7. Conclusions
Developing and supporting human search capabilities is at least equally important as developing the capabilities of search engines. Existing academic research suggests that particularly inexperienced users searching the Web utilize only a modest subset of the capabilities that the tools offer and are weak at understanding their real information needs, articulating them in a way that allows for effective searches, and interpreting search results in the context of those needs. This clearly suggests that training users to become better searchers is a worthwhile effort, and that understanding what makes certain search interventions successful and others not is vitally important for enabling users to make effective use of their time.
Our review of existing search training literature revealed relatively broadly scattered efforts that, to a large extent, were not programmatic or focused on developing well-defined theoretical models. This makes it difficult to integrate findings from different studies into cohesive bodies of work that would support the development and evaluation of new training interventions. In this chapter, we propose three approaches to using existing areas of research as a theoretical foundation for future work. Namely: a) understanding the nature of search processes is very important if we want to understand search training, because different stages of the search process require different training approaches; b) a thorough analysis of search errors forms a solid foundation for training approaches that helps users avoid the common errors; and c) training research from related disciplines, such as information systems, can be used to introduce new theoretical perspectives and suggest models that are also potentially helpful in search training.
Search is pervasive in modern life and performing effective online searches is a fundamentally important literacy skill, not only for 21st century knowledge professionals but for every individual who relies on material available from online sources. Understanding how we, as a research community, can help people become effective searchers is, therefore, of critical importance.
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Abdulla, G., Liu, B., and Fox, E. A. (1998). Searching the World-Wide Web: Implications From Studying Different User Behavior. Paper presented at the WebNet98 Conference, Orlando, FL.
Allen, B. L. (2001). Boolean Browsing in an Information System: An Experimental Test. Information Technology and Libraries, 20(1), 12–20.
Bandura, A. (1986). Social Foundations of Thought and Action: A Social Cognitive Theory. Englewood Cliffs, NJ: Prentice-Hall.
Bates, M. (1985). An Exploratory Paradigm for Online Information Retrieval. Paper Presented at the Sixth P International Research Forum in Information Science (IRFIS 6), Frascati, Italy.
Borgman, C. L. (1996). Why Are Online Catalogs Still Hard to Use? Journal of the American Society for Information Science and Technology, 47(7), 493–503.
Chan, H. C., Tan, B. C. Y, and Wei, K. K. (1999). Three Important Determinants of User Performance for Database Retrieval. International Journal of Human-Computer Studies, 51(5), 895–918.
Cheng, G. Y. T. (2003). Educational Workshop Improved Information-Seeking Skills, Knowledge, Attitudes and the Search Outcome of Hospital Clinicians: A Randomised Controlled Trial. Health Information and Libraries Journal, 20, 22–33.
Cloyd, B. and Spilker, B. (2000). Confirmation Bias in Tax Information Search: A Comparison of Law Students and Accounting Students. Journal of the American Taxation Association, 22, 60–71.
Colaric, S. M. (2003). Instruction for Web Searching: An Empirical Study. College and Research Libraries, 64(2), 111–122.
Compeau, D. and Higgins, C. (1995). Application of Social Cognitive Theory to Training for Computer Skills. Information Systems Research, 6(2), 144–176.
Cooper, W. (1988). Getting Beyond Boole. Information Processing and Management, 24(3), 243–248.
Davenport, T. H. and Prusak, L. (1993). Blow Up the Corporate Library. International Journal of Information Management, 13, 405–412.
Davis, F. D. and Yi, M. I. (2004). Improving Computer Skill Training: Behavior Modeling, Symbolic Mental Rehearsal, and the Role of Knowledge Structures. Journal of Applied Psychology, 89(3), 509–523.
Debowski, S. (2002). Developing Effective Electronic Information Seekers. Australian Journal of Management, 27, 21–30.
Detlor, B. (1999). Leveraging the Corporate Library Through Web User Training. Library Management, 20(7), 393.
Fallows, D. (2005). Search Engine Users. Washington, DC: Pew Reports.
Fallows, D., Rainie, L., and Mudd, G. (2004). Data Memo: The Popularity and Importance of Search Engines. Washington, DC: Pew Reports.
Ford, N., Miller, D., and Moss, N. (2001). The Role of Individual Differences in Internet Searching: An Empirical Study. Journal of the American Society for Information Science and Technology, 52(12), 1049–1066.
Halttunen, K. (2003a). Students’ Conceptions of Information Retrieval: Implications for the Design of Learning Environments. Library and Information Science Research, 25(3), 307–332.
Halttunen, K. (2003b). Scaffolding Performance in IR Instruction: Exploring Learning Experiences and Performance in Two Learning Environments. Journal of Information Science, 29(5), 375–390.
Halttunen, K. (2004). Two Information Retrieval Learning Environments: Their Design and Evaluation. Tampere University.
Halttunen, K. and Jarvelin, K. (2004). Assessing Learning Outcomes in Two Information Retrieval Learning Environments. Information Processing and Management, 41(4), 949–972.
Halttunen, K. and Sormunen, E. (2000). Learning Information Retrieval Through an Educational Game. Education for Information, 18(4), 289–311.
Hölscher, C. and Strube, G. (2000). Web Search Behavior of Internet Experts and Newbies. The International Journal of Computer and Telecommunications Networking, 33(1–6), 337–346.
Ingwersen, P. (1992). Information Retrieval Interaction. London: Taylor Graham.
Ingwersen, P. (1996). Cognitive Perspectives of Information Retrieval Interaction: Elements of a Cognitive IR Theory. Journal of Documentation, 52(1), 3–50.
Ingwersen, P. and Willet, P. (1995). An Introduction to Algorithmic and Cognitive Approaches for Information Retrieval. Libri, 45, 160–177.
Jansen, B. J. (2000). The Effect of Query Complexity on Web Searching Results. Information Research: An International Electronic Journal, 6(1).
Jansen, B. J. and Pooch, U. W. (2001). A Review of Web Searching Studies and a Framework for Future Research. Journal of the American Society of Information Science, 52(3), 235–246.
Jansen, B., J. Spink, A., and Saracevic, T. (2000). Real Life, Real Users, and Real Needs: A Study and Analysis of User Queries on the Web. Information Processing and Management, 36(2), 207–227.
Johnson, R.D. and Marakas, G. M. (2000). The Role of Behavioral Modeling in Computer Skills Acquisition: Toward Refinement of the Model. Information Systems Research, 11(4), 342–365.
Kim, K.-S. and Allen, B. (2002). Cognitive and Task Influences on Web Searching Behavior. Journal of the J American Society for Information Science and Technology, 53(2), 109–119.
Kirkpatrick, D. L. (1998). Evaluating Training Programs: The Four Levels. San Francisco: Berrett-Koehler Publishers.
Kraiger, K. J. Ford, K. and Salas, E. (1993). Application of Cognitive, Skill-Based, and Affective Theories of Learning Outcomes to New Methods of Training Evaluation. Journal of Applied Psychology, 78, 311–328.
Kuhlthau, C. C. (1993). Seeking Meaning: A Process Approach to Library and Information Services. Norwood, NJ: Ablex Publishing.
Lazonder, A. W. (2000). Exploring Novice Users’ Training Needs in Searching Information on the WWW. Journal of Computer Assisted Learning, 16(4), 326–335.
Lucas, W. and Topi, H. (2002). Form and Function: The Impact of Query Term and Operator Usage on Web Search Results. Journal of the American Society for Information Science and Technology, 53(2), 95–108.
Lucas, W. and Topi, H. (2004). Training for Web Search: Will It Get You in Shape? Journal of the American J Society for Information Science and Technology, 41(2), 383–403.
Marchionini, G. (1992). Interfaces for End-User Information Seeking. Journal of the American Society for J Information Science, 43(2), 156–163.
Pharo, N. (2002). The Search Situation and Transition Method Schema: A Tool for Analyzing Web Information Search Processes. Unpublished Ph.D. thesis, University of Tampere, Tampere, Finland.
Shneiderman, B., Byrd, D., and Croft, W. B. (1997, January 1997). Clarifying Search: A User-Interface Framework for Text Searches. Retrieved January, 2000, from http://www.dlib.org/dlib/january97/retrieval/01shneiderman.html
Silverstein, C., Henzinger, M., Marais, J., and Moricz, M. (1999). Analysis of a Very Large Web Search Engine Query Log. SIGIR Forum, 33(1), 6–12.
Sormunen, E. and Pennanen, S. (2004). The Challenge of Automated Tutoring in Web-Based Learning Environments for Information Retrieval Instruction. Information Research—An International Electronic Journal, 9(2), paper 169 [Available at: http://InformationR.net/ir/9-2/paper169.html].
Spink, A. and Saracevic, T. (1997). Interactive Information Retrieval: Sources and Effectiveness of Search Terms During Mediated Online Searching. Journal of the American Society for Information Science, 48(8), 741–761.
Spink, A., Wolfram, D., Jansen, B. J., and Saracevic, T. (2001). Searching the Web: The Public and Their Queries. Journal of the American Society for Information Science, 53(2), 226–234.
Sutcliffe, A., G. Ennis, M., and Watkinson, S. J. (2000). Empirical Studies of End-user Information Searching. Journal of the American Society for Information Science, 51(13), 1211–1231.
Te’eni, D. and Feldman, R. (2001). Performance and Satisfaction in Adaptive Websites: An Experiment on T Searches Within a Task-Adapted Website. Journal of AIS J, 2(3).
Topi, H. and Lucas, W. (2005). Searching the Web: Operator Assistance Required. Information Processing and Management, 41(2), 383–403.
Turtle, H. (1994). Natural Language vs. Boolean Query Evaluation: A Comparison of Retrieval Performance. In Proceedings of SIGIR 1994.
Yi, M. I. and Davis, F. D. (2001). Improving Computer Training Effectiveness for Decision Technologies: Behavior Modeling and Retention Enhancement. Decision Sciences, 32(3), 521–545.
Yi, M. I. and Davis, F. D. (2003). Developing and Validating an Observational Learning Model of Computer Software Training and Skill Acquisition. Information Systems Research, 14(2), 146–169.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer
About this chapter
Cite this chapter
Lucas, W., Topi, H. (2005). Learning and Training to Search. In: Spink, A., Cole, C. (eds) New Directions in Cognitive Information Retrieval. The Information Retrieval Series, vol 19. Springer, Dordrecht . https://doi.org/10.1007/1-4020-4014-8_11
Download citation
DOI: https://doi.org/10.1007/1-4020-4014-8_11
Publisher Name: Springer, Dordrecht
Print ISBN: 978-1-4020-4013-9
Online ISBN: 978-1-4020-4014-6
eBook Packages: Computer ScienceComputer Science (R0)