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Using galvanic skin response measures to identify areas of frustration for older web 2.0 users

Published: 26 April 2010 Publication History

Abstract

The World Wide Web (Web) is changing. The much vaunted Web 2.0 sees once static pages evolving into hybrid applications. Content that was once simple is now becoming increasingly complicated due to the many updating components located throughout the page. The information overload and visual complexity of such components is significant. This increased complexity can produce lower performance and higher levels of stress and frustration which negatively effect the user. In previous work we have shown how galvanic skin response (GSR) measurements, collected in tandem with eye-tracking data, can be used as a method for determining how stressed users become when interacting with content. The results of that study demonstrated that when used appropriately, the presence of Web 2.0 content can reduce GSR measurements and be of benefit to users. In this work, the previous study was repeated with twenty-three older Web users to establish if similar patterns of interaction could be established. The results reveal that while older participants made use of dynamic content, unlike previous participants, they were a non-homogenous group with a large variance in the GSR measurements. We assert that a cause of this is hesitancy and therefore developing techniques to reduce hesitancy will benefit older users when interacting with Web 2.0 content.

References

[1]
L. A. Granka, T. Joachims, and G. Gay. Eye-Tracking Analysis of User Behavior in WWW Search. In SIGIR '04: Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval, pages 478--479. ACM, 2004.
[2]
A. A. Hartley. The Handbook of Aging and Cognition, chapter 1: Attention, pages 3--53. Laurence Erlbaum Associates, 1992. ISBN: 0-8058-0713-6.
[3]
C. Jay, R. Stevens, M. Glencross, and A. Chalmers. How People Use Presentation To Search For A Link: Expanding The Understanding Of Accessibility On The Web. In W4A: Proceedings of the 2006 International Cross-Disciplinary Workshop on Web Accessibility (W4A), pages 113--120. ACM Press, 2006.
[4]
S. Kurniawan, A. King, D. Evans, and P. Blenkhorn. Personalising Web Page Presentation for Older People. Interacting with Computers, 18(3):457--477, 2006. Human Factors in Personalised Systems and Services.
[5]
D. Lunn and S. Harper. Understanding How Users Interact With Web 2.0 Content through GSR: A Comparison of Older and Younger User's GSR Measurements. SCWeb2 Technical Report 3, The University of Manchester, August 2009. http://hcw-eprints.cs.manchester.ac.uk/126/. Last Accessed 7th December 2009.
[6]
D. Lunn and S. Harper. Understanding How Users Interact With Web 2.0 Content through GSR: A Pilot Study Using Younger Participants. SCWeb2 Technical Report 2, The University of Manchester, August 2009. http://hcw-eprints.cs.manchester.ac.uk/109/. Last Accessed 7th December 2009.
[7]
J. D. McCarthy, M. A. Sasse, and J. Riegelsberger. Could I have the Menu Please? An Eyetracking Study of Design Conventions. In Proceedings of HCI2003, pages 401--414, Bath, UK, 2003.
[8]
D. Memmert. The Effects of Eye Movements, Age, and Expertise on Inattentional Blindness. Consciousness and Cognition, 15(3):620--627, 2006.
[9]
D. E. Millard and M. Ross. Web 2.0: Hypertext By Any Other Name? In HYPERTEXT '06: Proceedings of the Seventeenth Conference on Hypertext and Hypermedia, pages 27--30. ACM, 2006.
[10]
J. Montagu and E. Coles. Mechanism and Measurement of the Galvanic Skin Response. Psychological Bulletin, 65(5):261--279, May 1966.
[11]
C. Mooney, M. Scully, G. J. Jones, and A. F. Smeaton. Investigating biometric response for information retrieval applications. In Advances in Information Retrieval, volume 3936/2006 of Lecture Notes in Computer Science, pages 570--574. Springer Berlin / Heidelberg, 2006.
[12]
Y. Nagai, L. H. Goldstein, P. B. C. Fenwick, and M. R. Trimble. Clinical efficacy of galvanic skin response biofeedback training in reducing seizures in adult epilepsy: A preliminary randomized controlled study. Epilepsy & Behavior, 5(2):216--223, 2004.
[13]
M. Nakayama, K. Takahashi, and Y. Shimizu. The Act of Task Difficulty and Eye-Movement Frequency for the 'Oculo-Motor Indices'. In ETRA '02: Proceedings of the 2002 Symposium on Eye Tracking Research & Applications, pages 37--42. ACM, 2002.
[14]
B. Pan, H. A. Hembrooke, G. K. Gay, L. A. Granka, M. K. Feusner, and J. K. Newman. The Determinants of Web Page Viewing Behavior: An Eye-Tracking Study. In ETRA '04: Proceedings of the 2004 Symposium on Eye Tracking Research & Applications, pages 147--154. ACM, 2004.
[15]
C. H. Perala and B. S. Sterling. Galvanic Skin Response as a Measure of Soldier Stress. Final Report 7MB25R, U.S. Army Research Laboratory, Human Research & Engineering Directorate Aberdeen Proving Ground, MD 21005-5425, May 2007.
[16]
P. Pirolli, S. K. Card, and M. M. V. D. Wege. Visual Information Foraging in a Focus + Context Visualization. In CHI '01: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pages 506--513. ACM, 2001.
[17]
K. Rayner. Eye Movements in Reading and Information Processing: 20 Years of Research. Psychological Bulletin, 124(3):327--422, 1998.
[18]
M. Russell. Using Eye-Tracking Data to Understand First Impressions of a Website. Usability News, 7(1):1--14, February 2005.
[19]
M. Sàenz, G. T. Buracas, and G. M. Boynton. Global Feature-Based Attention for Motion and Color. Vision Research, 43(6):629--637, 2003.
[20]
A. Savitzky and M. J. E. Golay. Smoothing and Differentiation of Data by Simplified Least Squares Procedures. Analytical Chemistry, 36(8):1627--1639, July 1964.
[21]
M. Schiessl, S. Duda, A. Thölke, and R. Fischer. Eye tracking and its application in usability and media research. MMI-Interaktiv, 6:35--40, 2003.
[22]
P. D. Shenefelt. Complementary Psychotherapy in Dermatology: Hypnosis and Biofeedback. Clinics in Dermatology, 20(5):595--601, 2002.
[23]
D. A. Varakin and D. T. Levin. Change Blindness and Visual Memory: Visual Representations Get Rich and Act Poor. British Journal of Psychology, 97(1):51--77, February 2006.
[24]
R. D. Ward and P. H. Marsden. Affective Computing: Problems, Reactions and Intentions. Interacting with Computers, 16(4):707--713, 2004.
[25]
S. Wood, R. Cox, and P. Cheng. Attention Design: Eight Issues to Consider. Computers in Human Behavior, 22(4):588--602, 2006.

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cover image ACM Other conferences
W4A '10: Proceedings of the 2010 International Cross Disciplinary Conference on Web Accessibility (W4A)
April 2010
223 pages
ISBN:9781450300452
DOI:10.1145/1805986
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 26 April 2010

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Author Tags

  1. ageing
  2. eye tracking
  3. galvanic skin response
  4. web 2.0

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W4A '10 Paper Acceptance Rate 10 of 32 submissions, 31%;
Overall Acceptance Rate 171 of 371 submissions, 46%

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  • (2022)Information Overload!Research Anthology on Managing Crisis and Risk Communications10.4018/978-1-6684-7145-6.ch030(587-612)Online publication date: 1-Jul-2022
  • (2022)Reklam Çekicilikleri, Marka Hatırlanırlığı ve Uyarılma İlişkisinin Deri Tepkisi ile İncelenmesiExamining the Relationship Between Advertising Appeals, Brand Recall and Arousal by Skin ResponseAkdeniz Üniversitesi İletişim Fakültesi Dergisi10.31123/akil.1175066(178-193)Online publication date: 7-Dec-2022
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  • (2020)User Experience Evaluation: A Validation Study of a Tool-based Approach for Automatic Stress Detection Using Physiological SignalsInternational Journal of Human–Computer Interaction10.1080/10447318.2020.182520537:5(470-483)Online publication date: 4-Oct-2020
  • (2020)Stress Heatmaps: A Fuzzy-Based Approach that Uses Physiological SignalsDesign, User Experience, and Usability. Case Studies in Public and Personal Interactive Systems10.1007/978-3-030-49757-6_19(268-277)Online publication date: 19-Jul-2020
  • (2019)UDSP+Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers10.1145/3341162.3343831(125-128)Online publication date: 9-Sep-2019
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