Incorporating computer programming exercises into introductory physics is a delicate task that involves a number of choices that may have an effect on student learning. We present a “hybrid” approach that speaks to a number of common concerns regarding cognitive load which arise when using programming exercises in introductory physics classes where many students are absolute beginner programmers. This “hybrid” approach provides the student with a highly interactive web-based visualization, not unlike a PhET or Physlet interactive, but importantly the student is shown only the subset of the code where the initial conditions are set and the system variables are evolved. We highlight results from a coding activity that resembles the classic game Asteroids. The goals of this activity are to show how a simple 1D code can be modified into a 2D code, and to reinforce ideas about the relationship between force, velocity, and acceleration vectors. Survey results from four semesters of introductory physics classes at the Ohio State University's Marion campus, in which a high percentage of the students are weak or absolute beginner programmers, provide evidence that most students can complete coding tasks without severe difficulty. Other survey results are promising for future work where conceptual learning will be assessed in a direct way using metrics like the Animated Force Concept Inventory [Dancy and Beichner, Phys. Rev. Spec. Top. Phys. Educ. 2, 010104 (2006)]. The exercise highlighted here and others from our group are available for general use at http://compadre.org/PICUP.

1.
R. G.
Fuller
, “Numerical computations in US undergraduate physics courses,”
Comput. Sci. Eng.
8
,
16
21
(
2006
).
2.
U. B. of Labor Statistics
, Online Publication (
2014
), URL <https://www.bls.gov/careeroutlook/2014/spring/art01.pdf>.
3.
Code.org
, “
Promote computer science
,” <https://code.org/promote>, accessed July 6, 2017.
4.
D. F.
Smith
, “
What the essa means for the future of computer science in stem
,” <http://www.edtechmagazine.com/k12/article/2015/12/what-essa-means-future-computer-science-and-stem>, accessed December 30, 2016.
5.
R.
Chabay
and
B.
Sherwood
, “Computational physics in the introductory calculus-based course,”
Am. J. Phys.
76
,
307
313
(
2008
).
6.
M. D.
Caballero
,
M. A.
Kohlmyer
, and
M. F.
Schatz
, “Implementing and assessing computational modeling in introductory mechanics,”
Phys. Rev. Spec. Top. Phys. Educ.
8
,
020106
020117
(
2012
).
7.
J. M.
Aiken
,
M. D.
Caballero
,
S. S.
Douglas
,
J. B.
Burk
,
E. M.
Scanlon
,
B. D.
Thoms
, and
M. F.
Schatz
, “Understanding student computational thinking with computational modeling,” in
American Institute of Physics Conference Series
, edited by
P. V.
Engelhardt
,
A. D.
Churukian
, and
N. S.
Rebello
(
2013
),
vol. 1513
, pp.
46
49
, 1207.1764.
8.
K.
Aho
,
K.
Chandra
, and
E.
Roberts
, “Introducing programming into the physics curriculum at Haverhill High School using the R Language,”
Proc. Am. Soc. Eng. Educ.
(
2014
), available at https://www.asee.org/documents/zones/zone1/2014/Student/PDFs/201.pdf.
9.
C. E.
Wieman
,
W. K.
Adams
,
P.
Loeblein
, and
K. K.
Perkins
, “Teaching physics using PhET simulations,”
Phys. Teach.
48
,
225
227
(
2010
).
10.
W.
Christian
and
M.
Belloni
,
Physlet Physics: Interactive Illustrations, Explorations, and Problems for Introductory Physics
(
Addison-Wesley
,
Boston, MA
,
2003
).
11.
K.
Perkins
,
W.
Adams
,
M.
Dubson
,
N.
Finkelstein
,
S.
Reid
,
C.
Wieman
, and
R.
LeMaster
, “PhET: Interactive simulations for teaching and learning physic,”
Phys. Teach.
44
,
18
23
(
2006
).
12.
N. S.
Podolefsky
,
K. K.
Perkins
, and
W. K.
Adams
, “Factors promoting engaged exploration with computer simulations,”
Phys. Rev. ST Phys. Educ. Res.
6
,
020117
020128
(
2010
).
13.
T. D.
Jong
, “Cognitive Load Theory, educational research, and instructional design:some food for thought,”
Instruct. Sci.
38
,
105
134
(
2010
).
14.
R. E.
Mayer
and
R.
Moreno
, “Nine ways to reduce cognitive load in multimedia learning,”
Educ. Psychol.
38
,
43
52
(
2003
).
15.
M.
Kordaki
, “A drawing and multi-representational computer environment for beginners' learning of programming using C: Design and pilot formative evaluation,”
Comput. Educ.
54
,
69
87
(
2010
).
16.
S.
Tisue
and
U.
Wilensky
, “NetLogo: Design and implementation of a multi-agent modeling environment,” in
Proceedings of Agent 2004
(
2004
), p.
175
198
, available at https://digital.library.unt.edu/ark:/67531/metadc901709/m2/1/high_res_d/939907.pdf.
17.
F.
Esquembre
and
A.
Titus
, “
Exploring physics with video games
,” <http://www.opensourcephysics.org/items/detail.cfm?ID=13970>, accessed July 5, 2017.
18.
R.
Taub
,
M.
Armoni
,
E.
Bagno
, and
M. M.
Ben-Ari
, “The effect of computer science on physics learning in a computational science environment,”
Comput. Educ.
87
,
10
23
(
2015
).
19.
D.
Weintrop
,
E.
Beheshti
,
M.
Horn
,
K.
Orton
,
K.
Jona
,
L.
Trouille
, and
U.
Wilensky
, “Defining computational thinking for mathematics and science classrooms,”
J. Sci. Educ. Technol.
25
,
127
147
(
2016
).
20.
R.
Chabay
and
B.
Sherwood
,
Matter & Interactions
, 4th ed. (
Wiley & Sons
,
Hoboken, NJ
,
2015
).
21.
R. M.
Serbanescu
,
P. J.
Kushner
, and
S.
Stanley
, “Putting computation on a par with experiments and theory in the undergraduate physics curriculum,”
Am. J. Phys.
79
,
919
924
(
2011
).
22.
O.
Marion
, “
Quick facts, the Ohio state university at marion
,” <http://osumarion.osu.edu/about/quick-facts.html> (2014), accessed January 1, 2014.
23.
O.
Marion
, “
Quick facts, the Ohio state university at marion
,” <http://osumarion.osu.edu/about/quick-facts.html> (2015), accessed January 1, 2015.
24.
O.
Marion
, “
Quick facts, the Ohio state university at marion
,” <http://osumarion.osu.edu/about/quick-facts.html> (2016), accessed January 1, 2016.
25.
O.
Columbus
, “
2017 enrollment report
,” <http://enrollmentservices.osu.edu/report.pdf> (2017), accessed October 10, 2017.
26.
A.
Cromer
, “Stable solutions using the Euler approximation,”
Am. J. Phys.
49
,
455
459
(
1981
).
27.
B. Y.
White
, “Designing computer games to help physics students understand Newton's Laws of Motion,”
Cogn. Instruct.
1
,
69
108
(
1984
).
28.
V.
Sawtelle
,
E.
Brewe
, and
L. H.
Kramer
, “Exploring the relationship between self-efficacy and retention in introductory physics,”
J. Res. Sci. Teach.
49
,
1096
1121
(
2012
).
29.
M. H.
Dancy
and
R.
Beichner
, “Impact of animation on assessment of conceptual understanding in physics,”
Phys. Rev. Spec. Top. Phys. Educ.
2
,
010104
010111
(
2006
).
30.
D.
Hestenes
,
M.
Wells
, and
G.
Swackhamer
, “Force concept inventory,”
Phys. Teach.
30
,
141
158
(
1992
).
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