Better Understanding Procedural Search Tasks: Perceptions, Behaviors, and Challenges

Author:

Choi Bogeum1ORCID,Casteel Sarah1ORCID,Arguello Jaime1ORCID,Capra Robert1ORCID

Affiliation:

1. School of Information and Library Science University of North Carolina at Chapel Hill

Abstract

People often search for information to acquire procedural knowledge–“how to” knowledge about step-by-step procedures, methods, algorithms, techniques, heuristics, and skills. A procedural search task might involve implementing a solution to a problem, evaluating different approaches to a problem, and brainstorming on the types of problems that can be solved with a specific resource. We report on a study ( N =36) that aimed to better understand how people search for procedural knowledge. Much research has investigated how search task characteristics impact people’s perceptions and behaviors. Along these lines, we manipulated procedural search tasks along two orthogonal dimensions: product and goal. The product dimension relates to the main outcome of the task and the goal dimension relates to task’s success criteria. We manipulated tasks across three product categories and two goal categories. The study investigated four research questions. First, we examined the effects of the product and goal on participants’ (RQ1) pre-task perceptions, (RQ2) post-task perceptions, and (RQ3) search behaviors. Second, regardless of the task product and goal, by analyzing participants’ think-aloud comments and screen activities we closely examined how people search for procedural knowledge. Specifically, we report on (RQ4) important relevance criteria, types of information sought, and challenges.

Funder

U.S. Department of Defense

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Science Applications,General Business, Management and Accounting,Information Systems

Reference53 articles.

1. HealthAid: Extracting domain targeted high precision procedural knowledge from on-line communities

2. Lorin W. Anderson, David R. Krathwohl, Peter W. Airasian, Kathleen A. Cruikshank, Richard E. Mayer, Paul R. Pintrich, James Raths, and Merlin C. Wittrock. 2001. A Taxonomy for Learning, Teaching, and Assessing: A Revision of Bloom’s Taxonomy of Educational Objectives, Complete Edition.

3. Peter Bailey and Li Jiang. 2012. User task understanding: A web search engine perspective. (2012). https://www.microsoft.com/en-us/research/publication/user-task-understanding-a-web-search-engine-perspective/Presentation delivered at the NII Shonan: Whole-Session Evaluation of Interactive Information Retrieval Systems workshop. 8-11 October 2012 Shonan Japan.

4. An eye-tracking approach to the analysis of relevance judgments on the Web: The case of Google search engine

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