Evaluating the Impact of Idea Dissemination Methods on Information Loss

Zixuan Victoria Zhao, Christian E. Lopez, Conrad S. Tucker

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Information is transferred through a process consisting of an information source, a transmitter, a channel, a receiver, and its destination. Unfortunately, during the engineering design process, there is a risk of a design idea or solution being incorrectly transferred and interpreted due to the nonlinearity of the process, and many ways to communicate and disseminate ideas or solutions. The objective of this work is to explore the amount of relevant design information transmitted by different idea dissemination methods and how the receiver's familiarity with the idea impacts the effectiveness of the methods. First, this work explores the advantages and disadvantages of different dissemination methods in engineering design. Next, an experiment is conducted with engineering and nonengineering participants in order to quantify the information transmitted by different idea dissemination methods. This work also quantifies the effect that receivers' familiarity with a design artifact has on the amount of information transmitted by different dissemination methods. Finally, the results obtained from the experiments are compared with a previous theoretical model for validation. The results indicate that while certain methods are perceived as more informative and are able to convey more information than others (e.g., linguistic textual description versus virtual three-dimensional (3D) models), the effectiveness of the methods depends on a receiver's familiarity with the ideas being transmitted. Knowledge gained from this work can aid designers in selecting a suitable dissemination method needed to effectively communicate ideas and achieve a design solution.

Original languageEnglish (US)
Article number031006
JournalJournal of Computing and Information Science in Engineering
Volume19
Issue number3
DOIs
StatePublished - Sep 1 2019

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design
  • Industrial and Manufacturing Engineering

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