The Effects of Task Complexity on the Use of Different Types of Information in a Search Assistance Tool

Choi, Bogeum; Ward, Austin R.; Li, Yuan; Arguello, Jaime; Capra, Robert

doi:10.1145/3371707

Cited by 12 publications

(5 citation statements)

References 39 publications

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“…This study has been made possible thanks to CoST which has been designed in such a way that each participant has expertise in one among the 3 domains and has completed the same 15 search tasks corresponding to one task per complexity (×5) and per domain (×3). Thus, CoST setting fills in the critical gap identified by Choi et al [8]inthe majority of previous users studies which only design a single task per complexity.…”

Section: Analyzing the Effects Of Task Domain And Its Interaction Wit...mentioning

confidence: 89%

“…It is worth of mention that while a number of previous studies argued that the complexity of tasks may be impacted by both the domain in which they fall and doers' expertise [8,36,38], the majority of user studies offer a single task per complexity level and/or type. The main reason underlying this limitation is that the multiplication of tasks requires more effort and commitment from the users.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

CoST: An annotated Data Collection for Complex Search

Dosso

Moreno

Chevalier

et al. 2021

Proceedings of the 30th ACM International Conference on Information &Amp; Knowledge Management

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While great progress is made in the area of information access, there are still open issues that involve designing intelligent systems supporting task-based search. Despite the importance of task-based search, the information retrieval and information science communities still feel the lack of open-ended and annotated datasets that enable the evaluation of a number of related facets of search tasks in downstream applications. Existing datasets are either sampled from large-scale logs but provide poor annotations, or sampled from lower-scale user studies but focus on ranked list evaluation. In this work, we present CoST 1 : a novel richly annotated dataset for evaluating complex search tasks, collaboratively designed by researchers from the computer science and cognitive psychology domains, and intended to answer a wide range of research questions dealing with task-based search. CoST includes 5667 queries recorded in 630 task-based sessions that result from a user study involving 70 french native participants who are expert in one among 3 different domains of expertise (computer science, medicine, psychology). Each participant completed 15 tasks with 5 different types of cognitive complexity (fact-finding, exploratory learning, decisionmaking, problem-solving, multicriteria-inferential). In addition to search data (e.g., queries and clicks), CoST provides task and sessionrelated data, task annotations and query annotations. We illustrate possible usages of CoST through the evaluation of query classification models and the understanding of the effect of task complexity and domain on user's search behavior.

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Section: Analyzing the Effects Of Task Domain And Its Interaction Wit...mentioning

confidence: 89%

Section: Introductionmentioning

confidence: 99%

CoST: An annotated Data Collection for Complex Search

Dosso

Moreno

Chevalier

et al. 2021

Proceedings of the 30th ACM International Conference on Information &Amp; Knowledge Management

View full text Add to dashboard Cite

show abstract

“…Implication for complex search process —Though this study mainly focuses on exploratory search, our findings suggest that tools like OrgBox can be applied to other complex search scenarios when users need to find information from different sources, collect different types of information, and conduct comparison, evaluation, and idea generation over time. For instance, Researchers found that complex tasks often require a great amount of cognitive and metacognitive activities as users need to find different types of information (e.g., factual, procedural information, opinions; Choi et al, 2019) and their solutions/paths to the outcomes are unclear due to open‐ended task requirements like exploratory search (Byström & Järvelin, 1995; Campbell, 1988). The OrgBox tool can help distinguish different information types and topics by contrasting the information between boxes.…”

Section: Discussionmentioning

confidence: 99%

Thinking inside the box: An evaluation of a novel search‐assisting tool for supporting (meta)cognition during exploratory search

Crescenzi

Ward

et al. 2023

Asso for Info Science & Tech

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Exploratory searches involve significant cognitively demanding aiming at learning and investigation. However, users gain little support from search engines for their cognitive and metacognitive activities (e.g., discovery, synthesis, planning, transformation, monitoring, and reflection) during exploratory searches. To better support the exploratory search process, we designed a new search assistance tool called OrgBox. OrgBox allows users to drag-and-drop information they find during searches into "boxes" and "items" that can be created, labeled, and rearranged on a canvas. We conducted a controlled, within-subjects user study with 24 participants to evaluate the OrgBox versus a baseline tool called the OrgDoc that supported rich-text features. Our findings show that participants perceived the OrgBox tool to provide more support for grouping and reorganizing information, tracking thought processes, planning and monitoring search and task processes, and gaining a visual overview of the collected information. The usability test reveals users' preferences for simplicity, familiarity, and flexibility of the design of OrgBox, along with technical problems such as delay of response and restrictions of use. Our results have implications for the design of search-assisting systems that encourage cognitive and metacognitive activities during exploratory search processes.

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“…useful queries). Applying the former, Choi et al (2019) formed four information types to study how search task complexity affects their use: facts (objective statements), concepts (noun phrases denoting ideas, principles or entities), opinions (subjective statements) and insights (advice or tips). Choi and others emphasized that their typology is based on inherent characteristics of information as opposed to Bystr€ om's (1999, p. 45) functional role of information, that is, using information as an abstract tool.…”

Section: Approaches To Task Information In Information Studiesmentioning

confidence: 99%

“…useful queries). Applying the former, Choi et al. (2019) formed four information types to study how search task complexity affects their use: facts (objective statements), concepts (noun phrases denoting ideas, principles or entities), opinions (subjective statements) and insights (advice or tips).…”

Section: Literature Reviewmentioning

confidence: 99%

Task information types related to data gathering in media studies

Korkeamäki

Keskustalo

Kumpulainen

2022

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PurposeThe purpose of this paper is to examine what types of task information media scholars need while gathering research data to create new knowledge.Design/methodology/approachThe research design is qualitative and user-oriented. A total of 25 media scholars were interviewed about their research processes and interactions with their research data. The interviews were semi-structured, complemented by critical incident interviews. The analysis focused on the activity of gathering research data. A typology of information (task, domain and task-solving information) guided the analysis of information types related to data gathering, with further analysis focusing only on task information types.FindingsMedia scholars needed the following task information types while gathering research data to create new knowledge: (1) information about research data (aboutness of data, characteristics of data, metadata and secondary information about data), (2) information about sources of research data (characteristics of sources, local media landscapes) and (3) information about cases and their contexts (case information, contextual information). All the task information types should be considered when building data services and tools to support media scholars' work.Originality/valueThe paper increases understanding of the concept of task information in the context of gathering research data to create new knowledge and thereby informs the providers of research data services about the task information types that researchers need.

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The Effects of Task Complexity on the Use of Different Types of Information in a Search Assistance Tool

Cited by 12 publications

References 39 publications

CoST: An annotated Data Collection for Complex Search

CoST: An annotated Data Collection for Complex Search

Thinking inside the box: An evaluation of a novel search‐assisting tool for supporting (meta)cognition during exploratory search

Task information types related to data gathering in media studies

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