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           | Department of Sociology           |
| Collegiate Division               |                                   |
|                                   | University of Notre Dame          |
| The University of Chicago         |                                   |
|                                   | Notre Dame, IN 46556-5644         |
| Harper Box 76                     |                                   |
|                                   |                                   |
| 1116 East 59^th^ 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, 6^th^ Floor           |
|                                   |                                   |
| Ann Arbor, MI                     | Philadelphia, PA 19122            |
+-----------------------------------+-----------------------------------+
| **Ronald G. Ehrenberg**           | **Neil Stillings**                |
|                                   |                                   |
| Vice President for Academic       | School of Communication and       |
| Programs,\                        | Cognitive Science                 |
| Planning, and Budgeting           |                                   |
|                                   | Hampshire College                 |
| 433 Day Hall                      |                                   |
|                                   | Amherst, MA 01002                 |
| Cornell University                |                                   |
|                                   |                                   |
| 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:

> • What has social and behavioral science research contributed to our
> understanding of how students learn?

-   What are the obstacles to implementing change in curriculum and
    instruction in undergraduate education? How do we overcome them?

-   What are the unanswered questions about student learning that
    research needs to address?

-   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

-   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.

1.  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.

2.  A survey of all alumni who have been out 2,5,7,10,15,and 20 years
    1400/3600 responded (still coming in)

-   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

-   ten students have kept detailed diaries of their educational
    experience across three years.

    5\. A retrospective course examination

-   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:

-   Social science courses are currently attractive to students

-   the topics and issues are of immediate relevance to students

-   these courses may be accessible to a wide range of students because
    they normally do not rely on pre-requisite high school preparation

-   Social science courses may provide a cost-effective alternative

-   these courses normally have lower start-up equipment expenses and
    reclaiming costs for supplies

-   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

-   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.

    The social and behavioral sciences may offer curricular and
    pedagogical flexibility

-   this flexibility may allow the adaptations needed to meet the needs
    of non-science students

-   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

-   the topics of study may offer more obvious and direct connections to
    the use and misuse of scientific information and technology

-   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*[)]{.underline} 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

-   Textbooks (at least in psychology) usually have a historical
    organization, and do not integrate material so as to make it easier
    to learn.

-   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[^1]^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[^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.

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*[,]{.underline} 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, 2^nd^ 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.

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[^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.