Advertisement

Think-Aloud Exploratory Search: Understanding Search Behaviors and Knowledge Flows

Conference paper
Part of the Springer Proceedings in Complexity book series (SPCOM)

Abstract

This paper describes an experiment that uses Concurrent Think-Aloud protocol (CTA) and person-to-person interviews to map searching behaviors and knowledge flows during search sessions. The findings are: (1) the most used searching strategy during exploratory searches was the “Metacognitive Domain”; and (2) online searching experts have a fair ability to deal with ideas prompted by browsing the search results. The main contributions of this research lie in the understanding of the process in which people find, access, decide what content is useful and apply online data to their different information needs.

Keywords

Information searching behavior Data discovery Innovation from data Innovation as data 

References

  1. 1.
    A. Aula, K. Nordhausen, Modeling successful performance in web searching. J. Am. Soc. Inform. Sci. Technol. 57(12), 1678–1693 (2006).  https://doi.org/10.1002/asi.20340CrossRefGoogle Scholar
  2. 2.
    N. Hariri, M. Asadi, Y. Mansourian, The impact of users’ verbal/imagery cognitive styles on their Web search behavior. Aslib J. Inf. Manage. 66, 401–423 (2014).  https://doi.org/10.1108/AJIM-02-2013-0019CrossRefGoogle Scholar
  3. 3.
    T. Kelley, B. Capobianco, K. Kaluf, Concurrent think-aloud protocols to assess elementary design students. Int. J. Technolo. Des. Educ 25(4), 521–540 (2015)CrossRefGoogle Scholar
  4. 4.
    C. Liu, J. Gwizdka, J. Liu, T. Xu, N.J. Belkin, Analysis and evaluation of query reformulations in different task types. Proc. Am. Soc. Inf. Sci. Technol. 47(1), 1–9 (2010).  https://doi.org/10.1002/meet.14504701214CrossRefGoogle Scholar
  5. 5.
    I. Madjid, C. Stéphane, M. Daniel, The effect of individual differences on searching the web. Proc. Am. Soc. Inf. Sci. Technol 40(1), 240–246 (2003).  https://doi.org/10.1002/meet.1450400130CrossRefGoogle Scholar
  6. 6.
    G. Marchionini, Exploratory search: From finding to understanding. Commun. ACM 49(4), 41–46 (2006).  https://doi.org/10.1145/1121949.1121979CrossRefGoogle Scholar
  7. 7.
    S. Monchaux, F. Amadieu, A. Chevalier, C. Mariné, Query strategies during information searching: Effects of prior domain knowledge and complexity of the information problems to be solved. Inf. Process. Manage. 51(5), 557–569 (2015).  https://doi.org/10.1016/j.ipm.2015.05.004
  8. 8.
    I. Reisoğlu, A. Çebi, T. Bahçekapılı, Online information searching behaviours: examining the impact of task complexity, information searching experience, and cognitive style. Interactive Learning Environments, pp. 1–18 (2019).  https://doi.org/10.1080/10494820.2019.1662456
  9. 9.
    M. Tibau, S.W.M. Siqueira, B. Pereira Nunes, T. Nurmikko-Fuller, R.F. Manrique, Using query reformulation to compare learning behaviors in web search engines, in 2019 IEEE 19th International Conference on Advanced Learning Technologies (ICALT), vol. 2161-377X, pp. 219–223 (2019).  https://doi.org/10.1109/ICALT.2019.00054
  10. 10.
    M.J. Tsai, C.C. Tsai, Information searching strategies in web-based science learning: the role of internet self-efficacy. Innov. Educ. Teaching Int 40(1), 43–50 (2003).  https://doi.org/10.1080/1355800032000038822CrossRefGoogle Scholar

Copyright information

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021

Authors and Affiliations

  1. 1.Federal University of the State of Rio de JaneiroRio de JaneiroBrazil
  2. 2.Australian National UniversityCanberraAustralia

Personalised recommendations