Understanding Procedural Search Tasks “in the Wild”

People often search online for procedural (i.e., “how-to”) knowledge. A procedural search task might involve a do-it-yourself project, cooking a dish, fixing a problem, or learning a new skill. Prior research has studied procedural search tasks from different perspectives: estimating the frequency of procedural searches online, understanding how people acquire procedural knowledge in specific contexts, and developing tools to support procedural search. Less research has aimed at deeply understanding procedural search tasks “in the wild”. To bridge this gap, we conducted a survey (N = 128) on Amazon Mechanical Turk. Participants were asked to recall a recent procedural task for which they searched online. Participants were asked open-ended questions about the task itself and their unique situation (e.g., constraints and needs). Additionally, participants provided webpages they found useful in their searches and described the characteristics of the page that made it useful. Finally, they provided useful pieces of information from each selected page and explained what they gained from the information. Using an inductive coding approach, we analyzed participants’ responses to gain insights about: (1) procedural task characteristics, (2) goals, (3) constraints, (4) contextual factors, (5) relevance criteria, and (6) gains obtained from useful information. Based on our results, we discuss important implications for future research and system design.