Medical students using Grateful Med: analysis of failed searches and a six-month follow-up study
Computers and Biomedical Research
Information and information sources in tasks of varying complexity
Journal of the American Society for Information Science and Technology
The effects of topic familiarity on information search behavior
Proceedings of the 2nd ACM/IEEE-CS joint conference on Digital libraries
MedicoPort: A medical search engine for all
Computer Methods and Programs in Biomedicine
Investigating behavioral variability in web search
Proceedings of the 16th international conference on World Wide Web
A faceted approach to conceptualizing tasks in information seeking
Information Processing and Management: an International Journal
How does search behavior change as search becomes more difficult?
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Search behaviors in different task types
Proceedings of the 10th annual joint conference on Digital libraries
The effect of task type and topic familiarity on information search behaviors
Proceedings of the third symposium on Information interaction in context
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In this paper, we investigate medical students medical search behavior on a medical domain. We use two behavioral signals: detailed query analysis (qualitative and quantitative) and task completion time to understand how medical students perform medical searches based on varying task complexity. We also investigate how task complexity and topic familiarity affect search behavior. We gathered 80 interactive search sessions from an exploratory survey with 20 medical students. We observe information searching behavior using 3 simulated work task scenarios and 1 personal scenario. We present quantitative results from two perspectives: overall and user perceived task complexity. We also analyze query properties from a qualitative aspect. Our results show task complexity and topic familiarity affect search behavior of medical students. In some cases, medical students demonstrate different search traits on a personal task in comparison to the simulated work task scenarios. These findings help us better understand medical search behavior. Medical search engines can use these findings to detect and adapt to medical students' search behavior to enhance a student's search experience.