Eye tracking data understanding for product representation studies

Brandeis H. Marshall, Shweta Sareen, John A. Springer, Tahira Reid

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

Within the mechanical engineering discipline, product representation studies have been used to inform engineers on the suitability of their product designs for prospective customers. However, these studies are mainly based in customers' oral responses leading engineers to modify the product design accordingly. In contrast, we consider the eye tracking data associated with customer judgments of 2D and 3D product representation studies. Eye tracking data contains unforeseen facts and patterns not captured through customers' oral responses. In this research, we conduct data analysis and present a set of features for analyzing similar eye tracking studies. These features include (1) question-based analysis, (2) question and category dependencies, (3) product and category dependencies, (4) gender impact and (5) experiment repeatability situations. In addition, a brief comparison of the 2D and 3D product representation experiments is described for each feature.

Original languageEnglish (US)
Title of host publicationRIIT 2014 - Proceedings of the 3rd Annual Conference on Research in Information Technology
PublisherAssociation for Computing Machinery
Pages3-8
Number of pages6
ISBN (Electronic)9781450327114
DOIs
StatePublished - Oct 13 2014
Event3rd Annual Conference on Research in Information Technology, RIIT 2014 - Atlanta, United States
Duration: Oct 15 2014Oct 18 2014

Publication series

NameRIIT 2014 - Proceedings of the 3rd Annual Conference on Research in Information Technology

Conference

Conference3rd Annual Conference on Research in Information Technology, RIIT 2014
Country/TerritoryUnited States
CityAtlanta
Period10/15/1410/18/14

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Information Systems

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