Document Type : Original Article
Authors
1 Lecturer, Library and Information Science, Department of Knowledge and Information Science, Payame Noor University, Tehran, Iran
2 Assistant Professor, Knowledge and Information Science, Department of Knowledge and Information Science, School of Management, University of Tehran, Tehran, Iran
3 Assistant Professor, Knowledge and Information Science, Department of Knowledge and Information Science, School of Educational Sciences and Psychology, Shiraz University, Shiraz, Iran
Abstract
Introduction: Due to various factors such as mental models, users apply different methods when searching information retrieval systems. Therefore, this study aimed to determine the relationship between the students of Isfahan University of Medical Sciences (IUMS) mental models and their web searching behavior.Methods: A mixed approach was used in this applied research. In the identification stage (qualitative stage), the components of users’ mental models were determined using qualitative content analysis methods and semi-structured interviews, thinking aloud protocol and observation. Then, the types of mental models were identified. In quantitative stage, transaction log analysis and observation tool were used to investigate web search behavior. Then, the relationship between users' mental models and some variables of their web search behavior was investigated. The study population included all post-graduate students of IUMS among which 60 students were selected using purposeful sampling method. The descriptive and inferential statistics (Kolmogorov–Smirnov and Pearson correlation) was recruited using SPSS software.Results: In this research, 14 mental model components were identified. The majority of students (55%) had structural mental models. A significant association was observed between students’ mental models and web searching behavior in impact search session length, the complexity of query and natural language queries variables.Conclusion: Students’ mental models impact some web searching behavior variables, therefore, research in this field can lead to a better understanding of why users behave in certain ways. It can be a good method for improving information retrieval systems.
Keywords
- Mori R, Yamaoka T. On the measurement of mental models for interface design. Proceedings of the 7th International Conference on Advances in Computer-Human Interactions; 2014 March 23-27; Barcelona, Spain; 2014. p. 66-71.
- Linxen S, Heinz S, Müller LJ, Tuch A, Opwis K. Mental models for web objects in different settings. Proceedings of CHI'14 Conference on Human Factors in Computing Systems; 2014 Apr. 26-May 1; Toronto, Canada; 2014. p. 2557-62.
- Guthrie RW. Audience directed models and software design: How developer mental models of users influence the design of enterprise system features [PhD Thesis]. Claremont, CA: The Claremont Graduate University 2008.
- Li P. Doctoral students' mental models of a web search engine: An exploratory study [PhD Thesis]. Montreal, QC: McGill University; 2007.
- Mlilo S, Thatcher A. Mental models: Have users' mental models of web search engines improved in the last ten years? [MSc Thesis]. Johannesburg, South Africa: University of the Witwatersrand; 2010.
- Hochstotter N, Koch M. Standard parameters for searching behaviour in search engines and their empirical evaluation. J Inf Sci 2009; 35(1): 45-65.
- Aula A, Khan RM, Guan Z. How does search behavior change as search becomes more difficult? Proceedings of the SIGCHI Conference on Human Factors in Computing Systems; 2010 Apr. 10-15; New York, NY.
- Hariri N, Fazli F. A study on the usage of electronic journals, databases and alert services by faculty members of Shahid Beheshti University of Medical Sciences. Journal of Epistemology 2012; 5(16): 49-60. [In Persian].
- Hashemian M, Janatikia M, Hashemian A. Information seeking skills in online databases of iranian national medical digital library: A study among residents of Isfahan university of medical sciences. Health Inf Manage 2013; 10(1): 1-8. [In Persian].
- Okhovati M, Rahimi M, Zolala F. Effects of contextual factors on information seeking behavior on the web by postgraduate students at Kerman University of Medical Sciences. Journal of Information Processing and Management 2015; 30(2): 419-41. [In Persian].
- Mahmoodi Maybonde M, Osareh F. A Comparison of Online Search Skills among Public Medical Science Students of Bandar Abbas and Rafsanjan Universities in 2008-2009. Journal of Information Processing and Management 2012; 27(2): 307-23. [In Persian].
- Saxon S. Seventh grade students and electronic information retrieval systems: An exploratory study of mental model formation, completeness and change. Tallahassee, FL: Florida State University; 1997.
- Dimitroff A. Mental models and error behavior in an interactive bibliographic retrieval system [PhD Thesis]. Ann Arbor, MI: University Microfilms International; 1990.
- Holman L. Millennial students' mental models of information retrieval. J Acad Librariansh 2011; 37(1): 19-27.
- Zhang Y. The development of users' mental models of MedlinePlus in information searching. Libr Inf Sci Res 2013; 35(2): 159-70.
- Crudge SE, Johnson FC. Using the information seeker to elicit construct models for search engine evaluation. J Am Soc Inf Sci Technol 2004; 55(9): 794-806.
- Wilkinson EH. Usability and mental models of Google and primo in the context of an academic tertiary library [MSc Thesis]. Wellington, New Zealand: Victoria University of Wellington; 2009.
- Willson R, Given LM. Student search behaviour in an online public access catalogue: An examination of 'searching mental models' and 'searcher self-concept'. Inf Res 2014; 19(3): 640.
- Lewis C, Contrino J. Making the invisible visible: Personas and mental models of distance education library users. Journal of Library & Information Services in Distance Learning 2016; 10(1-2): 15-29.
- Safari A, Behzadi H, Radad I. Investigating master students' mental models of Google search engine. Journal of Information Processing and Management 2017; 32(4): 989-1016. [In Persian].
- Polit DF, Beck CT. The content validity index: Are you sure you know what's being reported? Critique and recommendations. Res Nurs Health 2006; 29(5): 489-97.
- Kulesza T, Stumpf S, Burnett M, Yang S, Kwan I, Wong WK. Too much, too little, or just right? Ways explanations impact end users' mental models. Proceedings of the IEEE Symposium on Visual Languages and Human-Centric Computing; 2013 Sep 15-19; San Jose, CA.
- Nakhoda M, Kazempour Z, Naghshineh N, Mirzabeigi M. Adjustment and development of health user's mental model completeness scale in search engines. J Health Man & Info 2016; 3(4): 111-9.
- Zhou M. Gender difference in web search perceptions and behavior: Does it vary by task performance? Comput Educ 2014; 78(Supplement C): 174-84.
- Asadi M. Analysis of users' query reformulation behavior in Web with regard to Wholis-tic/analytic cognitive styles, Web experience, and search task type. Human Info Interact 2014; 1(3): 191-203. [In Persian].
- Marchionini G. Information seeking in electronic environments. Cambridge, UK: Cambridge University Press; 1997.
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