Product dissection has been widely deployed in engineering education as a means to aid in student's understanding of functional product elements, development of new concept ideas, and their preparation for industry. However, there are large variations in the dissection activities employed in education with little research geared at understanding the impact of these variations on student cognitive load requirements and, ultimately, student conceptual understanding. This is problematic because without this knowledge, we do not know what components of product dissection impact (positively or negatively) conceptual understanding of the dissected product and how this is related to the cognitive requirements of the dissection activity. Therefore, the purpose of this study was to investigate how the type of product dissected (complexity and product power source), the virtuality of the product (physical or virtual), and the type of dissection activity performed impacted student conceptual understanding and cognitive requirements through a factorial experiment with 141 engineering students. While the type of cognitive load varied between virtually and physically dissecting products, no differences were found in subsequent levels of conceptual understanding. This indicates that virtual environments may be used as a proxy for physical environments without impacting the conceptual understanding of products by students. These results are used to develop recommendations for the use of product dissection in education and propel future research that investigates relationships between example-based design practices and student understanding outcomes.

References

References
1.
Bhatnagar
,
A.
,
2015
, “
Product Dissection: A Method for Hands on Engineering Education
,”
J. Eng. Educ. Transform.
,
28
(3), pp.
99
104
.
2.
Lamancusa
,
J. S.
,
Jorgensen
,
J. E.
, and
Zayas‐Castro
,
J. L.
,
1997
, “
The Learning Factory—A New Approach to Integrating Design and Manufacturing Into the Engineering Curriculum
,”
J. Eng. Educ.
,
86
(
2
), pp.
103
112
.
3.
Lamancusa
,
J. S.
,
Jorgensen
,
J. E.
, and
Fridley
,
J. L.
,
1996
, “
Product Dissection—A Tool for Benchmarking in the Process of Teaching Design
,”
Frontiers in Education Conference
(
FIE
), Salt Lake City, UT, Nov. 6–9, pp.
1317
1321
.
4.
Grantham
,
K.
,
Okudan
,
G. L.
,
Simpson
,
T. W.
, and
Ashour
,
O.
,
2010
, “A Study on Situated Cognition: Product Dissection's Effect on Redesign Activities,”
ASME
Paper No. DETC2010-28334.
5.
Toh
,
C.
, and
Miller
,
S. R.
,
2013
, “Product Dissection or Visual Inspection? The Impact of Designer-Product Interactions on Engineering Design Creativity,”
ASME
Paper No. DETC2013-13087.
6.
Otto
,
K. N.
, and
Wood
,
K. L.
,
1998
, “
Product Evolution: A Reverse Engineering and Redesign Methodology
,”
Res. Eng. Des.
,
10
(
4
), pp.
226
243
.
7.
Lefever
,
D.
, and
Wood
,
K.
,
1996
, “Design for Assembly Techniques in Reverse Engineering and Redesign,” ASME Design Theory and Methodology Conference, pp. 1–28.
8.
Sheppard
,
S. D.
,
1992
, “
Mechanical Dissection: An Experience in How Things Work
,”
Engineering Education: Curriculum Innovation & Integration
, Santa Barbara, CA, Jan. 6–10, pp.
1
8
.http://www-adl.stanford.edu/images/dissphil.pdf
9.
Hande
,
A. H.
,
He
,
W.
,
Bakarat
,
N.
, and
Carrol
,
M.
,
2005
, “
Product Dissection: An Important Tool for a First Year Introduction to Engineering Course Project
,”
ASEE North Central Conference
, Ada, OH, Apr., pp. 1–12.http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.122.3651&rep=rep1&type=pdf
10.
Borrego
,
M.
,
Froyd
,
J. E.
, and
Hall
,
T. S.
,
2010
, “
Diffusion of Engineering Education Innovations: A Survey of Awareness and Adoption Rates in U.S. Engineering Departments
,”
J. Eng. Educ.
,
99
(
3
), pp.
185
207
.
11.
Devendorf
,
M.
,
Lewis
,
K.
,
Simpson
,
T. W.
,
Stone
,
T. W.
,
Stone
,
R. B.
, and
Regil
,
W. C.
,
2010
, “
Evaluating the Use of Digital Product Repositories to Enhance Product Dissection Activities in the Classroom
,”
ASME J. Mech. Des.
,
9
(4), p. 041008.
12.
Devendorf
,
M.
,
Lewis
,
K.
,
Simpson
,
T. W.
,
Stone
,
R. B.
, and
Regli
,
W. C.
,
2007
, “Evaluating the Use of Cyberinfrastructure in the Classroom to Enhance Product Dissection,”
ASME
Paper No. DETC2007-35549.
13.
Toh
,
C.
,
Miller
,
S.
, and
Simpson
,
T.
,
2015
, “
The Impact of Virtual Product Dissection Environments on Student Design Learning and Self-Efficacy
,”
J. Eng. Des.
,
26
(
1–3
), pp.
48
73
.
14.
McKenna
,
A. F.
,
Chen
,
W.
, and
Simpson
,
T.
,
2008
, “Exploring the Impact of Virtual and Physical Dissection Activities on Students' Understanding of Engineering Design Principles,”
ASME
Paper No. DETC2008-49783.
15.
Chou
,
S. W.
, and
Liu
,
C. H.
,
2005
, “
Learning Effectiveness in a Web‐Based Virtual Learning Environment: A Learner Control Perspective
,”
J. Comput. Assisted Learn.
,
21
(
1
), pp.
65
76
.
16.
Toh
,
C.
, and
Miller
,
S. R.
,
2013
, “Exploring the Utility of Product Dissection for Early-Phase Idea Generation,”
ASME
Paper No. DETC2013-13096.
17.
Zacharia
,
Z. C.
,
Olympiou
,
G.
, and
Papaevripidou
,
M.
,
2008
, “
Effects of Experimenting With Physical and Virtual Manipulatives on Students' Conceptual Understanding in Heat and Temperature
,”
J. Res. Sci. Teach.
,
45
(
9
), pp.
1021
1035
.
18.
Feinberg
,
S.
, and
Murphy
,
M.
,
2000
, “
Applying Cognitive Load Theory to the Design of Web-Based Instruction
,”
Professional Communication Society International Professional Communication Conference and 18th Annual ACM International Conference on Computer Documentation: Technology & Teamwork
(
IPCC/SIGDOC 2000
), Cambridge, MA, Sept. 24–27, pp.
353
360
.
19.
Van Merriënboer
,
J. J.
,
Kester
,
L.
, and
Paas
,
F.
,
2006
, “
Teaching Complex Rather Than Simple Tasks: Balancing Intrinsic and Germane Load to Enhance Transfer of Learning
,”
Appl. Cognit. Psychol.
,
20
(
3
), pp.
343
352
.
20.
Warter-Perez
,
N.
, and
Dong
,
J.
,
2012
, “
Flipping the Classroom: How to Embed Inquiry and Design Projects Into a Digital Engineering Lecture
,”
ASEE PSW Section Conference
, pp.
1
17
.
21.
Jamieson
,
L. H.
, and
Lohmann
,
J. R.
,
2012
, “Innovation With Impact: Creating a Culture for Scholarly and Systematic Innovation in Engineering Education,” ASEE, Washington, DC,
Report
.http://www.abet.org/wp-content/uploads/2015/04/innovation-wth-impact-executive-summary.pdf
22.
Froyd
,
J. E.
,
Wankat
,
P. C.
, and
Smith
,
K. A.
,
2012
, “
Five Major Shifts in 100 Years of Engineering Education
,”
Proc. IEEE
,
100
(
Special Centennial Issue
), pp.
1344
1360
.
23.
Telenko
,
C.
,
Wood
,
K.
,
Otto
,
K.
,
Elara
,
M. R.
,
Foong
,
S.
,
Pey
,
K. L.
,
Tan
,
U.-X.
,
Camburn
,
B.
,
Moreno
,
D.
, and
Frey
,
D.
,
2016
, “
Designettes: An Approach to Multidisciplinary Engineering Design Education
,”
ASME J. Mech. Des.
,
138
(
2
), p.
022001
.
24.
Abdulwahed
,
M.
, and
Nagy
,
Z. K.
,
2009
, “
Applying Kolb's Experiential Learning Cycle for Laboratory Education
,”
J. Eng. Educ.
,
98
(
3
), pp.
283
294
.
25.
Trevelyan
,
J.
,
2007
, “
Technical Coordination in Engineering Practice
,”
J. Eng. Educ.
,
96
(
3
), pp.
191
204
.
26.
Prince
,
M. J.
, and
Felder
,
R. M.
,
2006
, “
Inductive Teaching and Learning Methods: Definitions, Comparisons, and Research Bases
,”
J. Eng. Educ.
,
95
(
2
), pp.
123
138
.
27.
Clyne
,
A. M.
, and
Billiar
,
K. L.
,
2016
, “
Problem-Based Learning in Biomechanics: Advantages, Challenges, and Implementation Strategies
,”
ASME J. Biomech. Eng.
,
138
(
7
), p.
070804
.
28.
Anderson
,
L. W.
,
Krathwohl
,
D. R.
,
Airasain
,
P. W.
,
Cruikshank
,
K. A.
,
Mayer
,
R. E.
,
Pintrich
,
P. R.
,
Raths
,
J.
, and
Wittrock
,
M. C.
,
2001
,
A Taxonomy for Learning, Teaching, and Assessing: A Revision of Bloom's Taxonomy of Educational Objectives
, Longman, White Plains, NY.
29.
Bloom
,
B. S.
,
1956
,
Taxonomy of Educational Objectives: The Classification of Education Goals
, Longman, White Plains, NY.
30.
Bransford
,
J. D.
,
Brown
,
A. L.
, and
Cocking
,
R. R.
,
1999
,
How People Learn: Brain, Mind, Experience, and School
,
National Academy Press
, Washington, DC.
31.
Lamancusa
,
J. S.
,
Torres
,
M.
,
Kumar
,
V.
, and
Jorgensen
,
J.
,
1996
, “
Learning Engineering by Product Dissection
,”
ASEE Annual Conference
, Washington, DC, June 23–26, pp.
1
13
.https://peer.asee.org/learning-engineering-by-product-dissection.pdf
32.
Brereton
,
M.
,
Sheppard
,
S.
, and
Leifer
,
L.
,
1995
, “
How Students Connect Engineering Fundamentals to Hardware Design: Observations and Implications for the Design of Curriculum and Assessment Methods
,”
Tenth International Conference on Engineering Design Prague
(
ICED
), Prague, Czech Republic, Aug. 22–24, pp.
336
342
.http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.32.3157
33.
Krishen
,
A.
,
2008
, “
Perceived Versus Actual Complexity for Websites: Their Relationship to Consumer Satisfaction
,”
J. Consum. Satisfaction, Dissatisfaction Complaining Behav.
,
21
, pp. 104–123.https://faculty.unlv.edu/anjala/Krishen_JCS_2008.pdf
34.
Zacharia
,
Z. C.
, and
Olympiou
,
G.
,
2011
, “
Physical Versus Virtual Manipulative Experimentation in Physics Learning
,”
Learn. Instr.
,
21
(
3
), pp.
317
331
.
35.
Chen
,
S.
,
Chang
,
W. H.
,
Lai
,
C. H.
, and
Tsai
,
C. Y.
,
2014
, “
A Comparison of Students' Approaches to Inquiry, Conceptual Learning, and Attitudes in Simulation‐Based and Microcomputer‐Based Laboratories
,”
Sci. Educ.
,
98
(
5
), pp.
905
935
.
36.
Zacharia
,
Z. C.
,
2007
, “
Comparing and Combining Real and Virtual Experimentation: An Effort to Enhance Students' Conceptual Understanding of Electric Circuits
,”
J. Comput. Assisted Learn.
,
23
(
2
), pp.
120
132
.
37.
Chittaro
,
L.
, and
Ranon
,
R.
,
2007
, “
Web3D Technologies in Learning, Education and Training: Motivations, Issues, Opportunities
,”
Comput. Educ.
,
49
(
1
), pp.
3
18
.
38.
Kirschner
,
P. A.
,
Sweller
,
J.
, and
Clark
,
R. E.
,
2006
, “
Why Minimal Guidance During Instruction Does Not Work: An Analysis of the Failure of Constructivist, Discovery, Problem-Based, Experiential, and Inquiry-Based Teaching
,”
Educ. Psychol.
,
41
(
2
), pp.
75
86
.
39.
Sweller
,
J.
,
1994
, “
Cognitive Load Theory, Learning Difficulty, and Instructional Design
,”
Learn. Instr.
,
4
(
4
), pp.
295
312
.
40.
Atkinson
,
R. C.
, and
Shiffrin
,
R. M.
,
1968
, “
Human Memory: A Proposed System and Its Control Processes
,”
Psychol. Learn. Motiv.
,
2
, pp.
89
195
.
41.
Miller
,
G. A.
,
1956
, “
The Magical Number Seven, Plus or Minus Two: Some Limits on Our Capacity for Processing Information
,”
Psychol. Rev.
,
63
(
2
), pp.
81
97
.
42.
Peterson
,
L.
, and
Peterson
,
M. J.
,
1959
, “
Short-Term Retention of Individual Verbal Items
,”
J. Exp. Psychol.
,
58
(
3
), pp.
193
198
.
43.
Chan
,
M. S.
, and
Black
,
J. B.
,
2006
, “
Direct-Manipulation Animation: Incorporating the Haptic Channel in the Learning Process to Support Middle School Students in Science Learning and Mental Model Acquisition
,”
Seventh International Conference on Learning Sciences
, Bloomington, Indiana, June 27–July 1, pp.
64
70
.https://dl.acm.org/citation.cfm?id=1150044&dl=ACM&coll=DL
44.
Tsang
,
P. S.
, and
Velazquez
,
V. L.
,
1996
, “
Diagnosticity and Multidimensional Subjective Workload Ratings
,”
Ergonomics
,
39
(
3
), pp.
358
381
.
45.
Mayer
,
R. E.
,
2005
, “
Principles for Reducing Extraneous Processing in Multimedia Learning: Coherence, Signaling, Redundancy, Spatial Conguity, and Tempora Contiguity Principles
,”
The Cambridge Handbook of Multimedia Learning
,
Cambridge University Press
,
Cambridge, UK
, pp.
183
200
.
46.
Schweppe
,
J.
, and
Rummer
,
R.
,
2014
, “
Attention, Working Memory, and Long-Term Memory in Multimedia Learning: An Integrated Perspective Based on Process Models of Working Memory
,”
Educ. Psychol. Rev.
,
26
(
2
), pp.
285
306
.
47.
Mayer
,
R. E.
, and
Chandler
,
P.
,
2001
, “
When Learning is Just a Click Away: Does Simple User Interaction Foster Deeper Understanding of Multimedia Messages?
,”
J. Educ. Psychol.
,
93
(
2
), pp.
390
397
.
48.
Tabbers
,
H. K.
,
Martens
,
R. L.
, and
Merriënboer
,
J. J.
,
2004
, “
Multimedia Instructions and Cognitive Load Theory: Effects of Modality and Cueing
,”
Br. J. Educ. Psychol.
,
74
(
1
), pp.
71
81
.
49.
Höffler
,
T. N.
, and
Leutner
,
D.
,
2007
, “
Instructional Animation Versus Static Pictures: A Meta-Analysis
,”
Learn. Instr.
,
17
(
6
), pp.
722
738
.
50.
Sweller
,
J.
,
1988
, “
Cognitive Load During Problem Solving: Effects on Learning
,”
Cognit. Sci.
,
12
(
2
), pp.
257
285
.
51.
Ume
,
C.
, and
Timmerman
,
M.
,
1995
, “
Mechatronics Instruction in the Mechanical Engineering Curriculum at Georgia Tech
,”
Mechatronics
,
5
(
7
), pp.
723
741
.
52.
Giurgiutiu
,
V.
,
Lyons
,
J.
,
Rocheleau
,
D.
, and
Liu
,
W.
,
2005
, “
Mechatronics/Microcontroller Education for Mechanical Engineering Students at the University of South Carolina
,”
Mechatronics
,
15
(
9
), pp.
1025
1036
.
53.
Kalyuga, S.
,
Ayres
,
P.
,
Chandler
,
P.
, and
Sweller
,
J.
,
2003
, “
The Expertise Reversal Effect
,”
Educ. Psychol.
,
38
(1), pp.
23
31
.
54.
Starkey
,
E. M.
,
McKay
,
A. S.
,
Hunter
,
S. T.
, and
Miller
,
S. R.
,
2016
, “
Dissecting Creativity: How Dissection Virtuality, Analogical Distance, and Product Complexity Impact Creativity and Self-Efficacy
,”
Design Computing and Cognition
(
DCC
), Evanston, IL, June 27–29, pp. 59–77.
55.
Doyle
,
T. E.
,
Baetz
,
B. W.
, and
Lopes
,
B.
,
2011
, “
First-Year Engineering Bicycle Dissection as an Introduction to Sustainable Design
,”
Canadian Engineering Education Association
, St. John's, NF, Canada, pp.
1
5
.
56.
Novak
,
S.
, and
Eppinger
,
S. D.
,
2001
, “
Sourcing by Design: Product Complexity and the Supply Chain
,”
Manage. Sci.
,
47
(
1
), pp.
189
204
.
57.
Donderi
,
D. C.
,
2006
, “
Visual Complexity: A Review
,”
Psychol. Bull.
,
132
(
1
), pp.
73
97
.
58.
Rubio
,
S.
,
Díaz
,
E.
,
Martín
,
J.
, and
Puente
,
J. M.
,
2004
, “
Evaluation of Subjective Mental Workload: A Comparison of SWAT, NASA‐TLX, and Workload Profile Methods
,”
Appl. Psychol.
,
53
(
1
), pp.
61
86
.
You do not currently have access to this content.