Zahra Kazempour; Maryam Nakhoda; Mahdieh Mirzabeigi; Nader Naghshineh
Volume 14, Issue 5 , October 2017, , Pages 217-223
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 ...
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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.
