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  • This paper reports on an examination of why information searchers find search tasks difficult and the specific reasons they feel difficult. Data was collected through a controlled laboratory experiment with 32 participants, each working with 4 search tasks. They were asked in questionnaires, both before and after the tasks, for task difficulty ratings and their reasoning for giving those ratings. We developed a coding scheme based on the difficulty reasons users gave, which covered various aspects of task, user, and user-task interaction. This helps us understand search task difficulty, as well as provides a scheme for task difficulty control in experiment task design.

  • Search task difficulty has been attracting much research attention in recent years, mostly regarding its relationship with searchers' behaviors and the prediction of task difficulty from search behaviors. However, it remains unknown what makes searchers feel the difficulty. A study consisting of 48 undergraduate students was conducted to explore this question. Each participant was given 4 search tasks that were carefully designed following a task classification scheme. Questionnaires were used to elicit participants' ratings on task difficulty and why they gave those ratings. Based on the collected difficulty reasons, a coding scheme was developed, which covered various aspects of task, user, and user-task interaction. Difficulty reasons were then categorized following this scheme. Results showed that searchers reported some common reasons leading to task difficulty in different tasks, but most of the difficulty reasons varied across tasks. In addition, task difficulty had some common reasons between searchers with low and high levels of topic knowledge, although there were also differences in top task difficulty reasons between high and low knowledge users. These findings further our understanding of search task difficulty, the relationship between task difficulty and task type, and that between task difficulty and knowledge level. The findings can also be helpful with designing tasks for information search experiments, and have implications on search system design both in general and for personalization based on task type and searchers' knowledge. (C) 2014 Elsevier Ltd. All rights reserved.

Last update from database: 3/13/26, 4:15 PM (UTC)

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