skip to main content
10.1145/1941007.1941022acmotherconferencesArticle/Chapter ViewAbstractPublication PagesihmConference Proceedingsconference-collections
research-article

What, where and how are young people looking for in a search engine results page?: impact of typographical cues and prior domain knowledge

Published:20 September 2010Publication History

ABSTRACT

In this paper, we describe an experiment that uses the eye-tracking technique to help us understand how young people (recruited from Grade 5 to Grade 11) explore a search engine results page (SERP) to find information. In particular, we looked at how varying the typographical cuing in Web search results (With boldface versus No boldface) and the familiarity of the search topic (Familiar versus Unfamiliar) affected user visual strategies. Results have mainly showed that (1) typographical cuing and prior domain knowledge influence the visual exploration of a SERP, that (2) four different visual strategies can be identified for young people (F-shaped strategy, Exhaustive strategy, Cued visual jumps, and F-inverse strategy), and that (3) the distribution of these strategies depends on the grade level and on the degree of familiarity of the search topic (i.e., the level of prior domain knowledge).

References

  1. Aula, A., Majaranta, P., and Räihä, K. J. Eye-tracking Reveals the Personal Styles for Search Result Evaluation. Proceedings of INTERACT 2005, LNCS 3585, September 16, 2005, pp. 1058--106. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Buscher, G., Cutrell, E., & Morris, M. R. What Do You See When You're Surfing? Using Eye Tracking to Predict Salient Regions of Web Pages. CHI'2009, April 4--9, Boston, Massachusetts, USA. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Cutrell, E., and Guan, Z. An eye-tracking study of information usage in Web search: Variations in target position and contextual snippet length. Tech report for Microsoft Research, MSR-TR-2007-01.Google ScholarGoogle Scholar
  4. Cutrell, E., and Guan, Z. What are you looking for? An eye-tracking study of information usage in Web Search. In Proceedings of CHI'07, Human Factors in Computing Systems, (San Jose, April 2007), 2007, ACM press, 407--416. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Dansdan, A., Tsioutsiouliklis, K., and Velipasaoglu, E. Web search engine metrics for measuring user satisfaction. 2009. On-line, retrieved from http://dasdan.net/ali/www2009/web-search-metrics-tutorial-www09-part6a.pdf.Google ScholarGoogle Scholar
  6. Dinet, J., Rouet, J.-F., and Passerault, J.-M. Document search and ICT: Are "new tools" compatible with students cognitive strategies? In Proceedings of Hypermédias et Apprentissages (Strasbourg, June 1999), 1999, 149--162.Google ScholarGoogle Scholar
  7. Dinet, J., and Rouet, J.-F. La recherche d'information: processus cognitifs, facteurs de difficultés et dimension de l'expertise. In C. Paganelli (Ed.), Interaction homme - machine et recherche d'information (pp. 133--161). Paris: Hermès, 2002.Google ScholarGoogle Scholar
  8. Dmitiroff, A., and Wolfram, D. Search response in a hyper-based bibliographic information retrieval system. Journal of the American Society for Information Science, Vol. 46(1), 1995, pp. 22--29. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Fidel, R., Davies, R., Douglass, M., Holder, J., Hopkins, C., Kushner, E., Miyagishima, B., and Toney, C. A visit to the information mall: Web searching behavior of high-school students. Journal of the American Society for Information Science, Vol. 50(1), 2004, pp. 24--37. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Gerjets, P., Kammener, Y., and Werner, B. Measuring spontaneous and instructed evaluation processes during Web search: Integrating concurrent thinking-aloud protocols and eye-tracking data. Learning and Instruction, in press., 2010, 1--12.Google ScholarGoogle Scholar
  11. Hembrooke, H. A., Granka, L. A., and Gay, G. K. The effects of expertise and feedback on search term selection and subsequent learning. Journal of the American Society for Information Science and Technology, Vol. 56(8), 2005, pp. 861--871. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Hirsh, S. G. Complexity of search tasks and children's information retrieval. Proceedings of the 59th American Society for Information Science Annual Meeting, Vol. 33, 1996, pp. 47--51.Google ScholarGoogle Scholar
  13. Hirsh, S. G. Children's relevance criteria and information seeking on electronic resources. Journal of the American Society for Information Science, Vol. 50, 2000, pp. 1265--1283. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Jansen, B. J., and Pooch, U. A review of web searching studies and a framework for future research. Journal of the American Society of Information Science and Technology, Vol. 52, 2000, pp. 235--246. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Kiestra, M. D., Stokmans, M. J. W., and Kamphuis, J. End-users searching the online catalogue: The influence of domain and system knowledge on search patterns. The Lectronic Library, Vol. 12(6), 1994, pp. 335--343.Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Knight, S. A., & Spink, A. Toward a Web Search Information Behavior Model. Information Science and Knowledge Management, Vol. 14, 2008, pp. 209--234.Google ScholarGoogle ScholarCross RefCross Ref
  17. Marchionini, G. Information seeking in electronic encyclopedias. Machine-Mediated Learning, Vol. 3, 1991, pp. 211--226. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Marchionini, G. Interfaces for end-user information seeking. Journal of the American Society for Information Science, Vol. 43, 1992, pp. 156--163.Google ScholarGoogle ScholarCross RefCross Ref
  19. Marchionini, G. Information seeking in electronic environments. Cambridge, MA: Cambridge University Press, 1995. Google ScholarGoogle ScholarCross RefCross Ref
  20. Marchionini, G. Information -- interaction research and development. Library and Information Science Research, Vol. 30, 2008, pp. 165--174.Google ScholarGoogle ScholarCross RefCross Ref
  21. Nielsen, J., and Pernice, K. Eyetracking Web usability. New Riders, London, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Park, Y., and Black, J. B. Identifying the impact of domain knowledge and cognitive style on web-based information search behavior. Journal of Educational Computing Research, Vol. 38(1), 2007, pp. 15--37.Google ScholarGoogle ScholarCross RefCross Ref
  23. Tu, Y.-W., Shih, M., and Tsai, C.-C. Eighth graders' web searching strategies and outcomes: The role of task types, web experiences and epistemological beliefs. Computers and Education, Vol. 51, 2008, pp. 1142--1153. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Vakkari, P. Subject knowledge, source of terms, and term selection in query expansion: An analytical study. Paper presented at the Advances in Information Retrieval: 24th BCS-IRSG European Colloquium on IR Research, Glasgow, UK, 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Willoughby, T., Anderson, S. A., Wood, C, E., Mueller, J., and Ross, C. Fast searching for information on the Internet to use in a Learning context: The impact of domain knowledge. Computers & Education, Vol. 52, 2009, 640--648. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. What, where and how are young people looking for in a search engine results page?: impact of typographical cues and prior domain knowledge

    Recommendations

    Comments

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Sign in
    • Published in

      cover image ACM Other conferences
      IHM '10: Proceedings of the 22nd Conference on l'Interaction Homme-Machine
      September 2010
      262 pages
      ISBN:9781450304108
      DOI:10.1145/1941007

      Copyright © 2010 ACM

      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]

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 20 September 2010

      Permissions

      Request permissions about this article.

      Request Permissions

      Check for updates

      Qualifiers

      • research-article

      Acceptance Rates

      Overall Acceptance Rate103of199submissions,52%

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader