Research Papers: Design Education

Piecing Together Product Dissection: How Dissection Conditions Impact Student Conceptual Understanding and Cognitive Load

[+] Author and Article Information
Elizabeth M. Starkey

Department of Industrial and
Manufacturing Engineering,
The Pennsylvania State University,
310 Leonhard Building,
University Park, PA 16802
e-mail: ems413@psu.edu

Alexander S. McKay

Industrial and Organizational Psychology,
The Pennsylvania State University,
140 Moore Building,
University Park, PA 16802
e-mail: asm273@psu.edu

Samuel T. Hunter

Industrial and Organizational Psychology,
The Pennsylvania State University,
140 Moore Building,
University Park, PA 16802
e-mail: sthll@psu.edu

Scarlett R. Miller

School of Engineering Design,
Technology and Professional Programs,
Department of Industrial and
Manufacturing Engineering,
The Pennsylvania State University,
213 Hammond Building,
University Park, PA 16802
e-mail: shm13@psu.edu

Contributed by the Design Education Committee of ASME for publication in the JOURNAL OF MECHANICAL DESIGN. Manuscript received April 11, 2017; final manuscript received February 8, 2018; published online March 23, 2018. Assoc. Editor: Katja Holtta-Otto.

J. Mech. Des 140(5), 052001 (Mar 23, 2018) (11 pages) Paper No: MD-17-1261; doi: 10.1115/1.4039384 History: Received April 11, 2017; Revised February 08, 2018

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.

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Grahic Jump Location
Fig. 1

A sample functional layout diagram of the mixer (complex, electric power source) with 11 out 23 unique parts. Written words were replaced with text for legibility.

Grahic Jump Location
Fig. 2

A sample SLA post-test of the mixer (complex, electric power source) for question of how mechanical motion is achieved receiving full points for sketch and written description

Grahic Jump Location
Fig. 3

Handout given to participants to record their cognitive load during product dissection




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