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Age, technology usage, and cognitive characteristics in relation to perceived disorientation and reported website ease of use

Published: 20 October 2014 Publication History

Abstract

Comparative studies including older and younger adults are becoming more common in HCI, generally used to compare how these two different age groups will approach a task. However, it is unclear whether user "age" is the underlying factor that differentiates between these two groups. To address this problem, an examination into the relationship between users' age, previous technology experience, and cognitive characteristics is conducted. Measures of perceived disorientation and reported ease of use are used to understand links that exist between these user characteristics and their effect on browsing experience. This is achieved through a lab-based information retrieval task, where participants visited a selection of websites in order to find answers to a series of questions and then self reported their feelings of perceived disorientation and website ease of use through a Likert-scored questionnaire.
The presented research found that age accounts for as little as 1% of user browsing experience when performing information retrieval tasks. Further, it showed that cognitive ability and previous technology experience significantly affected perceived disorientation in these searches. These results argue for the inclusion of metrics regarding cognitive ability and previous technology experience when analyzing user satisfaction and performance in Internet based-studies.

References

[1]
Ahuja, J. S., & Webster, J. (2001). Perceived disorientation: an examination of a new measure to assess web design effectiveness. Interacting with computers, 14(1), 15--29.
[2]
Cattell, R.B. 1982. Meaningful Memory. Institute for Personality and Ability Testing.
[3]
Chin, J., & Fu, W. T. (2010, April). Interactive effects of age and interface differences on search strategies and performance. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 403--412). ACM.
[4]
Chin, J., Fu, W. T., & Kannampallil, T. (2009, April). Adaptive information search: age-dependent interactions between cognitive profiles and strategies. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 1683--1692). ACM.
[5]
Czaja, S. J., & Lee, C. C. (2007). The impact of aging on access to technology. Universal Access in the Information Society, 5(4), 341--349.
[6]
Czaja, S. J., & Sharit, J. (1993). Age differences in the performance of computer-based work. Psychology and aging, 8(1), 59.
[7]
Czaja, S. J., Charness, N., Fisk, A. D., Hertzog, C., Nair, S. N., Rogers, W. A., & Sharit, J. (2006). Factors predicting the use of technology: findings from the Center for Research and Education on Aging and Technology Enhancement (CREATE). Psychology and aging, 21(2), 333.
[8]
Czaja, S. J., Sharit, J., Lee, C. C., Nair, S. N., Hern�ndez, M. A., Arana, N., & Fu, S. H. (2013). Factors influencing use of an e-health website in a community sample of older adults. Journal of the American Medical Informatics Association, 20(2), 277--284.
[9]
Czaja, S. J., Sharit, J., Ownby, R., Roth, D. L., & Nair, S. (2001). Examining age differences in performance of a complex information search and retrieval task. Psychology and aging, 16(4), 564.
[10]
Dommes, A., Chevalier, A., & Lia, S. (2011). The role of cognitive flexibility and vocabulary abilities of younger and older users in searching for information on the web. Applied Cognitive Psychology, 25(5), 717--726.
[11]
Ekstrom, R.B., French, J.W., Harman, H.H. and Dermen, D. 1976. Manual for kit of factor-referenced cognitive tests. Princeton, NJ: Educational Testing Service. (1976).
[12]
Etcheverry, I., Terrier, P., & Marqui�, J. C. (2012). Are older adults less efficient in making attributions about the origin of memories for web interaction?. Revue Europ�enne de Psychologie Appliqu�e/European Review of Applied Psychology, 62(2), 93--102.
[13]
Fairweather, P. G. (2008, October). How older and younger adults differ in their approach to problem solving on a complex website. In Proceedings of the 10th international ACM SIGACCESS conference on Computers and accessibility(pp. 67--72). ACM.
[14]
Gelman, A. (2008). Scaling regression inputs by dividing by two standard deviations. Statistics in medicine, 27(15), 2865--2873.
[15]
Gregor, P., Newell, A. F., & Zajicek, M. (2002, July). Designing for dynamic diversity: interfaces for older people. In Proceedings of the fifth international ACM conference on Assistive technologies (pp. 151--156). ACM.
[16]
Hanson, V. L. (2009, April). Age and web access: the next generation. InProceedings of the 2009 International Cross-Disciplinary Conference on Web Accessibililty (W4A) (pp. 7--15). ACM.
[17]
Hart, T. A., Chaparro, B. S., & Halcomb, C. G. (2008). Evaluating websites for older adults: adherence to "senior friendly" guidelines and end-user performance. Behaviour & Information Technology, 27(3), 191--199.
[18]
Herder, E., & Juvina, I. (2004). Discovery of individual user navigation styles.
[19]
Hodes, R. J., & Lindberg, D. A. (2002). Making your website senior friendly.National Institute on Aging and the National Library of Medicine.
[20]
Horn, J. L., & Cattell, R. B. (1967). Age differences in fluid and crystallized intelligence. Acta psychologica, 26, 107--129.
[21]
Horn, J. L., & Cattell, R. B. (1966). Refinement and test of the theory of fluid and crystallized general intelligences. Journal of educational psychology, 57(5), 253.
[22]
Juvina, I., & Van Oostendorp, H. (2006). Individual differences and behavioral metrics involved in modeling web navigation. Universal Access in the Information Society, 4(3), 258--269.
[23]
Kurniawan, S., & Zaphiris, P. (2005, October). Research-derived web design guidelines for older people. In Proceedings of the 7th international ACM SIGACCESS conference on Computers and accessibility (pp. 129--135). ACM.
[24]
Laberge, J. C., & Scialfa, C. T. (2005). Predictors of Web navigation performance in a life span sample of adults. Human Factors: The Journal of the Human Factors and Ergonomics Society, 47(2), 289--302.
[25]
McDonald, S., & Stevenson, R. J. (1998). Effects of text structure and prior knowledge of the learner on navigation in hypertext. Human Factors: The Journal of the Human Factors and Ergonomics Society, 40(1), 18--27.
[26]
O'brien, M. A., Rogers, W. A., & Fisk, A. D. (2012). Understanding age and technology experience differences in use of prior knowledge for everyday technology interactions. ACM Transactions on Accessible Computing (TACCESS), 4(2), 9.
[27]
Ofcom 2013. Adults' media use and attitudes report.
[28]
Sandelancls, L. E., & Buckner, G. C. (1989). Of art and work: Aesthetic experience and the psychology of work feelings. Research in organizational behavior, 100, l05--l3l.
[29]
Sharit, J., Hern�ndez, M. A., Czaja, S. J., & Pirolli, P. (2008). Investigating the roles of knowledge and cognitive abilities in older adult information seeking on the web. ACM Transactions on Computer-Human Interaction (TOCHI), 15(1), 3.
[30]
Sharit, J., Hernandez, M. A., Nair, S. N., Kuhn, T., & Czaja, S. J. (2011). Health problem solving by older persons using a complex government web site: Analysis and implications for web design. ACM Transactions on Accessible Computing (TACCESS), 3(3), 11.
[31]
Trewin, S., Richards, J. T., Hanson, V. L., Sloan, D., John, B. E., Swart, C., & Thomas, J. C. (2012, October). Understanding the role of age and fluid intelligence in information search. In Proceedings of the 14th international ACM SIGACCESS conference on Computers and accessibility (pp. 119--126). ACM.
[32]
Schaik, P. V., & Ling, J. (2012). An experimental analysis of experiential and cognitive variables in web navigation. Human-Computer Interaction, 27(3), 199--234.
[33]
Webster, J., & Ahuja, J. S. (2006). Enhancing the design of web navigation systems: the influence of user disorientation on engagement and performance. MIS Quarterly, 661--678.
[34]
Westerman, S. J., Davies, D. R., Glendon, A. I., Stammers, R. B., & Matthews, G. (1995). Age and cognitive ability as predictors of computerized information retrieval. Behaviour & Information Technology, 14(5), 313--326.

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      cover image ACM Conferences
      ASSETS '14: Proceedings of the 16th international ACM SIGACCESS conference on Computers & accessibility
      October 2014
      378 pages
      ISBN:9781450327206
      DOI:10.1145/2661334
      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: 20 October 2014

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      Author Tags

      1. cognitive psychology
      2. hci
      3. older adults
      4. search strategies
      5. web search

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      ASSETS '14 Paper Acceptance Rate 29 of 106 submissions, 27%;
      Overall Acceptance Rate 436 of 1,556 submissions, 28%

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      • (2020)Influence of Age on the Usability Assessment of the Instagram Application17th International Conference on Information Technology–New Generations (ITNG 2020)10.1007/978-3-030-43020-7_56(423-428)Online publication date: 12-May-2020
      • (2020)An Evolving Perspective to Capture Individual Differences Related to Fluid and Crystallized Abilities in Information Searching with a Search EngineUnderstanding and Improving Information Search10.1007/978-3-030-38825-6_5(71-96)Online publication date: 30-May-2020
      • (2019)User-friendly search interface for older adults: supporting search goal refreshing in working memory to improve information search strategiesBehaviour & Information Technology10.1080/0144929X.2019.164238439:10(1094-1109)Online publication date: 26-Jul-2019
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      • (2017)How do older and young adults start searching for information? Impact of age, domain knowledge and problem complexity on the different steps of information searchingComputers in Human Behavior10.1016/j.chb.2017.02.03872:C(67-78)Online publication date: 1-Jul-2017
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      • (2016)An Analysis of Age, Technology Usage, and Cognitive Characteristics Within Information Retrieval TasksACM Transactions on Accessible Computing10.1145/28560468:3(1-26)Online publication date: 6-Apr-2016
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