a more desirable outcome
would be for students to possess the ability to apply abstract principles to
different situations, e.g. to "recognize situations in their own environments
where the Law of Large Numbers applies" (Neil Stillings, School of Communication
and Cognitive Science, Hampshire College, Amherst, Massachusetts).

Undergraduate students come from diverse communities and cultures with
distinctive expectations about the education process.  The values, norms, and
expectations of students about what to expect from undergraduate studies in
their chosen institutions of higher education are influenced by the size of the
institution, the selectivity of that institution, and the region of the country
in which it is located (Maureen Hallinan, Department of Sociology, University of
Notre Dame). Learning is inhibited when the values, norms, and expectations of
the student "come into clash with what we are at the moment doing in
institutions" (Rochel Gelman).   This point was underscored by some participants
with respect to the rapid pace of change that has occurred in some institutions.
Change should proceed in an orderly fashion, because "radical change in course
design breaks an unwritten social contract between faculty and students" (Jill
Larkin).

As will be developed in the remaining sections, developing educational
technology has a lot of potential for students in higher education.   However,
in the short run, technology scares a lot of students (Rochelle Gelman), and the
heavy use of technology scares more women than men.  "What we need from the
social sciences is some architectural perspectives on how to make technology
work" most effectively (Uri Treisman, Department of Mathematics, University of
Texas, Austin, and member of the Advisory Committee for Education and Human
Resources).

The Teacher

Because the teacher controls both what is taught and how it is taught, the
teacher is vital.  Five themes were discussed in the context of describing
effective and ineffective teaching techniques.

The disadvantages of the "broadcast model of education" were discussed.  Many
faculty consider the prerequisites for good teaching to be met "if I know and
understand my discipline, and I get up in front of the class and give good
lectures, and I give good assignments" (Jill Larkin, Department of Psychology,
Carnegie Mellon University).  However, there is evidence to suggest that simply
giving students more information does not improve learning.  A preferable
teaching paradigm is where teachers interact with their students and act as
facilitators in the learning process.

While traditional teaching methods often attempt to counter students'
misconceptions by teaching the 'correct' way to think, "curricula which take
misconceptions as a point of departure rather than a road block can be more
successful" (Nora Newcombe, Department of Psychology, Temple University).  New
techniques for teaching science should thus "arrange experiences in which
students realize how different aspects of their thinking are incompatible, then
work to resolve this impasse" (Nora Newcombe).  This will help to counter a
major problem, that many students have a "strange and impairing view of the
natural sciences and mathematics," seeing them as a collection of facts that are
hard to grasp (Jill Larkin).   More stress on applied research in the classroom
will also help, many agreed.

Research conducted by sociologists suggests "that working in groups in a
cooperative setting produces greater growth in achievement that straining for
relative gains in a competitive environment (Maureen Hallinan).  Thus it is
important for teachers to provide students with opportunities to work in groups.

Technology, such as email and bulletin boards, provides opportunities for
faculty to interact with students at a greater frequency, while Web pages
provide new information resources for students. However, technological
innovation is costly in terms of the "human effort that has to go into designing
it," as well as the human investment of educating teachers to use these
innovations (Neil Stillings).  Evaluating the effectiveness of new technology in
the classroom is also problematic because "we don't have quality benchmarks ...
to bring these innovations together with some of our learning theories" 
(Kenneth Foote, Department of Geography, University of Texas, Austin).

Improving undergraduate education by teaching faculty how to teach includes
helping them to effectively use everything from "the oldest and most transparent
technology" of a blackboard, to "tens of thousands of dollars worth of
multimedia equipment" (Daniel Goroff, Derek Bok Center for Teaching and
Learning, Harvard University, and National Research Council).  Improving
undergraduate education entails that teachers as well as students invest in
learning new skills.  It is important to use technology effectively, to promote
interactions among students, faculty, and material, and to avoid using it as
merely another method of broadcasting information to passive student recipients.
In learning to use technology, and use it wisely, many older faculty are seen
as irretrievably lost, while younger faculty typically recognize that print
media is losing its effectiveness (Andrew Abbot, Master, Social Sciences
Collegiate Division, University of Chicago).

Curriculum

Much of the current curriculum of the sciences, mathematics, engineering, and
technology in college courses "follows an instructional paradigm, not a learning
one" (Luther S. Williams, Assistant Director, NSF).   The following themes focus
on how curricula can facilitate learning by students.

Students interpret new information in the context of what they already know. 
However, students in a classroom begin from different places.  To promote
learning in the classroom, faculty must provide "stepping stones from the minds
of our students who may not overlap" with the structure mapped by teachers, "to
the point where they have in fact achieved understanding that they didn't have
in the first place" (Rochel Gelman).  Thus, the content of the curriculum should
be flexible enough to accommodate students' different learning styles and
starting points.

In many institutions, the majority of students fulfill science requirements
through social science courses.  The "social sciences tend to be great fields
for hands-on experience with science" (Neil Stillings).  To the average
undergraduate, the social sciences offer better accessibility to knowledge
relative to the physical and biological sciences.  " It's very important to put
students in a context where they can connect their understanding of physical and
biological knowledge with social life, with the life of the mind, and that means
we have to put them in classrooms where things about the brain and about
behavior genetics are being taught together with things about behavior and
society so that they can make that connection" (Neil Stillings).  If the study
of experimental design and statistics in the social sciences are combined with
topics in cognitive science such as causal reasoning and normative models of
thinking, and this is done effectively, then greater numbers of students will
achieve a reasonable level of scientific literacy by grasping the significance
of these connections. Also, "cognitive science is a good vehicle for teaching a
lot of mathematics and computer programming" (Neil Stillings).  Thus, in
general, students benefit from a curriculum that has an interdisciplinary
approach.

However, "beyond the question of the social sciences contributing to the broad
issue of the learning of science ... we have to give increased emphasis to the
social sciences themselves" (Luther Williams).  Despite the promise of the
social and behavioral sciences as a metaphor for buttressing student
understanding of the physical and biological sciences, there are problems
specific to these fields that are more extensive than found today in the natural
sciences, namely, that passive learning is perhaps more widespread, and basic
research on curriculum and learning in these fields is considerably behind. 
This may be due to the fact that a growing majority of high school graduates now
attend college and enrollments in the social and behavior sciences have been
swelling. Consequently there is less introspection about student learning than
is found in the natural sciences and engineering.

To achieve significant and lasting improvements in undergraduate education, we
must be able to pinpoint whether students successfully learn curriculum content.
Many students have the idea that "understanding something is kind of being
familiar with it" rather than trying "to really master something" (Jill Larkin).
From the perspective of most faculty, current forms of evaluation often mean
that "we give an exam, hand it back and then go on with the next lecture (Jill
Larkin).  This does not tell us, in general, whether mastery of the material has
been achieved.  Successful evaluation should include a feedback loop where
faculty and students together can determine the extent of mastery.  

Institutional Context

In order for undergraduate education to improve on a large scale, the
institutional context in which it takes place must be examined.  Change is more
likely to occur if it is supported at the institutional level.  The following
themes suggest some ways to accomplish this objective.

The potential for systemic reform has been improved by the development of new
educational technologies.  New teaching models, often incorporating some of the
potential of new technology, "cut across traditional disciplinary and really
university boundaries" (Kenneth Foote).  With the appearance of the Internet and
the Worldwide Web, the walls of departments and universities must be permeable
enough to "cultivate ... more types of local, regional, and national
collaborations" (Kenneth Foote).  Institutions that promote these kinds of new
linkages are more likely to benefit from new technologies and ideas.

Cost constraints already are demanding that most universities have large class
sizes, despite evidence suggesting that smaller classes have an environment more
conducive to learning.  Thus, administrators of institutions of higher education
need to "start to think about how to facilitate these kinds of needs within the
environment" of large class size that currently exists in many institutions
(Rochel Gelman).   Investment in technology may allow for students and faculty
to have more interaction at a lower cost by providing "other ways to communicate
the same type of lecture material" (Ronald Ehrenberg, Vice President for
Academic Programs, Cornell University).

In the existing institutional context, "we don't have good integrative
mechanisms for thinking about making sensible decisions about how to affect the
trajectories" or paths that students take throughout their undergraduate
education as well as after they leave (Melvin George, Chair of the Subcommittee
of the Subcommittee of NSF Advisory Committee for Education and Human
Resources).  We must focus on issues of choice of major and course-taking, and
pay increased attention to the high percentages of students who do not complete
their undergraduate education.

Meanwhile, the discussion continued to emphasize that though the pace of
institutional change is accelerating, it is important to retain the "human
touch" of contact between faculty and students. There has been a lot of research
on the impact of mentoring on student achievement and persistence that informs
us that careful mentoring is a powerful force.  Furthermore, even modest
indications of faculty interest in their students and student learning outcomes
have a big impact on student effort and persistence.  For example, faculty tend
to get high marks on student evaluations even in courses with difficult material
and examinations if the faculty have demonstrated a minimal level of caring, for
example, being able to call on students by name, keeping track of class
attendance, and demonstrating a willingness to discuss problems outside of class
time.


               The Social Sciences and Undergraduate Education


                                Andrew Abbott

    Professor in Sociology and Master, Social Sciences Collegiate Division
                            University of Chicago
                              Chicago, Illinois


There are two aspects to the role of the social sciences in undergraduate
education. The first is the place of the social sciences in the content of
instruction. The second is the contribution of social science research to
understanding the impact of undergraduate education on those who are taught.

Social Sciences in the Curriculum

Of the place of the social sciences in the content of undergraduate education
there is little doubt. In the ideal curriculum, the social sciences are both an
essential, freestanding constituent of "core learning" and an important subset
of majors for upper level students. That is, the social sciences are crucial to
both general and specific education at the undergraduate level. In my own
university, social sciences constitute six courses in the required curriculum of
22 (of 42 total) quarter courses, and social science majors constitute the
plurality (about 42 percent) of undergraduate majors.

At the level of general education, the social sciences raise two kinds of
issues. In our curriculum these are contained in the two different required
sequences: core and civilizations.

Our core sequences inquire into certain basic problems of social life:
individual and group, freedom and determinism, equality and inequality,
personality and culture, difference and similarity. The exact content of our
five core courses varies, although there is a tendency to focus on classic texts
and on particular modes of inquiry. What does not vary is the classroom
structure and pedagogical technique. The classes are small (maximum 25-30), are
taught largely by Ph.D.-level faculty (about 75 percent), and are largely
discussion-based. This reflects our strong belief that general education is not
about content but about the skill of critical reading and thinking. We aim to
create citizens who can think clearly, critically, and creatively about the
social life that surrounds them. This can be accomplished only in small classes,
where faculty can intimately model the process of reflective thought, and where
students' work - both oral and written - can receive the detailed comments that
alone promote effective learning.

Each of the five core sequences has a number of "tracks" - from five to fifteen
at any given time - taught by individual faculty. Within a course, tracks share
about 70 percent of their curricula, so that student learning continues in the
dormitory and lounge as students from different tracks argue about common
themes. Across tracks, faculty meet weekly to discuss pedagogy, to argue about
text materials, and to plan future curricula. Such staff meetings offer an
important resource to faculty, both in terms of sharing of pedagogical secrets
and in terms of interdisciplinary learning, for the courses are generally
staffed across disciplines.

The five core tracks really shake down to two curricula:
Plato-Aristotle-Machiavelli-Locke-Hobbes- Marx and friends and
Smith-Marx-Durkheim-Weber-Freud and friends. From time to time, we have also had
a core sequence based on empirical social science, which takes students from a
quarter on philosophy of inquiry through a quarter on actual social science
research to a quarter on policy. Even in such a sequence, however, the focus
continues to be on addressing basic questions; classic texts continue to provide
an organizing role, augmented by doing actual social science research.

The other required social science sequence is civilization; a much more
complicated pedagogical structure. There are three teaching rationales behind
the civilization sequences: a concern with contingency and diversity, a concern
that students contact a culture or cultures different from theirs, and a concern
that students truly understand their own culture, whatever that may be. Two of
our civilization sequences are taught in "core format," as just described:
Western Civilization (about 40 percent of students in 16 tracks) and American
Civilization (about 10 percent of the students in 4 tracks). The others are
taught in the more standard lecture/recitation format. All, however, tend to
focus on classic texts. These are reviewed and updated periodically.  (Those for
American Civilization are on-line, for example.)

The civilization sequences (the largest eight of them cover 95 percent of the
students) generally involve history and anthropology faculty. For faculty, the
problems of curriculum planning and design again produce the interdisciplinary
contact of the core courses. For students, this interdisciplinary gives rise,
again, to a complicated, nuanced approach to learning.

Beyond the required curriculum, we also have, as I noted, a steady 40-45 percent
of the majors in the College. As in most colleges, the largest is economics, but
social science in fact dominates the University of Chicago undergraduate scene;
we have four of the largest six majors (economics, political science,
psychology, and history). Extensive research, which I mention below, shows that
students treat their majors essentially as an advanced form of liberal
education. Most of our students do not perceive their choice of major as related
to a career decision. (Two-third of our premeds major outside biological
sciences, for example.) As a result, learning in the majors is driven again by
the problem of mastering a specific body of skills and thinking, the skills and
thinking of advanced inquiry in a particular field. It is this specific
discipline, not the content that alumni report as important in their later
lives.

The center of this specific learning is the B.A. paper, required in most of our
majors. At its best (in our history program), the major introduces the student
to the problems of advanced thinking with a junior colloquium, then advances by
associating paper-writing seniors with preceptors at a ten to one ratio. The
resultant papers are read and improved by faculty in their later drafts, once
they have been effectively pre-prepared. Other majors work essentially like
mini-curricula, with introductory sequences, methods courses, and upper-level
electives. In general, our majors are effective but "quick" curricula. The
exigencies of the core, the tendency of students to front-load their science
requirements (we require year-long sequences in BOTH physical and biological
science), and the tendency of many students to switch into social sciences late
in their career.  It means that the social science majors must move students
through the discipline of advanced knowledge faster than is done elsewhere.

It should be noted that our curriculum assumes that the social sciences are an
independent area of knowledge, between the social sciences and the humanities.
They are not a stepchild of either, but rather proudly freestanding. In part
this reflects institutional history; we are perhaps the only major university in
which the social science departments enjoy higher national rankings than those
in either humanities or natural sciences, a situation that has persisted from
the 1920s. Moreover, the curricular structure has been etched into the internal
administrative organization since 1929, when Robert Maynard Hutchins divided the
faculty into Divisions (Humanties, Social Sciences, Physical Sciences,
Biological Sciences), each with a Dean responsible for graduate teaching and
general oversight and (since the end of a separate College Division in 1963) a
Master responsible for undergraduate teaching and the College's half of the
personnel jurisdiction. We have no faculty of Arts and Sciences and no
overarching Dean. Divisions report to the Provost.

Thus a central question of this [EHR Advisory Committee] Review - whether the
social sciences can serve as a vehicle for "science education" - is ruled out of
court. Our faculties do not feel that social science learning can be collapsed
into natural science learning or vice versa.

Social Science Research and the Undergraduate Experience

In the area of research on the curriculum, however, the social sciences have
much to say. I here report on a large investigation under way at Chicago with
the help of the Ford Foundation.

Three years ago, the Foundation provided us with a grant for the support of
social science majors at the University. (This was part of a larger program
involving a number of leading universities.) With this funding, I have
undertaken a large body of research aimed at two fundamental questions, neither
of which has ever seen much study.

The first and simpler of these questions is that of origins. Nobody seems to
have asked why we have majors in the first place. There was one dissertation,
long ago, on the subject. I have supported research into the history of majors
with an idea to finding out the original pedagogical rationale as well as the
administrative forces driving the change. It has indeed proved that to a
considerable extent we have majors because we have departments, majors proved a
way of solving the administrative problem of regulating universities that, for
the first time, had numbers of faculty concentrated in particular areas. On the
other hand, majors were also a crucial part of reining in the chaos of the
electives-based curriculum of the late 1 9th century, and in that sense an
alternative to the core-based programs (at Columbia, Chicago, and elsewhere)
that attempted the same structuring of the curriculum but in a different manner.
Other than the conflict with core-based curricula, there has been no serious
challenge to the idea of majors in the 20th century. As with the graduate
intellectual life, however, it seems that there is much more overlap in the
actual contents of majors than in the disciplinary origins of the faculty
teaching them. On the ground, considerable interdisciplinarity has probably been
the normal state of affairs.

The second and more difficult question we have addressed is the impact of the
major on the later life of students. Because Chicago has had for at least twenty
years a curriculum with both a serious core and serious majors, we are able to
ask specific questions about the relation of these for students in choosing
Chicago, in studying here, and in their later lives. Ideally, such research
should be prospective, and I would certainly propose that for the future. But at
present, we have mounted a large "synthetic cohort" examination of the problem.

This analysis includes the following components:

     1. A survey of the class of 1995
        o  300/700 responded information on parents' majors, employment, hopes
           for children on respondents' aims in high school and later, choice of
           major, choice of career, satisfaction with education, etc.

     2. A sequence analysis of exact transcripts of 1995 class (entire) to study
        changing of majors, juggling of required curricular elements, the actual
        "experience" of education in terms of order and structure.

     3. A survey of all alumni who have been out 2,5,7,10,15,and 20 years 
        1400/3600 responded (still coming in)
        o  information on parents' majors, employment, hopes on respondents' 
           choice of major, impact of major and of core on later occupational
           and intellectual experience (we have data at the level of specific
           intellectual skills - problem analysis, writing, creativity, etc.)

     4. A diary project 
        o  ten students have kept detailed diaries of their educational
           experience across three years.

     5. A retrospective course examination 
        o  twenty-five students (1996 seniors) will prepare essays discussing
           their experience in retrospect.

These data will permit us to examine the impact of different parts of the
curriculum on later experience.

Our central research questions here all involve the "trajectory" of education; a
topic that seems relatively little studied. Questions include:

     1. How are core and major related to later occupational life?
     
     2. How is core and major related to other parts of respondents' lives? 
        citizenship? participation in cultural life?
        
     3. How do students imagine their college careers?
     
     4. How does reality cut across students' expectations and early college 
        experiences?
        
     5. What are the impacts of parents' hopes and dreams on students' lives? 
        are these specific to specific ethnic groups? occupational types?
        
     6. Which parts of the curriculum produce or support which kinds of skills
       in adult life?

The underlying vision here is one envisioning education as a process and seeking
the forces that channel that process in a particular direction. My own
expectation is that skills training lasts far longer into and proves more
valuable for adult life than does specific content, and that the disappearance
of major content from the horizon of adult experience is quite quick. But these
are empirical questions, to be addressed only by surveying an alumni body with
long-standing experience of a particular curriculum.

The University of Chicago is an elite institution. Results, and indeed research
questions, will probably be quite different at another kind of university. This
issue seems to me one of the most difficult facing the workshop. I am confident
we could agree more on the content of the kind of education proposed here than
we can either on the content of other forms of education or indeed upon the idea
that education for elites and masses are likely to be fundamentally different.
But the latter point - the recognition that elite and mass higher education is
likely to differ - seems a crucial one. Such research as we have on learning
seems to indicate that amount and quality of feedback to students is the strong
predictor of good education, and effective feedback requires staff quality and
intensity unreachable at most public institutions. I propose this issue without
any idea of how we should address it.


Andrew Abbott is Professor in Sociology and Master of the Social Sciences
Collegiate Division at The University of Chicago.  His current work includes a
theoretical book on time and social structure as well as diverse analyses in the
methodological area of optimal alignment and sequence analysis.  He is also
currently writing a book on the concept of college majors and the experience of
generations of University of Chicago Students with the University's
concentration program.


                 Scientific Literacy and the Social Sciences


                              John F. Dovidio

                          Department of Psychology
                             Colgate University
                             Hamilton, New York


In a world increasingly shaped by science and technology, a fundamental
understanding of science is an essential aspect of contemporary education. We
can no longer talk of science and the liberal arts; science must be an integral
part of a liberal arts education. While I suspect that there will be little
debate about the importance of scientific literacy, there may be fewer
consensuses about how this can be generally achieved. The focus of this brief
presentation will therefore be on question #3: In many institutions, students
take courses in the social and behavioral sciences as a means to fulfill their
science distribution requirements. In what ways can and do these courses
effectively promote scientific and quantitative literacy?

As a basis for the presentation, I will use the case study of Colgate
University.  Colgate is a selective undergraduate liberal arts institution
enrolling approximately 2,800 students and employing about 240 faculty members.
It has a strong emphasis on majors (concentrations), as well as a distribution
requirement - two courses in the sciences: social sciences, and humanities and a
core general education program. Of course, I choose this example not solely
because of its representativeness, but also because of the availability of the
data I will be presenting.

Despite the increasing need for general science education, there are currently
several practical barriers to achieving this objective successfully. First,
although there is renewed interest in the sciences among students compared to a
decade ago, still relatively fewer students major in the science compared to the
social sciences and humanities. Five years ago, 22 percent of the graduating
Colgate students majored in the sciences; today that figure has improved to 28
percent. Nevertheless, 33 percent currently major in the humanities and 39
percent major in the social sciences. Therefore, we cannot necessarily depend on
science concentrations to provide a science education for students in general.
The vast majority of students do not major in science.  Second, perhaps because
of lack of interest or lack of preparation, a substantial portion of students
take the minimal amount of science possible within the liberal arts curriculum.
As I noted earlier, Colgate has a two-course-per-Division distribution
requirement. Thirty-four percent of Colgate students graduate with only these
two science courses on their transcript (compared to 24 percent with the minimum
social science and 9 percent with the minimum humanities requirements). Third,
in a time of diminishing financial resources to higher education, the costs of
traditional science education are high and are escalating. At Colgate, the
average department budget allocation per faculty member in the sciences is six
times what it is in the humanities and four times what is in the social
sciences. Start-up costs are ten times higher in the sciences than in the
humanities or social sciences. Because of teaching credit for laboratories,
science instructors teach only .8 of the range of courses per year as other
instructors, and the sciences accommodate only about 28 percent of the total
enrollments. Recently, the controversial study from the University of Rhode
Island has raised questions about the overall cost- effectiveness of pursuing
research grants.  An Important question then becomes: How can we provide a
better general science education for students in the face of these barriers?

The answer I propose is that the social sciences can effectively and efficiently
contribute to science education in ways that complement and support the
traditional sciences. Colgate's experiences offer some insights because it's
unusual Division structure. The Division of Natural Sciences and Mathematics
consists of biology, chemistry, computer science, geology, mathematics,
physics/astronomy and psychology. Psychology is considered a social science on
many, if not most, other college campuses. Using the social sciences more
effectively can help overcome each of the obstacles I just raised; the first
issue involves capturing student interest in courses that can potentially make
major contributions to scientific and quantitative literacy. Among the seven
science departments, psychology's enrollments have consistently been the
highest. In addition, unlike each of the other departments, it did not
experience the dramatic decline in enrollments of the 1980s. Among those
students taking only the minimum two-course science distribution, psychology
courses are clearly the courses of choice: 73 percent of those students had a
psychology course as one of those two courses. Geology was second with 37
percent. The traditional, central sciences, such as chemistry and physics were
largely represented in these students' records (3 percent and 4 percent; see
Figure 2.2). The attraction of Psychology is not likely easy grades; the average
grade in the introductory psychology courses is the lowest of all of the
introductory science courses. Thus, social science courses may provide an
inherently attractive avenue among students for achieving the essential goals of
a general science education. 

The curricula of some social science disciplines may also be particularly 
well-suited to developing general scientific and quantitative literacy because 
of their explicit focus on methodology and statistical analysis. Table IV.1 
lists the departments in which a statistics (or mathematics course) is a 
required or elective course in the major.

Table IV.1
    Departments with statistics or mathematics courses as required or elective
    courses (science departments in boldface type). 

                       Required                 Elective
--------------------------------------------------------------------------------           
                   Computer Science             Biology
                       Economics               Education
                      Mathematics              Geography
                        Physics            Political Science
                       Psychology              Sociology


The science concentrations not on this list - astronomy, chemistry, and geology
- instead have required instrumentation courses. Although experience with
sophisticated, state-of-the-art scientific equipment may be essential for
students continuing on in science, the development of transferable quantitative
and information management techniques may be significantly more useful to the
general student who will not pursue formal scientific training beyond graduation
- and can be provided effectively at a fraction of the cost of equipment,
supplies, and overhead.

At the introductory course level, social science courses that emphasize the
application of the scientific method and experimental approaches to verification
can be as effective as traditional science courses in achieving essential goals
of scientific literacy in a context or personal relevance to students. Figure 2
[projected slide not published here]  illustrates a comparison of student
responses (1 = "disagree strong1y" to 7 = "agree strongly") to three statements
identified by science faculty as central objectives of a general science
education:  (1) "The course required me to engage in scientific reasoning"; (2)
"After taking this course, I am more able to evaluate current issues and
problems"; and (3) "The course improved my problem-solving skills." The
responses to these items for three traditional introductory science courses
(biology, chemistry, and geology) are compared to Introductory Psychology and to
an interdisciplinary Introductory Environmental Studies course (reflecting an
integration of areas of biology, geology, and geography). The two "non-science"
courses are generally as effective - and in some ways are more eff6ctive - in
achieving the general goals identified by the faculty.

Because of the hierarchical nature of science curricula, the burden of providing
the prerequisite factual information to prospective majors may interfere with an
emphasis on the process of scientific inquiry that may be an essential aspect of
a general science education for non-majors. Thus curricula that offer
alternative entries to the major, rather than a strict linear sequence, may
offer more opportunity for pedagogical innovation and flexibility and time to
devote to an understanding of the process of scientific inquiry. Among the
sciences, only geology offers multiple alternative entries to the concentration.
The majority of the social sciences (i.e., not psychology or economics) allow
different entry points. Recently Colgate has introduced a series of pilot
Scientific Perspectives courses, which are staffed by social scientists as well
as natural scientists as part of the required Liberal Arts Core program. These
are designed to enhance scientific literacy, by focusing on the process of
scientific inquiry with the mastery of a specific body of factual information,
as a secondary concern. The results of student responses to these courses,
separated by those taught by social scientists (economists and psychologists)
and those taught by natural scientists, are presented in Figure 3 [projected
slide not published here]. These results compare favorably to the results for
the traditional science courses depicted on the previous figure. Thus, teaching
introductory science may not be the only or the most effective way to achieve
scientific literacy among non-science majors. In addition, science literacy may
be achieved at least as effectively through selected social science courses.

In conclusion, it is currently particularly important to recognize and support
the role of the social and behavioral sciences in science education. The
incorporation of selected social science courses to complement traditional
science courses in scientific education programs is valuable because:

o  Social science courses are currently attractive to students
      o  the topics and issues are of immediate relevance to students
      o  these courses may be accessible to a wide range of students because 
         they normally do not rely on pre-requisite high school preparation

o  Social science courses may provide a cost-effective alternative
      o  these courses normally have lower start-up equipment expenses and 
         reclaiming costs for supplies
      o  these courses do not normally require dedicated laboratory space; when
         equipment (such as computers, network links, graphics equipment) is 
         needed, it frequently can be used for multiple other purposes
      o  the skills that are acquired in laboratory experiences (e.g., computer
         or networking skills, skills in information retrieval, evaluation, and
         management, and skills in quantitative analysis) are highly 
         transferable skills that will benefit students beyond graduation.

o  The social and behavioral sciences may offer curricular and pedagogical
   flexibility
      o  this flexibility may allow the adaptations needed to meet the needs of
         non-science students
      o  more flexibility in the amount and nature of information presented can
         permit a more deliberate and self-conscious examination of the 
         scientific method, experimental procedures, and data analysis
      o  the topics of study may offer more obvious and direct connections to 
         the use and misuse of scientific information and technology
      o  the use of less structured laboratories can encourage the use of a 
         wider range of pedagogical strategies, such as cooperative learning and
         creative problem solving.


John Dovidio is Director of the Division of University Studies, past Director of
the Division of Natural Sciences and Mathematics, and Professor of Psychology at
Colgate University.  He served on the Executive Committee of the Society for
Experimental Social Psychology and is Editor of the Personality and Social
Psychology Bulletin and the author of several books, book chapters, and numerous
articles focusing on racism and on altruism. Academic Press and Prentice-Hall
will, soon publish two new works, Experimental Design and Statistical Methods
and Social Psychology, respectively.  Dr. Dovidio is the recipient of many
awards and distinctions, including the Professor of the Year award conferred by
Eta Sigma Phi, a first year students' honors society.


         Why Study Economics? Why Teach It Using Frontier Technology?


                             Ronald G. Ehrenberg
       
        Vice President for Academic Programs, Planning, and Budgeting
  Irving M. Ives Professor of Industrial and Labor Relations and Economics
                             Cornell University
                              Ithaca, New York


Teaching Introductory Economics at Cornell University Using the Worldwide Web

Cornell University has revamped the way it teaches Introductory Microeconomics
using Worldwide Web technology. Partially as a result of the need to conserve
faculty resources, Cornell reduced the number of lecture sections of
Introductory Microeconomics that are taught throughout the University and
increased the average lecture class size by roughly 50 percent (from 250 to
380). My colleague, John Abowd, who is a continual NSF Economics Program grant
winner and a former NSF Economics Program Advisory Committee member, assumed
responsibility for one of the classes. He did so motivated by the belief that
students at selective research universities should be exposed early on in their
education to prominent researchers and that they should be taught using frontier
technologies.

Abowd's course is structured as follows:

On the first day of class students are given a multiple-choice exam that tests
their knowledge of, and ability to apply, all the concepts to he learned
throughout the semester in the class. Scores on each question for each student
are stored on his server for future use by him.

Students are forced on to the Worldwide Web as lecture notes for the class are
placed on the Web in advance of the professor's in-class lectures. Not
surprising, attendance is lower than one observes in comparable size classes in
which the lectures have to be attended to learn the professor's views. However,
as noted below, Abowd can actually test if attendance, per se, improves
performance.

Given the scale of his class, Abowd has enough teaching assistant (TA) resources
to conduct office hours for multiple hours each day. Cornell is located on a
very spacious campus and while the TAs are physically located in one room,
students do not have to actually go to that room to see them. Rather, they can
go to any one of a number of locations on campus and be "connected" to a TA
using a computer technology that allows two way audio and visual contact between
the students and the TA. Alternatively, they can communicate with the TAs by
electronic mail.

Whenever a student asks a question relating to a point in the lecture notes, a
star is placed on that spot on the Worldwide Web copy of the lecture notes. By
"clicking" on that star any student in the class can read the question and see
the answer. Effectively, use of the Web has multiplied the value of office
hours. All students now have the potential to learn from the questions of any
one. In the language of economists, office hours, which once were a private
good, have become a public good.

Periodic exams are given in the course. Some of the questions are, in fact,
identical to those given on the pretest. Thus Abowd can learn which specific
concepts/questions are the ones that the students are having the most difficulty
learning. Put another way, he can learn which sections of the lectures confuse
rather than clarify things. Given the students self-reported class attendance,
he can also estimate if attendance per se influences what students learn. 

Weekly problem sets are given in the form of spreadsheets found on the web sight
and answers must be submitted over the web. While students have complained about
being forced to learn a new technology that is not essential to economics, they
quickly master it and then observe how spreadsheet programs facilitate "what
if?" discussions.

This course has not been an easy one to get off of the ground in spite of the
Herculean efforts of Abowd for a number of reasons. First it has required a
substantial initial capital outlay for equipment, including remote
teleconference sites. Individual departments do not have the resources needed to
develop such equipment funds; the university as a whole has to at least be
partially responsible for them.

Second, it has required funding for all of the Web programming for the lecture
notes, problem sets and exams. While it is rapidly getting easier to translate
word processor files into Web-compatible format, this is not something that most
"mature" professors feel themselves capable of doing. Many new undergraduates
have mastered the technology and they provide the necessary labor pool for this
activity.

Finally, Abowd is easily among the top 5 percent of all Cornell professors in
terms of his facility with new technology. Once he has created the course
structure, other colleagues can adapt it for their own courses. But how many of
us will? And who will pay for the extra support costs such courses entail? Our
saving in faculty time is only a saving to the university if we reduce the size
of the faculty and/or use the freed up faculty type in some other revenue
producing activity (e.g. off- campus learning or continuing education on
campus). So far, most faculty and universities show little inclination to do
either.

The Importance of Economics in the Curriculum

Research by economists (some of it funded by NSF) has demonstrated that the
likelihood that any individual will spend his or her career with a single
employer, or even in a single occupation, has declined in recent years. To have
a successful career, individuals must be flexible and adaptive to continually
changing technologies and economic forces. Learning to become accustomed to the
former while in college may be almost as valuable to students in the long-run as
the subject matter they study.

I say "almost" because I strongly believe that it is important that students
study economics in college. Economics provides a conceptual framework that they
can use to analyze private and public decision problems throughout their lives.
Such basic (to an economist) concepts as demand and supply, the tendency of
markets to move towards equilibrium, maximizing behavior under constraints,
marginal analyses, externalities, opportunity costs, the prisoner's dilemma, the
importance of relative prices, moral hazard, unintended side affects of
decisions, adverse selections and rational expectations provide students with
"tools" to help them evaluate their own private decisions and the issues they
read about in the newspapers that policy makers continually face.

I regularly taught a course at Cornell for about 15 years called the "Evaluation
of Social Programs." For six weeks I dazzled the students with my knowledge of
quasi-experimental design and Campbell and Stanley's "threats" to internal and
external validity.  Showed the students how to implement the designs in the
context of regression models and how each of the "threats" corresponded to an
econometric problem, demonstrated how to compute sample sizes needed to obtain
statistically significant program effects, and finally introduced them to
benefit/cost analysis in a social context. I then spent the final eight weeks
applying these models and techniques to the evaluation of labor market programs
and policies, always using simple microeconomic models to conceptualize things.
By the end of each semester I was always convinced that I had "wowed" students
with how much I knew and with how exciting social policy analysis was.

Several years ago I ran into one of my former undergraduate students, who by
then was high up in the human resource department of a major corporation. He
told me that my course was the most valuable course that he had taken at Cornell
and that he used concepts from it regularly in his work. I was dumbfounded. My
course dealt with social programs; he was working for a private corporation.
Ultimately I realized that he understood much better than I did what the course
was really all about. Our job as academic economists is to increase our
student's analytical abilities, not to cram them full of specific applications
that interest us. Fortunately, the tools of economists are sufficiently useful
that sometimes students understand this point, even if we don't ourselves.


Ronald Ehrenberg is the Irving M. Ives Professor of Industrial and Labor
Relations and Economics, Director of Research, and Director of the Institute for
Labor Market Policies at the School of Industrial and Labor Relations, Cornell
University, and a Research Associate at the National Bureau of Economic
Research.  He received a Ph.D. in economics from Northwestern University in 1970
and has authored or co-authored over 100 papers and books in the areas of public
sector labor markets, wages in regulated industries, labor market programs and
legislation, resource allocation issues in education, and the incentive effects
of compensation systems.  Effective July 1, 1995, he became Vice-President for
Academic Programs, Planning, and Budgeting at Cornell.


             Social Science Education, Information Technologies,
                          and Virtual Universities


                              Kenneth E. Foote

                   Associate Vice-President for Research
                     The University of Texas at Austin
                                Austin. Texas


I wish to concentrate on only a few of the issues that are the focus of today's
agenda. My stress will be on technology and the way it is transforming the
entire learning process, affecting our vision of how and what to train students,
and changing our repertoire of best practices. First I want to draw attention to
the role of the social, behavioral, and economic disciplines in basic science
education.

On my campus, the fact is not always appreciated that the social, behavioral,
and economic sciences play a major role in basic science education, whether
measured in student numbers or innovative projects. For a large cohort of
students, basic science requirements are met by courses outside of the natural
and biological sciences and engineering. Instead, their contacts will arise from
courses in sociology, demography, anthropology, archeology, psychology,
economics, geography and the like. Even though this is the case at many other
campuses too, I realize that it is not always weighted as heavily as it perhaps
should be in efforts to improve scientific literacy and the quality of the
American scientific workforce. Yet within these disciplines, faculty is clearly
concerned with these issues. They are taking the challenge of scientific
literacy to heart and developing very promising models that address the broader
concerns of general science education, in at least two ways.

In the first, stress has been placed on cultivating the analytical and
problem-solving skills of students through active learning strategies. Too
often, science curricula seem to value mastery of content over comprehension of
the process of research and investigation. New prototypes seek to redress this
situation and reassert the importance of cultivating analytical reasoning skills
in the undergraduate curriculum. Social scientists are using small-group
learning techniques and collaborative problem-solving to engage students in
active debate and investigation of pressing scientific, political, and social
issues.

Second, many social scientists are attempting to span disciplinary boundaries by
challenging students to consider concepts and issues from interdisciplinary
perspectives. The sense here is that conventional disciplinary boundaries are
increasingly blurred in both theory and practice and students must learn to
apply conceptual and analytical skills from many disciplines, rather than those
of a single field. These projects often rely on a team of faculty drawn from
several departments to address a single important and interesting topic, such as
sustainable development or environmental quality, from a variety of
perspectives. All of these projects take a fresh look at the curriculum and
attempt to move away from compartmentalizing knowledge within time-worn
disciplinary categories. Such projects are likely to increase in number and
scope in coming years as means of reintegrating specialized undergraduate
curricula.

The Impact of New Technologies

Some of the most exciting curriculum development projects involve creative
applications of information technology. As recently as a few years ago,
information technology was equated solely with the use of microcomputers in
traditional quantitative subfields such as econometrics, demography,
experimental psychology, or my own field of geographic information systems.

But it is now apparent that information technologies are rapidly and
irreversibly transforming higher education and the ways in which students and
scholars learn, teach, communicate, conduct research, disseminate knowledge, and
serve the public. Scholars from all disciplines are experimenting extensively
with multimedia, hypertext, Internet resources, distance learning, and many
other techniques that fall under the broad heading of information technology.

Hypermedia authoring techniques have just recently become accessible to large
numbers of scholars and in the past two years Internet and the Worldwide Web
have made it possible to develop high- quality on-line course materials. As the
academic community masters these resources, experiments will go even further. It
is now easy to envision "virtual" departments, disciplines, or universities in
which ready access to educational resources of all sorts is available through an
easy-to-use graphical interface. The idea of using the Internet and hypermedia
resources to link faculty and students from many departments and universities
is, in some respects, just around the corner. Such cooperative endeavors would
not only expose students to a richer educational environment but also help to
average out the high development costs of hypermedia resources. This summer I am
starting up NSF- funded Geography Virtual Department Project. Over the next
three years, geographers from all over the United States will gather at the
University of Texas to plan and develop materials to support an entire
undergraduate geography curriculum on-line in the Worldwide Web. The Western
Cooperative for Educational Telecommunications has just made public a sound plan
for a Western Virtual University that can begin to be realized almost
immediately.

Toward the Virtual University: Needs, Requirements, and Programs of the Future

Support will be required for disciplines and entire universities as they
re-invent themselves to serve new and diverse clienteles throughout the nation
and world using a new generation of learning technologies, but how? It is not
just a question of massive new investment. Change is taking place so rapidly
that large investments in unproved technologies can be very risky.

But, unfortunately, a wait-and-see attitude is just as risky. It can jeopardize
the lead American universities have assumed in cyberspace. My suggestion is to
look carefully at the processes of change themselves. If these new technologies
are to benefit students and society through the educated used of information,
people and systemic reform of institutions will be as critical to the process of
change as the evolution of the underlying technologies. The "virtual university"
must be viewed as the product of a process of change across the entire knowledge
base of higher education. The transformation will involve:

    1.  Active collaboration of faculty, students, and staff in the development
        of new teaching and curriculum models and materials that will link 
        across traditional disciplinary and university boundaries and result in
        systemic change of undergraduate and graduate education. 
        
    2.  Careful evaluation and testing of prototypes including the cultivation
        of new modes of peer review, planning, and collaboration. 

    3.  Comprehensive support for time invested in developing these new models
        including equipment, staff, and rewards that cut across conventional
        distinctions among educational, research, and public service.

    4.  Sustained support for collaborations and partnerships that will 
        contribute to and draw upon far broader efforts to interlink advances in
        K-12 and collegiate instruction at the local, regional, national, and
        international levels.

This means that some traditional distinctions are gradually losing their
relevance. Even the clearest divides among disciplines are disappearing as
faculty and students build intellectual bridges electronically. Separate
universities are finding themselves no more than a click away from one another
on the computer screen. The sharp distinctions that were once made among
research, teaching, and public service have blurred substantially. The most
pressing question in this situation is what can be done at the national level to
insure that these changes support the nation's lead in science education.
Attention should be give to programs that:

    1. Stress systemic reform of science education within individual 
       institutions by reinforcing collaborative linkages among disciplines and
       approaching the knowledge-base of higher education as more than the
       simple sum of the social, behavioral, economic, biological and natural
       sciences. A strong faculty enhancement component is essential so that
       faculty can gain the skills and support needed to make a success of these
       efforts. American universities have never before been asked to "retrain"
       faculty on the scale they are today. It will be very important to adjust
       the academic rewards system to recognize this fact 
   
    2. Promote innovative educational partnerships at all levels to highlight
       the fundamental relationship between K-12, collegiate, and graduate
       science education. Such partnerships might also benefit from close 
       connections with business and industry. Consortia must be cultivated at
       the local, regional, and national levels.
   
    3. Establish rigorous benchmarks for the review, testing, and evaluation of 
       these internal linkages and external partnerships. These benchmarks must
       be suited to the demands of new modes of technology enhanced learning and
       must address both the process of development and the products that are
       created.
       
    4. These internal linkages, external partnerships, and quality benchmarks
       must be conceived with an eye toward broader education horizons, both 
       temporally and spatially. What are needed are models and prototypes that
       can be scaled up to encompass the emergence of other linkages and
       partnerships through time and are robust enough to be applied to many 
       different types of institution all across the country. 


Kenneth Foote joined the faculty of the University of Texas at Austin in 1983
after training at the University of Chicago and the University of
Wisconsin-Madison.  In addition to his research in cultural geography and
American landscape history, Dr. Foote has many years' experience teaching
computer cartography, geographic information systems, and spatial statistics. 
He is the director of his department's Environmental Information Systems
Laboratory.  He is now beginning the Geography Virtual Department project to
interlink geography curricula nationally and internationally using the Worldwide
Web.  Dr. Foote was awarded the University of Texas President's Associates
Teaching Excellence Award in 1992.


              Contributions to the NSF Social Sciences Workshop


                                Rochel Gelman

                           Professor of Psychology
                    University of California, Los Angeles
                           Los Angeles, California


The last twenty years or so of research on learning and cognition has born
witness to a theoretical sea change. The widespread view that the mind absorbs
whatever data it is offered has given way to an alternative. This is that the
mind actively selects, interprets and even creates environments with reference
to existing knowledge bases.

These active tendencies of mind are pervasive; they reveal themselves as much in
studies of social cognition as they do studies of learning about mathematics and
physics. When the same news clip is shown to Israelis and Palestinians, both
report that it is a biased presentation in favor of the other. When fractions
are introduced to the curriculum, children interpret them as novel examples of
the natural numbers, reporting that 114 is more than 1/2 "because 4 is more than
2" or 1/76 is more than 1/65 "because 76 is more than 65." We are more inclined
to attend to things we know something about; we interpret what we encounter with
reference to what we already know. These active tendencies of mind have deep
implications for education.

Educators no longer can assume that they material they offer learners will be
interpreted as intended. Whether or not learning proceeds depends heavily on
whether there is structural overlap between what is already known and the
to-be-learned body of knowledge. When there is overlap, there is a reasonable
chance that students will move along domain-relevant learning paths. When there
is not overlap, there is a non-trivial chance that students will unwittingly
misinterpret what they are offered, often enough in ways that are hard to
anticipate. For example, it never occurred to me that my undergraduates would
"hear" Kant as Can't. (I now write Kant's name on the board when I first
introduce his ideas about knowledge and learning).

These facts about cognition are especially relevant to our discussions for
today. When our goal is to teach a new body of knowledge to undergraduates
expertise in one's discipline does not guarantee success in the classroom. The
odds are high that there are qualitative differences between the knowledge
structures of learners and teachers. Indeed, there is reason to anticipate gaps
between learners and learners given our commitment to universal literacy be it
in the humanities, social, physical or biological sciences, sciences,
humanities. I will expand on this point in my remarks about the way that
cognitive research can facilitate the goals of undergraduate education.


Rochel Gelman is a Professor of Psychology at UCLA and Visiting Scholar at NYU. 
NSF supports her research on the early understandings and subsequent learning of
mathematical and scientific concepts.  She also collaborates with cognitive
scientists on programs designed to support the acquisition of scientific and
technical literacy - in ways that are appropriate for preschool settings, high
school English as a Second Language classes, and beginning undergraduate courses
in the biological and physical sciences.  She is the author of The Child's
Understanding of Number (1978) with C.R. Gallistel and the editor of The
Epigenesis of Mind (1991) with Susan Carey.  Gelman's awards include fellowships
from the Center for Advanced Study in the Behavioral Studies, Palo Alto, a
Guggenheim Fellowship, and ones for an Early Career Research Contribution and
Distinguished Scientific Contribution from the American Psychological
Association.


               Social Science Research and the Learning Process


                             Maureen T. Hallinan

                        White Professor of Sociology
                          University of Notre Dame
                             Notre Dame, Indiana


Learning is a function of student ability, motivation and effort. These three
factors interact in a non-linear manner to produce knowledge. In addition,
learning takes place in a social context, which differs for each student by
their ascribed and achieved characteristics. The contribution of the social
sciences, and sociology in particular, to an understanding of how to improve
undergraduate education is based, in large part, on the research that has been
conducted on the various components of this learning model.

In general, psychology has led the social sciences in broadening our
understanding of student ability. Recent research on the nature of intelligence
has challenged old narrow definitions of intelligence that were almost solely
related to analytical abilities and to cognitive thinking. Identifying different
bases for intelligence and for understanding the world has made a significant
impact on attitudes toward the learning process and toward achievement. More
research needs to be conducted in this area, both to increase our understanding
of intelligence and to disseminate this work to educators. The implications of
this work for curriculum content, pedagogical techniques and performance
evaluation are profound.

Psychologists also have made significant advances in understanding of individual
differences in learning strategies. Their research has identified several
different learning styles, such as visual learners and kinetic learners, and
demonstrated that the better the fit between a teacher's instructional
techniques and the student's learning style, the more the student learns.

Both psychologists and sociologists have addressed the issue of student
motivation. While psychologists have been concerned about intrinsic motivation,
sociologists have studied extrinsic motivation in the form of rewards and
sanctions. Sociological research has examined whether students are more
motivated in cooperative or competitive environments and working individually or
in groups.  Findings suggest that working in groups in a cooperative setting
produces greater growth in achievement than straining for relative gains in a
competitive environment.

Motivation also is affected by student interest in the subject matter. 
Sociological research on the organization of instruction in secondary schools
demonstrates that the higher the quality of instruction, the more interesting
the curriculum and materials, and the greater the amount of time exposed to the
curriculum, the greater the growth in achievement.  The social organization of
students for instruction affects the quality and quantity of instruction.
Organizational arrangements such as ability grouping and tracking at the middle
and secondary levels have been shown to differentially channel opportunities to
learn to students who differ in ability. The higher the ability group or track
level, the higher the quantity and quality of instruction and, even with ability
controlled, the greater the growth in achievement. At the college level, the
quantity and quality of instruction also varies across courses. Access to the
most favorable learning situations varies by student characteristics, such as
ability, and linkages to faculty and peers who can provide relevant information
about courses.

Another factor affecting student motivation is the influence of peers. A large
body of sociological research demonstrates that peer groups are a significant
factor in the learning process. Students who belong to a peer group that
devalues academic work are less likely to succeed academically than those who
have peer models who are serious about academic achievement.  Peers affect the
amount of time spent studying, the nature of non-academic activities (wholesome
or dangerous), the choice of courses, educational aspirations and academic
achievement. Some studies show that school personnel can modify an anti-academic
peer culture through the creation of desired rewards and through the expansion
of the bases for social hierarchies.

Research reveals that individuals differ in the relationship they see between
motivation and effort. Students with similar levels of motivation may expend
different amounts of effort to attain their educational goals. Coleman's
research identified a race effect on students' sense of "locus of control", with
black students believing that luck played a greater role in outcome than white
children. Cultural differences in the value and effects of effort also have been
documented. With the increased racial, ethnic and cultural diversity of college
campuses, the need to take these differences into account only increases.

Other contextual variables that affect learning include the size and composition
of the class. A large body of research demonstrates that the larger the class
the slower the growth in achievement. The linkages between class size and
academic achievement include degree of student participation in class, number of
teacher-student interactions, and student self-esteem. Studies also show that
the stronger the academic climate of the class, usually related to the student
distribution of achievement, the greater the effort and achievement. Here, the
mechanism connecting academic composition to learning involves role models and
socialization.

In addition to the contextual variables that affect the dynamics of learning
depicted in the learning model, individual ascribed and achieved characteristics
affect learning. In a recent article in The Chronicle of Higher Education,
Jerome Kagan cites studies showing that the components of self- esteem differ by
the history and cultural background of the individual.


Similarly, the way the components of the learning model interact to produce
knowledge differ by the gender, race, ethnicity, socioeconomic status and age of
students. They also differ by family characteristics and by school factors. This
is undoubtedly true at undergraduate institutions as well as primary and
secondary schools. A better understanding of these interconnections will provide
better direction to educators who design and implement college curriculum and
instruction.


Maureen Hallinan is the White Professor of Sociology at the University of Notre
Dame and President of the American Sociological Association.  Her research
interests are in the area of sociology of education.  She is currently studying
the effects of tracking on mathematics learning.


       The Social Sciences Contribution to the EHR Undergraduate Review:
                        Comments on Guiding Questions


                               Jill. H. Larkin

        Department of Psychology and Center for Innovation in Learning
                         Carnegie Mellon University
                          Pittsburgh, Pennsylvania


Background

Personal experience underlies many of the following comments. Therefore, I
provide here a brief summary of the most relevant experience.

            The Carnegie Mellon Center for Innovation in Learning

Carnegie Mellon University provides funds for a center with a charge to use
research results, experimentation, and technology to improve education at
Carnegie Mellon. Four tenured faculty, as well as one senior scientist, have
full- or part-time appointments within the Center. Other faculty may apply for
one-semester sabbaticals at the center. During this time they work to improve
one or more undergraduate courses, and gain general expertise in the science of
education, which they can continue to apply to their work and share with others
in their department. These faculties remain associated with the Center as
"affiliates" and have desk and computer space to continue to work there when
they wish.

The center also supports graduate students and post-doctoral fellows who work
jointly with CIL faculty and an outside faculty member to apply scientific
education to improve a target undergraduate course.

             Applying Cognitive Science to Pre-College Education

For six years I headed the James S. McDonnell Foundation's Program in Cognitive
Studies for Educational Practice. It provided good support (~$300,000/yr for
three year terms), for cognitive researchers to begin to move research results
towards pre--college classroom applications. The program produced some stunning
examples of how well this approach can work. (See, Bruer, J. and McGilley, K.)

      Developing an Innovative Introductory Course in Cognitive Psychology

Over the past 12 years I have taught an increasingly innovative course which
provides an introduction to cognitive psychology. I organize the course around
three main models appearing in modern cognitive psychology (network models such
as ACT, rule models such as Soar and CAPS, and neural or parallel-distributed
processing models).

The student body is diverse, including students from all four years and all five
of the "colleges" of Carnegie Mellon (Humanities and Social Science, Fine Arts,
Engineering, Mathematics and Mathematical Sciences, Computer Science). Thus
there is an enormous range in type of interest and ability to handle the
quantitative aspects of the course. I have experimented extensively with
technology use, and with various pedagogical methods.

At this time, I believe the course is a cognitive success, with highly mixed
sociological and motivational results. By the end of the course, most students
can solve problems, write essays, and answer a special kind of very challenging
multiple-choice question indicating understanding of the three model-types, and
ability to apply them to a variety of data and every-day situations. However, as
indicated by course evaluations and student comments.  Many students do not
"feel" they have learned much, and are others dissatisfied with the course
format.

What other research efforts in the social and behavioral sciences inform us
about the learning process?

                              Social Psychology

Social psychology has had little attention from scientific educators with
consequences that are now becoming obvious. Everyone I know who dramatically
restructures an undergraduate course initially experience hostility and
unhappiness from the students. (A recent report in Science dramatically
documents this effect for NSF sponsored introductory calculus courses.) However
good the instructional design, and even the instructional effectiveness, unhappy
students are undesirable. Ultimately courses that students don't like are not
viable.

We need to understand how school-sophisticated undergraduates' view their
"social contract" with a professor. What should and should not happen and why?
Can we work with students' expectations instead of against them? Can we exploit
other features of the student-professor relationship in achieving good learning
outcomes? This is uncharted territory, and crucial to continued success in
applying results of behavioral science to improve instruction.

                               Applied Research

The McDonnell Program (briefly described above) was successful because it
recognized an area ripe for exploitation and provided realistic funds to attract
first-rate scientists to attack the problems of doing the exploitation. Research
results do not jump to classroom application without several years of
experimentation, and trial and error. Prototypes must be expanded to coherent
curricula. Materials appealing enough in the laboratory must now catch and hold
attention of more varied students in an environment with many distractions. New
methods, practical for groups of students must be developed. Through this
process, one wants to avoid simply trying to make a curriculum, but to maintain
a goal of keeping the instruction tied to learning principles. Without this, the
result is merely one more curriculum, and not a contribution to the science of
education.

                          Meta-Knowledge of Science

Students have well-known misconceptions in both physical and behavioral sciences
(e.g., the so-called "cognitive illusions" in probability). Less well
documented, but apparent to all thoughtful teachers, are students'
misconceptions about the goals and nature of science. Most students believe
science is a collection of facts and rules, and that their learning task is to
memorize some of this collection, perhaps along with some straightforward ways
to apply the rules.

The behavioral sciences can, in my view, provide a particular opportunity for
teaching how science works. Introductory physics (for example) teaches a
well-developed theory that has been stable for many years. It may look to
students like immutable fact, unconnected with human enterprise. In contrast,
the younger behavioral sciences involve smaller scale models, which are
regularly challenged and modified as new experimental evidence appears. Most
students find this sequence baffling at first. (But in Chapter 3, they said...!)
But this confusion gives an entree to discussing science as a process for better
describing observations. 

Most students lack the ability to construct a scientific argument, including 
data, theoretical statements, and links between them. We have repeatedly 
observed students' omitting any or all of these components in both history and 
psychology.

                           General learning skills

Just as students lack knowledge of the nature of science, and often have
misconceptions that interfere with effective learning, there are parallel
problems in students' knowledge and beliefs about learning.

                              Passive Learning
                              
Many students see learning as a passive process. They attend lectures, read
assignments. Study consists of ... "sitting somewhere comfortable, preferably in
bed, and paging through notes and textbook" - quote from a parent. The idea that
learning requires active practice seems often entirely foreign. "It's a strange
thing with this course. 1 don't understand what's going on until after I've done
the homework and taken the exam" - email from a student in my psychology course.
"I've learned twice as much in class as in the other two Psychology courses
combined. The reason is that this is a hands-on course. Here I've done things" -
paraphrase of a comment from another student in the same course. Students' model
of understanding often seems to be mere familiarity with the terms and phrases.

                        Failure to Learn from Errors

Students too rarely have the ability (or the motivation) to use mistakes as an
opportunity for learning. For example, in my course, if a student believes there
is a correct explanation for a multiple-choice answer graded as incorrect,
sending me an explanation by email produces either a grade change (if I agree
with the student) or a careful explanation of where the student's thinking is
wrong. About 30 percent of the students never use this opportunity. The answers
I've heard to the question, "Why not?" include: "I didn't really understand that
I could do this. It's so firm in my head that an exam is an exam, and you get
the grade, and that's that." "Arguing with the professor is for grade-grubbers
and poor students." "I did so poorly I just didn't want to think about it any
more."

Although my particular treatment of tests is unusual, these quotes illustrate
clearly that many students do not use test results as an opportunity to learn.
(See also Gagne, E., Cognition & Instruction) We need to teach students how to
use errors as a cue to their own misunderstandings, and how to work towards
detecting and preventing similar misunderstanding in the future.

              Lack of Even Primitive School and Learning Skills

Colleagues who regularly visit many classes at Carnegie Mellon tell me that
40-50 percent attendance is common, and that of those present, there are still
the sleepers and the note-passers in the back. I have reluctantly developed a
system of requiring and checking attendance (collecting a class assignment in
each lecture). Many students have great difficulty taking notes, especially on
class discussion. And, as reflected by some of the previous comments, many have
little idea how to study.

Specifically, I believe that many of my students have no idea how to study
"actively." I suggest repeatedly a technique of working either with oneself or a
partner to generate and answer questions about the material. I show a method for
generating such questions. We maintain a bulletin board where students post
questions they can't answer. Sometimes other students answer. Ultimately I
either endorse some students' answers, or provide comments of my own. But, as
indicated by some of the comments quoted above, this is clearly not an activity
many students use. 

The difficulties are almost certainly both cognitive and social or motivational.
The methods of effective study are certainly as difficult as the methods of 
psychology or physics. We need to analyze them and teach them effectively. But,
even more than subject-matter procedures, these must be procedures students are
motivated to use. Thus again, I emphasize the need for more social psychology
to use as a base in improving instruction.

In many institutions, students take courses in the social and behavioral
sciences as a means to fulfill their science distribution requirements. In what
ways can (do) these courses effectively promote science and quantitative
literacy?

                                 Difficulties

       1. Traditional teaching methods (lectures & reading)
          The student is passive, except for one or two exams, and perhaps a 
          term paper.
          There is no weekly homework, often any regular discussion sessions. If
          there are discussion sessions, the teaching assistants may receive 
          little or no training or guidance.

       2. Little background of basic research
          There has been little research in cognitive processes in these arenas 
          (and little financial support for such work). Thus we must translate
          from research in other fields (e.g., physics, mathematics), and begin
          some basic research in these areas.
       
       3. Current textbooks
       
          o  Textbooks (at least in psychology) usually have a historical 
             organization, and do not integrate material so as to make it easier
             to learn.
          o  Worse, textbooks often make integration especially difficult for
             students. For example, introductory psychology textbooks
             universally refer to experiments by authors' names and publication 
             date. Since few students know automatically what Posner and Boyes 
             did, if they wish to integrate, they must go to the author index,
             and then back to the page describing Posner & Boyes' experiment. 
             Use of mnemonic titles for key experiments could solve this whole
             problem.

Opportunities

     1. Modern social science is highly quantitative.
        Therefore perhaps we can transfer approaches similar to those effective
        in the physical and mathematical sciences.
     
     2. There are educational journals in this area, which may contain useful
        lore to use as guidance.

     3. As the behavioral sciences mature, it becomes possible to better 
        integrate the material we teach. (See, for example, my comments on 
        structuring cognitive psychology. 

What are the ways in which technology is being incorporated into courses in the
social and behavioral sciences to enhance learning and the curriculum and also
to promote technological literacy?

The notes below summarize how I use technology, or have seen it used 
effectively.

     1. Presentation software: sideshows, animation, integrated video material.
     
     2. Visualization: before presenting formal models, I use animation to show
        how the model works qualitatively.
     
     3. Interaction software: class response systems (Classtalk) bulletin
        boards; Web.

     4. Computational instruction: computer-assisted learning, tutors, 
        hypertext.

     5. Commercial software: spreadsheets, graphs, outlining, and writing.

     6. Public domain research-level models. Increasingly researchers make
        available their model code.

     7. Data analysis: Many commercial packages aid in qualitative and visual as
        well as quantitative data conceptualization.

     8. Distribution: Material placed on the web often gets a lot of access from
        surprising places.

     9. Evaluation: (See appended essay by F. Reif.) In my course, using some
        computer-assisted grading, three people grade roughly 100 exams (half
        essay, half multiple choice) in one afternoon.

What can the social and behavioral sciences recommend that will enable faculty
to meet the challenges posed by a student body that is increasingly diverse with
respect to level of academic preparation and cultural background?

                           Long-term stable effort

Many of these issues are addressed above. A central remaining issue is how more
effective practices can become available to a wider group of faculty.

The central issue, I believe, is that most faculty have a "broadcast" model of
pedagogy. That is, a professor who knows the subject matter, lectures clearly
provides good assignments, grades well, etc. - this professor teaches well, and
the rest is up to the student. Shifting to a model of analyzing the learning
task, and asking how to facilitate that learning in a particular course - this
is a difficult shift of view. Once the shift is made, then there is a large body
of knowledge about learning mechanisms and how teaching can make use of them.
This needs to be mastered, at least in a form relevant to the professor's own
teaching. We believe that this process takes at least one semester of dedicated
effort, and therefore provide the one-semester "sabbaticals" at the Center for
Innovation in Learning.

What are the obstacles to determining, implementing, and evaluating "best
practices"?

                                 Evaluation 

I have appended an essay by Frederick Reif discussing possibilities for
evaluating instruction in physics. There has been far more work in physics
education than in the behavioral sciences (and far more financial support of
such work). Thus the behavioral sciences may or may not be ready for such an
approach. However, an effort such as Reif describes could aid in better defining
reasonable learning goals, a crucial step towards improving instruction.

                              Collegial support

(Quoted from an abstract for a talk by Herbert A Simon) One striking contrast
between our research lives and our teaching lives are that research is a highly
social activity, teaching most often a solo performance. Research is carried on
with colleagues, local, national and international; It's products are widely
published; it is constantly judged by peers - and sometimes rewarded. Typically
there is little intellectual interchange with colleagues about teaching, and few
of our thoughts about it or its products are communicated.

Thesis: To give teaching the same intellectual excitement as our research (if it
doesn't have it already), and equal claims on our attention, we must convert it
into a collegial activity like research.

                                 New talent

Other than the new and small effort at Carnegie Mellon, and a slightly larger
effort (aimed at technology) at Georgia Institute of Technology, there are (to
my knowledge) no locations for training new talent in instructional research,
application, and innovation at the undergraduate level. NSF could have a big
influence by providing relatively long-term training grants to establish or
support centers that could train the new young talent desperately needed if we
are to address any of the issues discussed above.


Jill Larkin has joint appointments in the Psychology Department and in the
Center for Innovative Learning at Carnegie Mellon University, where she also has
a courtesy appointment in the Computer Science Department.  Her research has
demonstrated strategic differences in problem solving between physics students
and expert physicists, and has elucidated how diagrams and displays function in
supporting effective reasoning.  These observations have been part of the
research base used to develop an introductory physics course that raised
students' scores on comparable final exams from averages in the 60's to averages
in the 80's.  For six years Professor Larkin directed the McDonnell Foundation's
Program in Cognitive Studies for Educational Practice.  During this time a
number of cognitive scientists, using results from cognitive science, produced
new learning results in a variety of pre- college classrooms.


Appendix
To be published as a "guest comment" in the American Journal of Physics.


                   Standards and Measurements in Physics:
                        Why not in Physics Education?


                               Frederick Reif

        Center for Innovation in Learning and Department of Physics
                         Carnegie-Mellon University
                          Pittsburgh, Pennsylvania


Standards and measurements have played a centrally important role in the
development of physics. They have yielded reliable data based on accurate and
reproducible observations. They have facilitated meaningful sharing of results
among different scientists. They have allowed unambiguous checks of theoretical
ideas and have thus led to cumulative improvements of valuable knowledge. For
these reasons physicists have, throughout history, expended considerable efforts
on refining their standards and measurement methods.

The situation has been quite different in physics education, although the needs
are no less. There, a lack of reliable standards and measurements has made it
difficult to assess the efficacy of different instructional approaches. Although
it is easy to proclaim the virtues of various innovative curricula or teaching
methods, how do we really know in what respects one teaching method is more
effective than another? Or how do we know whether a teaching method, seemingly
effective in helping students acquire some abilities, does not fail in helping
them acquire other abilities that are even more essential?

Can we expect to achieve much progress in physics education (both in
understanding of the basic issues and in practical efficacy) if we lack at least
reasonably reliable common measurement standards? Could we not perhaps develop
and use better standards? The following comments explore these questions in the
hope of stimulating more serious consideration of them.

Formulating basic standards

Scientists, concerned with accurate measurements, who sometimes officially meet
to arrive at a consensus reflecting their best judgments, establish standards in
physics. Standards in physics education would similarly need to be formulated by
a careful process leading to a consensus among knowledgeable workers in the
field.

Better standards might perhaps most usefully be developed for the introductory
college-level physics course for physical science or engineering students. Not
only is this an important course faced by many instructors and students.
Physicists would probably also find it easier to agree about the aims of this
course than about courses intended for biology majors or non- scientists.

The first need would be to agree about what the standards should specify. The
aim of any instruction is designed to endow students with new capabilities
enabling them to cope better with later courses, jobs, or other tasks in their
lives. Mere specification of a syllabus, listing the topics to be "covered" in a
course, does not indicate what students actually learn. Accordingly, educational
standards need to be performance standards specifying what students should
actually be able to do after completing a course. 

One should, at least, be able to agree on some minimal performance standards. 
e.g., on a half dozen or so kinds of basic capabilities expected of all students
emerging from a one-semester course. One might perhaps hope that students learn
more than that. But any course in which students fail to acquire these basic 
capabilities could then be clearly judged a failure.

The mere discussion of basic standards would force physicists to examine more
closely their teaching goals and to specify the actual capabilities expected of
their students. I am sure that there would be heated debate reflecting diverse
points of view and previously unexamined assumptions. But the debate would be
very healthy in confronting issues that are often not explicitly addressed. For
example, should students rely on various memorized formulas or be able to reason
from a few basic principles? Should they be able to solve problems
mathematically or should they also be able to do qualitative reasoning? Should
they mostly engage in numerical manipulations or also be able to obtain
algebraic results that they can examine for their qualitative implications?
Should they just be able to obtain answers or also be able to articulate
well-based scientific explanations?

Operational specification of standards

Operationally meaningful standards need to be accompanied by procedures
specifying how they can be determined by actual measurements. Some detailed work
would, therefore, need to be done to design questions or tasks exemplifying the
basic capabilities specified by these standards. There would also need to be
agreement that a student's ability to answer such a question, or to perform such
a task, would provide good evidence that he or she possesses the specified
capability.

The Hestenes tests(See endnote 1) provide good examples of questions designed to
assess one basic kind of capability desired of students in an introductory 
physics course. However, other basic capabilities important in such a course 
would also need to be specified (e.g., the ability to apply Newton's laws to 
solve simple mechanics problems).

Utility for assessments. Suppose that consensus had been reached on a few basic
performance standards in a course and that each were accompanied by a set of N
questions designed to assess achievement of the specified performance. These N
questions (where N might be about 30) should be approximately equivalent and
could have been empirically tested to ensure that they are of comparable
difficulty.

One could then construct an assessment instrument (e.g., a final examination) by
selecting at random one question for each of the specified kinds of performance.
No one, including the instructor teaching the course would know beforehand,
which of these questions would be selected. Hence one would eliminate the
dangers of bias, e.g., of deliberate or inadvertent teaching directed at
particular questions on the test. (If the number N of possible questions is
large enough, trying to teach students to answer all of them would pretty much
ensure that students have attained the desired competence.)

Persons interested in assessing instructional effectiveness would then have
available measuring instruments allowing them to determine more reliably in what
ways a teaching method used one year is more effective than another one used
previously - or more effective than another method used by others willing to use
the same measurement methods(See endnote 2).

Purely individual efforts might help to achieve some of these aims, but would
suffer from some insurmountable limitations. In particular, there would then be
no assurance that measurements made by one individual would be deemed legitimate
or significant by others. Even more important, there would be no meaningful ways
to compare the efficacy of instructional interventions devised by different
people. Good standards and measurements in the domain of physics education, as
well as in physics, necessarily require the collaborative efforts of the
community of workers in the field.

Practical realizability

The preceding proposals are not beyond the bounds of realistic feasibility,
especially if the following points are kept in mind: 1) These proposals aim to
improve the present situation in physics education, but do not pretend to
achieve perfect standards. However, even modest improvements could be quite
valuable; 2) Standards are not to be cast in stone, but can be periodically
reexamined and modified. (Even in physics standards get periodically refined or
even redefined.); and 3) There is no compulsion forcing anybody to abide by any
formulated standards. However, such standards could be used to good advantage by
people interested in more reliable assessments of instructional effectiveness.
Furthermore, the very existence of these standards could beneficially influence
teaching practices.

Well-specified performance criteria in any field help to avoid fruitless debates
and wasted efforts. When the goals are clear, it becomes much easier to decide
the merits of alternative approaches and to ensure cumulative progress. It will
probably always be more difficult to specify standards and measurements in
physics education than in physics, but it seems possible to do significantly
better than is currently the case.

--------------------------------------------------------------------------------
(1) Halloun, I.A. and D.Hestenes, 1985. The initial knowledge state of college
students. American Journal of Physics. 53:1043-1055. Hestenes, D. and M.Wells,
1992. "A mechanics baseline test." The Physics Teacher. 30:159-166. Hestenes,
D., Wells, M. and G.Swackhamer, 1992. "Force concept inventory," The Physics 
Teacher. 30:141-158.

(2) Some statistical sampling issues would need to be addressed in these 
measurement procedures, but they would be less severe than those prevalent at
present.
--------------------------------------------------------------------------------

        Contributions of Cognitive Science to Undergraduate Education


                               Nora S. Newcombe

                           Department of Psychology
                              Temple University
                          Philadelphia, Pennsylvania


Cognitive science is an interdisciplinary endeavor involving cognitive and
cognitive - developmental psychology, computer science, and the neurosciences.
The aim of cognitive science is to understand the workings of the mind/brain. 
Hence, its insights are basic to the development of an understanding of human
mastery of mathematical and scientific material and habits of thought.  An
emerging subdiscipline within cognitive science aims explicitly to develop
knowledge relevant to learning and instruction. (For a readable and eloquent
summary of this movement, see John Bruer's 1993 Schools for Thought). This
emerging sub- discipline can be seen as reinventing, or at least reshaping,
traditional educational psychology.

Educationally oriented cognitive scientists have worked on several problems
whose solution is necessary to effective teaching of mathematics and science. In
this short paper, to give participants in the Social Sciences Workshop a sense
of the potential for cognitive scientists to contribute to the improvement of
undergraduate education, I discuss two problems which cross cut various
mathematical and scientific fields, and two developments with specific relevance
to the teaching of certain fields (physics and geometry). Thus, this paper is
mainly addressed to answering the first question posed to the Workshop ("What
are the implications of cognitive research for an understanding of how students
learn?"), although I also touch on issues of promoting flexibility and life-long
learning (question 6), issues of diversity (question 5) and what is needed in
terms of a research agenda (question 8).

Transfer of learning from one context to another

One issue basic to effective education is devising conditions under which
students will show transfer, or generalization of learning.  That is, having
1earned a skill in one context (e.g., mathematical operations of compounding in
the context of calculating compound interest), we want people to be able to
apply this knowledge in a different context (e.g., velocity problems). Transfer
of skills and knowledge from domain to domain will likely be increasingly
important, as we move into an era in which workers will need to adapt flexibly
to changing technology and to different work situations.  Unfortunately, the
cognitive literature shows that people are frequently distressingly narrow and
rigid in their transfer, realizing the applicability of existing knowledge and
skills only when its relevance is explicitly pointed out to them.

At the same time, there are beginning to be demonstrations that this narrowness
and rigidity can be overcome. Teaching needs to be aimed at producing
decontextualization, while at the same time not itself being decontextualized. 
That is, people learn best when they study a problem in context, motivated by
interaction with physical materials and relevance to real- world problems.  But
they also need to encounter multiple instantiations of underlying principles,
each in context, but with the deeper similarities a focus of instruction.  For
example, students appear to learn compounding in a more generalizable fashion in
mathematics classes, in which they encounter a variety of problem types, than in
finance or in physics classes, in which the domain of application is narrower.
Teaching based on the principles of contextualized instruction with a range of
domains of application can help students learn general principles and
procedures, whose relevance to new situations they can see spontaneously.

This newly achieved understanding of the nature of the instruction, which is
necessary to result in transfer, and generalization presents a research
opportunity to NSF. Cognitive scientists can build on their understanding of
when transfer is and is not achieved to work in partnership with instructors of
specific mathematical and scientific disciplines to devise curricula which will
maximize deeper understanding (and hence transfer) of an identified number of
basic principles. Facilitating interdisciplinary research partnerships involving
the mathematical and scientific disciplines with cognitive sciences should be an
important priority for NSF.

Student diversity as related to patterns of cognitive ability and learning
styles As we all know, undergraduate student bodies are increasingly diverse in
cultural background, age, and level of academic preparation.  This fact is
sometimes interpreted as implying that instructional styles need to be
correspondingly diversified, to accommodate the different patterns of
intellectual strengths and weaknesses seen in different groups and to
accommodate what is conceptualized as different learning styles shown by
different groups. However, while appealing, research support for these
assumptions is largely lacking.

One subtopic in this general realm of discourse concerns visuospatial ability,
generally agreed to be one of the two most important components of general
intelligence, the other being verbal intelligence. Certain types of visuospatial
ability show fairly sizable sex differences. There are recurring attempts to
link this fact to sex differences in mathematical achievement and to recommend
that different instructional strategies be used with males and females because
of this difference. However, such recommendations are shortsighted. There is
compelling evidence that visuospatial ability is underdeveloped in both men and
women and extremely responsive to training and instruction (see review by
Baerminger and Newcombe, 1995). There is a need for research on the benefits of
linking interventions designed to maximize the spatial potential of
undergraduates to facilitating their mathematical and scientific learning.

Second, diversity is frequently conceptualized in terms of hypothesized
differences in learning styles across populations. However, the cognitive
literature is not encouraging of this conceptualization.  To be useful, learning
styles would need to be operationally definable, reliably assessed, show
long-term stability, and, most importantly, be related to instructional style so
that particular types of instruction could be paired with particular students.
The search for such aptitude-treatment interactions has been an active one, but
few have been found.

There is a possibly interesting exception to this rule, however, in recent work
by Robert Sternberg at Yale University. Sternberg has reported reliable and
valid assessment of analytic, creative and practical intelligence, coupled with
maximization of learning in an introductory psychology course when instructional
styles are matched to student learning styles. Following up on this finding in
teaching mathematical and scientific content represents another example of a
research opportunity for NSF in efforts to pair cognitive scientists with
instructors m mathematical and scientific subjects.

Changing student misconceptions about physics

Cognitive scientists have documented that students, even at the college level,
frequently have intuitive notions of physics which are fundamentally different
from physics the way physicists think of it. College students may predict that
balls shot out of curved tubes will follow curved paths of motion after release,
or think that a heavier object dropped from a tower will hit the ground before a
lighter one dropped at the same time from the same height. Such misconceptions
may appear discouraging to instructors. Or, instructors may simply attempt to
contradict these beliefs, lecturing on the "correct" way of thinking about these
problems. Unfortunately, traditional teaching techniques are frequently
ineffective. For instance, students are prone to predict a curved path for the
ball shot from a curved tube even after taking a college course covering
mechanics.

Curricula, which take misconceptions as a point of departure rather than a
roadblock, can be more successful. A program developed for a high school physics
course by Jim Minstrell, in collaboration with Earl Hunt, a cognitive scientist
at the University of Washington, is frequently cited as an example. The
Minstrell approach takes students' thinking about physical phenomena as a point
of departure, working to arrange experiences in which students realize how
different aspects (or facets) of their thinking are incompatible, and then work
to resolve these impasses. Teaching through impasse resolution is slow, but
effective. Impasse resolution approaches could easily serve as the basis for
college curricula as well. The research challenge for NSF is again to commission
interdisciplinary groups of cognitive scientists and mathematicians/scientists
to work together on curricular developments suggested by cognitive science.

A technology-based program of geometry instruction

Students frequently dislike geometry, and relatively few master the skill of
constructing geometric proofs. John Anderson, a cognitive scientist at
Carnegie-Mellon University, has devised an interactive computer program, which
can impressively increase high school students' ability to do proofs. The
approach taken in building the program is one that does not necessarily depend
on technology. Teachers also could learn to teach using the ideas, which the
program uses, such as those experts frequently approach proofs by trying both to
reason forward from the givens and backward from the desired conclusion. Again,
the research challenge is implementation.

Conclusion

This short paper was aimed to give workshop participants a sense of the
relevance of cognitive science to instruction by presenting four examples. Much
has been achieved, but basic research is far from over. For instance, there is
still considerable controversy about how one can maximize transfer in
problem-solving situations, and several competing models of the process exist
(see review by Reeves and Weisberg, 1994).

NSF could contribute to improving undergraduate instruction by supporting
cognitive science in two ways. First, funding is needed for basic research in
cognitive science on topics with educational relevance. While there are,
theoretically, existing funding mechanisms within NSF for such research, in
actuality the SBER programs such as Human Cognition and Perception frequently
look askance at educationally-oriented proposals and the EHR programs may find
cognitive-science proposals too theoretical and too far removed from the field.
Joint programs would be helpful, in which the announced goal is to fund
proposals in the intersection of the two research domains. Second, funding is
needed for the research/practice collaborations necessary to effective
implementation of the insights and achievements, which already exist. There are
many difficult steps between scientific understanding and widespread adoption of
specific curricula and practices. Detailed recommendations, along these same
lines, are elaborated in a report written on an NSF-sponsored conference on a
very similar topic, namely the contributions of cognitive science research to
K-12 mathematics and science education (Hawkins and Newcombe, 1994).

Nora S. Newcombe is Professor of Psychology at Temple University.  Her research
is on cognitive development, and concerns spatial processes and also early
memory.  At Temple, she is working with the Center for Excellence in Teacher
Preparation, a project to improve the ability of K-12 teachers to educate
children in science and mathematics.

References

Baenninger, M.A and Newcombe, N., 1995. Environmental input to the development
      of sex-related differences in spatial and mathematical ability. Learning
      and Individual Differences.  7: 363-379.

Bruer, J.T., 1993.  Schools for thought: A science of learning in the classroom.
      Cambridge, MA: MIT Press.

Hawkins, J. and Newcombe, N., 1994. Developing a new research agenda to
      facilitate innovation in the teaching and learning of science and 
      mathematics. Report to the National Science Foundation.

Reeves, L.M and Weisberg, R.W., 1994. The role of content and abstract
      information in analogical transfer. Psychological Bulletin, 115: 381-400.


               Cognitive Science and Undergraduate Education


                               Neil Stillings

                         Cognitive Science Program
                             Hampshire College
                                Amherst, MA


The primary purpose of this paper is to address questions 3 and 6 in the guide
to the workshop discussion from the perspective of the cognitive sciences. From
this perspective, question 3 asks how introductory undergraduate courses in the
cognitive sciences effectively promote scientific and quantitative literacy.
Question 6 asks how knowledge of the cognitive sciences prepares students to
meet the challenges of the 21st Century. I will also address the research and
development efforts (Questions 7 & 8) that are needed to realize the potential
of cognitive science as an area of undergraduate science instruction.

Undergraduate education in cognitive science

Cognitive science is the science of intelligence in humans, other animals, and
artificial systems. It includes the study of perception, learning, memory,
knowledge, meaning, reasoning, language, attention, affect, consciousness, and
the control of action. In undergraduate curricula, the field is offered both as
a new scientific discipline that emphasizes computational models of cognitive
processes and as an integrative interdisciplinary field that draws together
insights from several traditional disciplines, including psychology, biology,
computer science, linguistics, philosophy, and anthropology. In the context of
the present workshop, it should be pointed out that cognitive science highlights
the somewhat arbitrary nature of traditional distinctions between physical,
biological, and social sciences. Cognitive science has significant social,
behavioral, biological, and even physical (e.g., psychophysical studies of
sensory systems) dimensions. Stillings (1995) is a recent report on the current
status of undergraduate education in cognitive science. Stillings et al. (l995)
is a survey of the field.

Scientific literacy and the social sciences

Before answering Question 3 for the cognitive sciences, the larger context of
the question should be considered. We should not assume that the typical
undergraduate science distribution requirement could effectively promote
scientific literacy, if only the mix of physical, biological, and social
sciences were optimal. Undergraduates may not be taking enough science, and the
science that they take may not be taught effectively. Empirical research, of the
kind described by other participants in this discussion, is required to assess
the effectiveness of and to improve college-level science instruction.

We should also not assume that instruction in the physical and biological
sciences alone provides, or is even capable of providing, a superior or
sufficient path to scientific literacy. For the foreseeable future, many policy
issues that will concern a scientifically literate citizenry fall at least
partly in the domain of the social and behavioral sciences. Furthermore, as I
will suggest below, the social and behavioral sciences are equal, and in some
cases superior, to the physical and biological sciences as arenas for general
science education.

How courses in the cognitive sciences can promote scientific and quantitative
literacy

The contributions of courses in the cognitive sciences to science education fall
into five areas. First, cognitive science provides a scientific approach to a
distinctive set of questions that is of great interest to contemporary
undergraduates: What is the nature of meaning? What distinguishes perception
from knowledge objective? What is the relationship between mind and brain? What
is consciousness? Cognitive science's empirical approach to such questions can
bring science to a new group of undergraduates, and it can show them the
connections between science and areas of life and academic pursuit that can seem
distant from science. Cognitive science can also play a crucial role in helping
students to critically understand mind-brain-behavior relationships in an era of
rapidly expanding knowledge in neuroscience and behavior genetics, as well as in
cognitive science.

Second, cognitive science is a superb field for giving beginning and
intermediate undergraduate students hands-on experience with science.
Instrumentation costs, even for sophisticated original research, are generally
low, and many currently active research questions are accessible to
undergraduates. Often, a personal computer can serve as the student's
laboratory. A wide range of cognitive psychological experiments on perception,
memory, language, thinking, and motor control can be run and analyzed on
unmodified desktop computers. Students can both replicate experiments and work
with high-level software that allows them to design and run original
experiments. Artificial intelligence and cognitive simulation software that is
powerful, flexible enough to support original research, and usable by
undergraduates can also be run on personal computers (e.g., Anderson, 1993;
McClelland and Rumelhart, 1986).

Third, students can study reasoning, critical thinking and the scientific method
in a context where normative conceptions of rationality are compared with
empirical research on human thought. This naturalistic approach to epistemology
allows the student to see the motivation for normative conceptions and to learn
to recognize situations in which biases and heuristics in everyday thinking lead
to sub-optimal conclusions. Recent research suggests that it is possible to
train people to apply abstract rules of reasoning more successfully in varying
real situations (Nisbett, l993), and this research is finding its way into
curricular materials on critical thinking (e.g., Halpern, 1995a, 1995b). A more
naturalistic epistemology can also provide a realistic appreciation of the
special strengths of scientific reasoning to students who have lost, or perhaps
never possessed, an uncritical faith in science (Giere, 1988; Thagard, 1988).

Fourth, cognitive science is an excellent field for attracting students into an
encounter with formal mathematical intellectual disciplines. Within the context
of attractive questions about the mind and brain, the student can encounter such
disciplines as experimental design and statistics, probability and decision
theory, formal logic, the theory of algorithms, and the theory of dynamical
systems. Students who become fascinated with artificial neural networks as
freshmen, for example, discover that they must take calculus and linear algebra
to pursue their interest further.

Finally, cognitive science is being applied in important areas of public policy
and technology. Cognitive scientists are pursuing issues in human-computer
interaction, workplace organization, reading remediation, mathematics education,
cognition and aging, and the reliability of traumatic memories, among many
others. Increasingly, some familiarity with cognitive science will be a
condition for informed citizenship.

Not all courses in the cognitive sciences have all of the characteristics
mentioned.  The range of courses that possess at least some of them is fairly
broad, including courses in cognitive science, courses in constituent
disciplines of cognitive science such as psychology or psycholinguistics,
courses in overlapping disciplines such as psychology or neuroscience, or
special interdisciplinary topics courses such as critical thinking.

Considerable faculty development and research on and development of
instructional approaches and materials are also needed to fully realize the
potential just sketched.

How knowledge of the cognitive sciences helps prepare students to meet the
challenges of the 21st Century

The characteristics of the cognitive sciences discussed above are equally
relevant here. The cognitive sciences can engage students in science. They are a
context for learning critical thinking and formal quantitative and scientific
methods. They are critical to the understanding of many emerging public policy
issues.

Students who major or minor in cognitive science tend to have a broad
intellectual base and strong analytical and writing skills. Many of them, of
course, go on to graduate work in the cognitive sciences, computer science,
neuroscience, medicine, or education. There are also anecdotal reports from
faculty members involved in cognitive science programs that their students are
successful in the job market upon graduation. They have skills in computer
programming, research design, data analysis, and writing, and they have
knowledge of human cognition that is of value in the rapidly growing
information-intensive sectors of the economy.

Research and development in cognitive science instruction

The potential for undergraduate instruction in the cognitive sciences has not
been fully realized. The improvement of undergraduate programs in cognitive
science and their curricula for majors are addressed in Stillings (1995).

The potential of the cognitive sciences to contribute to scientific and
quantitative literacy in non-science majors would be enhanced by targeted
support for the development of new instructional approaches and materials. The
analysis above suggests three particularly promising areas for funding.

The first area is the development of critical thinking courses that blend the
cognitive psychology of reasoning and decision making with training in
normatively correct reasoning that is based on recent research in transfer of
training and skill decontextualization (see Nora Newcombe's contribution to this
workshop). Such courses might blend material in deduction, causal reasoning,
experimental design, probability theory (particularly reasoning with conditional
probability and Bayes's theorem), and topics in elementary statistical
inference, such as the law of large numbers and statistical regression.

The second area is the development of introductory courses that give students
significant hands-on experience with cognitive science research, either by
running original experiments or by performing original simulations.

The final area is the development of courses that explore public policy issues
that have significant cognitive science content. Such courses could be taught in
a way that focused on the learning of transferable critical thinking skills as
well as on a particular content area. Such courses also offer many avenues for
collaboration between the cognitive sciences and other disciplines. For example,
a cognitive scientist, an economist, and a philosopher could jointly develop a
course on cost-benefit and risk-benefit analysis.

Neil Stillings is Professor of Psychology in the Cognitive Science Program at
Hampshire College.  He is the editor and first author of Cognitive Science: An
Introduction, 2nd edition, MIT Press, 1995.  He has organized national workshops
on cognitive science education for the Sloan Foundation and the National Science
Foundation.


References
Anderson, J.R., 1993. Rules of the Mind. Hillsdale, NJ: Erlbaum.

Giere, R.N., 1988. Explaining Science: A Cognitive Approach. Chicago: University
      of Chicago Press.

Halpern, D.F., 1995a.  Thought and Knowledge: An Introduction to Critical
      Thinking, 3d Ed. Hillsdale, NJ: Erlbaum.

Halpern, D.F., 1995b. Thinking Critically About Critical Thinking. Hillsdale,
      NJ: Erlbaum.

McClelland, J.L. and D.E. Rumelhart, l989. Explorations in Parallel Distributed
      Processing: A Handbook of Models, Programs, and Exercises. Cambridge: MIT
      Press.

Nisbett, R.E., 1993.  Rules for Reasoning. Hillsdale, NJ: Erlbaum.

Stillings, N.A., 1995. Undergraduate education in cognitive science current
      status and future prospects. Final report of a planning workshop for the
      National Science Foundation. Washington, DC, May 21-23, 1993. Available on
      the Worldwide Web at http://hamp.hampshire.edu/~nasCCS/nsfreport.html.

Stillings, N.A., Weisler, S.E., Chase, C.H., Feinstein, M.H., Garfield, J.L. and
      E.L. Rissland, 1995.  Cognitive Science: An Introduction, 2nd Edition. 
      Cambridge, MA: MIT Press.

Thagard, P., 1988. Computational Philosophy of Science. Cambridge, MA: M1T 
      Press.

--------------------------------------------------------------------------------