Distribution of cognitive load in Web search

Abstract

The search task and the system both affect the demand on cognitive resources during information search. In some situations the demands may become too high for a person. This article has a three-fold goal. First, it presents and critiques methods to measure cognitive load. Second, it explores the distribution of load across search task stages. Finally, it seeks to improve our understanding of factors affecting cognitive load levels in information search. To this end, a controlled Web search experiment with 48 participants was conducted. Interaction logs were used to segment search tasks semiautomatically into task stages. Cognitive load was assessed using a new variant of the dual-task method. Average cognitive load was found to vary by search task stages. It was significantly higher during query formulation and user description of a relevant document as compared to examining search results and viewing individual documents. Semantic information shown next to the search results lists in one of the studied interfaces was found to decrease mental demands during query formulation and examination of the search results list.These findings demonstrate that changes in dynamic cognitive load can be detected within search tasks. Dynamic assessment of cognitive load is of core interest to information science because it enriches our understanding of cognitive demands imposed on people engaged in the search process by a task and the interactive information retrieval system employed.

The economics in interactive information retrieval

“…If β is greater than one than it is relatively more expensive to pose a query than to assess a document, and vice versa. For these experiments, we determined β by drawing upon the user experiments conducted in [9], where the cognitive load of various interactions in the information seeking process were measured. In these experiments, a dual-task method was used which measured how long it takes for the participant to respond to a secondary task (in milliseconds).…”

The effect of cognitive abilities on information search for tasks of varying levels of complexity

“…As the user's knowledge changes as he/she engages in cognitive processing [30,38], the original information need changes also, requiring the user to adjust his or her search strategy to accommodate the new need [43]. It is also generally accepted that the search process will require the user to exert mental effort in varying degrees depending on individual characteristics [22,26], the search tasks and their structures [12,48], and the information system [10].…”

Real-time Prediction of User Performance based on Pupillary Assessment via Eye-Tracking

“…Both IS (Evaristo, Adams, & Curley, 1995;Johannsen, Levis, & Stassen, 1992;Stassen, Johannsen, & Moray, 1990) and, in particular, neuroIS research (Gwizdka, 2010;Riedl et al, 2010: Dimoka et al, 2011Dimoka et al, 2012;Buettner, 2014Buettner, , 2017bde Guinea et al, 2014) has often cited the means of determining a user's mental effort as a fundamental problem. Researchers have established mental effort as an essential construct in theories such as information processing theory (Miller, 1956), cognitive load theory (Sweller, 1988;Sweller, van Merrienboer, & Paas, 1998), task-technology fit theory (Goodhue & Thompson, 1995), flow theory (Csíkszentmihályi, 1975), job demands-resources theory (Bakker & Demerouti, 2006), psychobiological theory (Kock, 2004), and dual process theory (Stanovich & West, 2000).…”

“…Xie & Salvendry, 2000). However, IS scholars have pointed out the need to pay attention to the dynamics of mental effort (e.g., Gwizdka, 2010).…”