An Analysis of Information Types and Cognitive Activities Involved in Cross-session Search

2021 
Previous studies found that cross-session search tasks are often complex due to the uncertainty of task features, users' perception of the tasks, and the challenges (e.g., time limitation, interruptions) that users encounter during the process. Using Anderson & Krathwohl's taxonomy of learning, we analyzed the complexity of real-life cross-session search tasks reported by 110 Amazon Mechanical Turk workers. We found that cross-session search tasks often require different types of information (i.e., factual and conceptual information, procedure information, opinions, and information for helping metacognition) and are frequently associated with higher-level cognitive activities, including: applying analyzing, evaluating, and creating. Our findings add knowledge about cross-session search, and have insights for future research related to system design and studying cross-session search.
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