Eye tracking data understanding for product representation studies

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

doi:10.1145/2656434.2656439

Eye tracking data understanding for product representation studies

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

Mechanical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

5 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 language	English (US)
Title of host publication	RIIT 2014 - Proceedings of the 3rd Annual Conference on Research in Information Technology
Publisher	Association for Computing Machinery
Pages	3-8
Number of pages	6
ISBN (Electronic)	9781450327114
DOIs	https://doi.org/10.1145/2656434.2656439
State	Published - Oct 13 2014
Event	3rd Annual Conference on Research in Information Technology, RIIT 2014 - Atlanta, United States Duration: Oct 15 2014 → Oct 18 2014

Publication series

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

Conference

Conference	3rd Annual Conference on Research in Information Technology, RIIT 2014
Country/Territory	United States
City	Atlanta
Period	10/15/14 → 10/18/14

All Science Journal Classification (ASJC) codes

Computer Networks and Communications
Information Systems

Access to Document

10.1145/2656434.2656439

Cite this

Marshall, B. H., Sareen, S., Springer, J. A., & Reid, T. (2014). Eye tracking data understanding for product representation studies. In RIIT 2014 - Proceedings of the 3rd Annual Conference on Research in Information Technology (pp. 3-8). (RIIT 2014 - Proceedings of the 3rd Annual Conference on Research in Information Technology). Association for Computing Machinery. https://doi.org/10.1145/2656434.2656439

Marshall, Brandeis H. ; Sareen, Shweta ; Springer, John A. et al. / Eye tracking data understanding for product representation studies. RIIT 2014 - Proceedings of the 3rd Annual Conference on Research in Information Technology. Association for Computing Machinery, 2014. pp. 3-8 (RIIT 2014 - Proceedings of the 3rd Annual Conference on Research in Information Technology).

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title = "Eye tracking data understanding for product representation studies",

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.",

author = "Marshall, {Brandeis H.} and Shweta Sareen and Springer, {John A.} and Tahira Reid",

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publisher = "Association for Computing Machinery",

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note = "3rd Annual Conference on Research in Information Technology, RIIT 2014 ; Conference date: 15-10-2014 Through 18-10-2014",

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Marshall, BH, Sareen, S, Springer, JA & Reid, T 2014, Eye tracking data understanding for product representation studies. in RIIT 2014 - Proceedings of the 3rd Annual Conference on Research in Information Technology. RIIT 2014 - Proceedings of the 3rd Annual Conference on Research in Information Technology, Association for Computing Machinery, pp. 3-8, 3rd Annual Conference on Research in Information Technology, RIIT 2014, Atlanta, United States, 10/15/14. https://doi.org/10.1145/2656434.2656439

Eye tracking data understanding for product representation studies. / Marshall, Brandeis H.; Sareen, Shweta; Springer, John A. et al.
RIIT 2014 - Proceedings of the 3rd Annual Conference on Research in Information Technology. Association for Computing Machinery, 2014. p. 3-8 (RIIT 2014 - Proceedings of the 3rd Annual Conference on Research in Information Technology).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Marshall BH, Sareen S, Springer JA, Reid T. Eye tracking data understanding for product representation studies. In RIIT 2014 - Proceedings of the 3rd Annual Conference on Research in Information Technology. Association for Computing Machinery. 2014. p. 3-8. (RIIT 2014 - Proceedings of the 3rd Annual Conference on Research in Information Technology). doi: 10.1145/2656434.2656439

Eye tracking data understanding for product representation studies

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All Science Journal Classification (ASJC) codes

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