334 CATALYZING INQUIRY
has noted that “biologists are biologists because they love living things. A computation is not alive.”^4
Indeed, this has been true for several generations of students, so that many of these same students are
now incumbent instructors of biology. Managing this particular problem will pose many challenges.
10.2.2.2 Undergraduate Programs
The primary rationale for undergraduate programs at the BioComp interface is that the under-
graduate years of university education in the sciences carry the greatest burden in teaching a student
the professional language of a science and the intellectual paradigms underlying the practice of that
science. The term “paradigm” is used here in the original sense first expounded by Kuhn, which
includes the following:^5
- Symbolic generalizations, which the community uses without question,
- Beliefs in particular models, which help to determine what will be accepted as an explanation or
a solution, - Values concerning prediction (e.g., predictions must be accurate, quantitative) and theories (e.g.,
theories must be simple, self-consistent, plausible, compatible with other theories in current use), and - Exemplars, which are the concrete problem solutions that students encounter from the start of
their scientific education.
The description in Section 10.3.1 suggests that the disciplinary paradigm of biology is significantly
different from that of computer science. Because the de novo learning of one paradigm is easier than
subsequently learning a second paradigm that may (apparently) be contradictory or incommensurate
with one that has already been internalized, the argument for undergraduate exposure is based on the
premise that simultaneous exposure to the paradigms of two disciplines will be more effective than
sequential exposure (as would be the case for someone receiving an undergraduate degree in one field
and then pursuing graduate work in another).
Undergraduate programs in most scientific courses of study are generally designed to prepare
students for future academic work in the field. Thus, the goal of undergraduate curricula at the BioComp
interface is to expose students to a wide range of biological knowledge and issues and to the intellectual
tools and constructs of computing such as programming, statistics, algorithm design, and databases.
Today, most such programs focus on bioinformatics or computational biology, and in the most typical
cases, the integration of biology and computing occurs later rather than earlier in these programs (e.g.,
as senior-year capstone courses).
Individual programs vary enormously in the number of computer science classes required. For
example, the George Washington University Department of Computer Science offers a concentration in
bioinformatics leading to a B.S. degree; the curriculum includes 17 computer science courses and 4
biology courses, plus a single course on bioinformatics. The University of California, Los Angeles
(UCLA) program in cybernetics offers a concentration in bioinformatics, in contrast, in which the stu-
dents can take as few as seven computer science courses, including four programming classes and two
biology-themed classes. In other cases, a university may have an explicit undergraduate major in
bioinformatics associated with a bioinformatics department. Such programs are traditionally structured
in the sense of having a set of specific courses required for matriculation.
In addition to concentrations at the interface, a number of other approaches have been used to
prepare undergraduates:
- An explicitly interdisciplinary B.S. science program can expose students to the interrelationships
of the basic sciences. Sometimes these are co-taught as single units: students in their first year may take
(^4) W.D. Hillis, “Why Physicists Like Models, and Biologists Should,” Current Biology 3(2):79-81, 1993.
(^5) T.S. Kuhn, The Structure of Scientific Revolutions, Third Edition, University of Chicago Press, Chicago, 1996.