As the frontiers of biology become increasingly interdisciplinary, the physics education community has engaged in ongoing efforts to make physics classes more relevant to life science majors. These efforts are complicated by the many apparent differences between these fields, including the types of systems that each studies, the behavior of those systems, the kinds of measurements that each makes, and the role of mathematics in each field. Nonetheless, physics and biology are both sciences that rely on observations and measurements to construct models of the natural world. In this article, we propose that efforts to bridge the teaching of these two disciplines must emphasize shared scientific practices, particularly scientific modeling. We define modeling using language common to both disciplines and highlight how an understanding of the modeling process can help reconcile apparent differences between the teaching of physics and biology. We elaborate on how models can be used for explanatory, predictive, and functional purposes and present common models from each discipline demonstrating key modeling principles. By framing interdisciplinary teaching in the context of modeling, we aim to bridge physics and biology teaching and to equip students with modeling competencies applicable in any scientific discipline.

1.
National Science Board
,
Science and Engineering Indicators 2012
(
National Science Foundation
,
Arlington, VA
,
2012
), <http://www.nsf.gov/statistics/seind12/>.
2.
National Research Council
,
Discipline-Based Education Research: Understanding and Improving Learning in Undergraduate Science and Engineering
(
The National Academies Press
,
Washington, DC
,
2012
), <http://www.nap.edu/catalog.php?record_id=13362>.
3.
National Research Council
,
Adapting to a Changing World—Challenges and Opportunities in Undergraduate Physics Education
(
The National Academies Press
,
Washington, DC
,
2013
), <http://www.nap.edu/catalog.php?record_id=18312/>.
4.
Vision and Change in Undergraduate Biology Education: A Call to Action
, edited by
Carol A.
Brewer
and
Diane
Smith
(
AAAS
,
Washington, DC
,
2011
), <http://visionandchange.org/finalreport/>.
5.
National Research Council
,
Bio2010: Transforming Undergraduate Education for Future Research Biologists
(
The National Academies Press
,
Washington, DC
,
2003
), <http://www.nap.edu/catalog.php?record_id=10497>.
6.
President's Council of Advisors on Science and Technology, Engage to Excel: Producing One Million Additional College Graduates with Degrees in Science, Technology, Engineering, and Mathematics (Executive Office of the President, Washington, DC, 2012), <http://www.whitehouse.gov/sites/default/files/microsites/ostp/pcast-engage-to-excel-final_2-25-12.pdf/>
7.
D. C.
Meredith
and
E. F.
Redish
, “
Reinventing physics for life-sciences majors
,”
Phys. Today
66
,
38
43
(
2013
).
8.
J. S.
Gouvea
,
V.
Sawtelle
,
B. D.
Geller
, and
C.
Turpen
, “
A framework for analyzing interdisciplinary tasks: Implications for student learning and curricular design
,”
CBE-Life Sci. Educ.
12
,
187
205
(
2013
).
9.
B.
O'Shea
,
L.
Terry
, and
W.
Benenson
, “
From F = ma to flying squirrels: Curricular change in an introductory physics course
,”
CBE-Life Sci. Educ.
12
,
230
238
(
2013
).
10.
K. V.
Thompson
,
J.
Chmielewski
,
M. S.
Gaines
,
C. A.
Hrycyna
, and
W. R.
LaCourse
, “
Competency-based reforms of the undergraduate biology curriculum: Integrating the physical and biological sciences
,”
CBE-Life Sci. Educ.
12
,
162
169
(
2013
).
11.
K.
Cummings
,
P. W.
Laws
,
E. F.
Redish
,
P. J.
Cooney
, and
E. F.
Taylor
,
Understanding Physics
(
Wiley
,
Hoboken, NJ
,
2004
).
12.
D. C.
Giancoli
,
Physics for Scientists and Engineers with Modern Physics
(
Pearson
,
Upper Saddle River, NJ
,
2008
).
13.
R. D.
Knight
,
Physics for Scientists and Engineers: A Strategic Approach
(
Pearson/Addison Wesley
,
Upper Saddle River, NJ
,
2004
).
14.
R. W.
Chabay
and
B. A.
Sherwood
,
Matter and Interactions
(
Wiley
,
Hoboken, NJ
,
2011
).
15.
R. A.
Serway
,
Physics for Scientists and Engineers
(
Cengage Learning
,
Stamford, CT
,
2012
).
16.
J. B.
Reece
,
L. A.
Urry
,
M. L.
Cain
,
S. A.
Wasserman
,
P. V.
Minorsky
, and
R. B.
Jackson
,
Campbell Biology
(
Benjamin Cummings
,
San Francisco
,
2010
).
17.
R.
Brooker
,
E.
Widmaier
,
L.
Graham
, and
P.
Stiling
,
Biology
(
McGraw-Hill
,
New York
,
2013
).
18.
P.
Raven
,
G.
Johnson
,
K.
Mason
,
J.
Losos
, and
S.
Singer
,
Biology
(
McGraw-Hill
,
New York
,
2013
).
19.
National Research Council
,
A Framework for K-12 Science Education: Practices, Crosscutting Concepts, and Core Ideas
(
The National Academies Press
,
Washington, DC
,
2012
), <http://www.nap.edu/catalog.php?record_id=13165>.
20.
Achieve, Inc. on behalf of the 26 states and partners that collaborated on the NGSS, Next Generation Science Standards (
2013
), <http://www.nextgenscience.org/next-generation-science-standards>.
21.
M.
Wells
,
D.
Hestenes
, and
G.
Swackhamer
, “
A modeling method for high school physics instruction
,”,
Am. J. Phys.
63
,
606
619
(
1995
).
22.
E.
Etkina
and
A.
Van Heuvelen
, “
Investigative science learning environment: A science process approach to learning physics
,” in
Research-Based Reform of University Physics
, edited by
E. F.
Residh
and
P. J.
Cooney
(
American Association of Physics Teachers
,
College Park, MD
,
2007
), <http://www.per-central.org/document/ServeFile.cfm?ID=4988/>.
23.
A.-M.
Hoskinson
, “
How to build a course in mathematical-biological modeling: Content and processes for knowledge and skill
,”
CBE-Life Sci. Educ.
9
,
333
341
(
2010
).
24.
D.
Hestenes
, “
Toward a modeling theory of physics instruction
,”
Am. J. Phys.
55
,
440
454
(
1987
).
25.
I. A.
Halloun
,
Modeling Theory in Science Education, Vol. 24
(
Springer
,
New York
,
2004
).
26.
C. V.
Schwarz
 et al., “
Developing a learning progression for scientific modeling: Making scientific modeling accessible and meaningful for learners
,”
J. Res. Sci. Teach.
46
,
632
654
(
2009
).
27.
A. M.
Starfield
,
K.
Smith
, and
A. L.
Bleloch
,
How to Model It: Problem Solving for the Computer Age
(
McGraw-Hill
,
New York
,
1993
).
28.
J.
Odenbaugh
, “
Idealized, inaccurate but successful: A pragmatic approach to evaluating models in theoretical ecology
,”
Biol. Philos.
20
,
231
255
(
2005
).
29.
R.
Levins
, “
The strategy of model building in population biology
,”
Am. Sci.
54
,
421
431
(
1966
).
30.
J. T.
Dauer
,
J. L.
Momsen
,
E. B.
Speth
,
S. C.
Makohon-Moore
, and
T. M.
Long
, “
Analyzing change in students' gene-to-evolution models in college-level introductory biology
,”
J. Res. Sci. Teach.
50
,
639
659
(
2013
).
31.
S.
McKagan
,
K.
Perkins
, and
C.
Wieman
, “
Why we should teach the Bohr model and how to teach it effectively
,”
Phys. Rev. Special Top.—Phys. Educ. Res.
4
,
010103
1
(
2008
).
32.
C.-Y.
Tsui
and
D. F.
Treagust
, “
Genetics reasoning with multiple external representations
,”
Res. Sci. Educ.
33
,
111
135
(
2003
).
33.
J.
Rice
,
J.
Doherty
, and
C.
Anderson
, “
Principles, first and foremost: A tool for understanding biological processes
,”
J. College Sci. Teach.
43
,
74
82
(
2014
).
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