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In this paper, we examined why information searchers perceive search tasks as difficult, and what factors/reasons make them perceive tasks as difficult. We also examined if task difficulty reasons vary across different tasks (task types). Data was collected through a controlled laboratory experiment in which tasks were designed following a classification scheme. A total of 32 undergraduate students participated, each was given 4 search tasks, and they were asked in questionnaires both before and after the tasks for task difficulty ratings and why they gave 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. Difficulty reasons were categorized following this scheme. Results showed that searchers had some common reasons for task difficulty in different tasks, but most of the difficulty reasons varied across tasks. For each task, there were also common reasons for task difficulty, although there was some variation here as well. Task difficulty was also found to be negatively correlated with users topic knowledge, previous experience, and topic interest. Our findings help understand search task difficulty, as well as the relationships between task difficulty and task type, knowledge background, etc. These can also be helpful with experiment task design. © 2013 ACM.
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We report findings on how the user's perception of task difficulty changes before and after searching for information to solve tasks. We found that while in one type of task, the dependent task, this did not change, in another, the parallel task, it did. The findings have implications on designing systems that can provide assistance to users with their search and task solving strategies.
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We report findings that help us better understand the difficulty of tasks which involve information seeking, retrieving, gathering, and use. We examined the data gathered from two interactive information retrieval user studies on how users' perception of task difficulty changes before and after searching for information to solve tasks, and how the difficulty of tasks relates with users' background, previous experience with the tasks, and knowledge of the task topics, etc. The two studies employed carefully designed tasks with different types along several dimensions: task structure (subtasks being dependent upon or parallel with each other), task goal in quality (being specific or amorphous), and naming (being named or unnamed). It was found that while in some types of tasks, users' perceptions of task difficulty did not change before and after working on the tasks, in others, this did, either increasing or decreasing. Specifically, in the dependent-structured task, this did not change. In the parallel-structured or specific/named task, it decreased. In the amorphous/unnamed task, it increased. We also found that users' background factors do not normally correlate with their perceived task difficulty, or perceived difficulty change. In addition to helping understand the dynamic and complex nature of task difficulty, our findings have implications for system design that can provide assistance to users with their search and task solving strategies.
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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.
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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.
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In this study, we attempted to use dwell time on content pages as a predictor of document usefulness, and evaluated the prediction performance in different types of tasks. A user study was conducted to address this research problem. A total of 32 participants conducted searches associated with 4 different tasks, varying along several task type dimensions. In the study, participants were asked to save documents that were useful for the tasks during the searches. Participants' information-seeking activities were recorded. Using the logged dataset, we used the recursive partitioning method to identify the best threshold (cutoff point) of dwell time to predict which pages would be useful, i.e., be saved by the users. We examined the differences in the threshold and compared the prediction performance for each type of task. Our results indicate that the threshold should be developed according to the type of task users are working on. While the prediction performance using dwell time as the only indicator of document usefulness is acceptable for Factual tasks, it is not good for Intellectual tasks. Our results have implications on IR system design.
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