scholarly journals The effect of interface consistency and cognitive load on user performance in an information search task

Author(s):  
Jeremy Mendel ◽  
Richard Pak
2006 ◽  
Author(s):  
Sara J. Czaja ◽  
Joseph Sharit ◽  
Sankaran N. Nair

2020 ◽  
Author(s):  
Victoria Kordovski ◽  
Savanna M. Tierney ◽  
Samina Rahman ◽  
Luis D. Medina ◽  
Michelle A. Babicz ◽  
...  

Objective: Searching the Internet for health-related information is a complex and dynamic goal-oriented process that places demands on executive functions, which are higher-order cognitive abilities that are known to deteriorate with older age. This study aimed to examine the effects of older age on electronic health (eHealth) search behavior, and to determine whether executive functions played a mediating role in that regard. Method: Fifty younger adults (≤ 35 years) and 41 older adults (≥50 years) completed naturalistic eHealth search tasks involving fact-finding (Fact Search) and symptom diagnosis (Symptom Search), a neurocognitive battery, and a series of questionnaires. Results: Multiple regression models with relevant covariates revealed that older adults were slower and less accurate than younger adults on the eHealth Fact Search task, but not on the eHealth Symptom Search task. Nevertheless, executive functions mediated the relationship between older age and eHealth Fact Search and Symptom Search accuracy. Conclusions: Older adults can experience difficulty searching the Internet for some health-related information, which is at least partly attributable to executive dysfunction. Future studies are needed to determine the benefits of training in the organizational and strategic aspects of Internet search for older adults and whether these findings are applicable to clinical populations with executive dysfunction.


2002 ◽  
Vol 14 (1) ◽  
pp. 157-177 ◽  
Author(s):  
Jennifer M. Mueller ◽  
John C. Anderson

An auditor generating potential explanations for an unusual variance in analytical review may utilize a decision aid, which provides many explanations. However, circumstances of budgetary constraints and limited cognitive load deter an auditor from using a lengthy list of explanations in an information search. A two-way between-subjects design was created to investigate the effects of two complementary approaches to trimming down the lengthy list on the number of remaining explanations carried forward into an information search. These two approaches, which represent the same goal (reducing the list) but framed differently, are found to result in a significantly different number of remaining explanations, in both low- and high-risk audit environments. The results of the study suggest that the extent to which an auditor narrows the lengthy list of explanations is important to the implementation of decision aids in analytical review.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Anna Matysek ◽  
Jacek Tomaszczyk

PurposeThe quest to discover optimal conditions or amounts has been carried out in many scientific disciplines and practical fields. In astrophysics, biology, medicine, psychology and education, the quest has resulted in finding the right amount of something, a desirable middle between extremes, a balance between conditions or the optimal state of a system. The results are referred to as the Goldilocks principle, which is based on the idea of being “just right”. The aim of our study was to find out if there are any measures in information search that could be identified as Goldilocks ranges.Design/methodology/approachWe conducted a user experiment in which 68 participants carried out a time-unlimited, topical search task involving finding relevant websites on the basis of which the participants were supposed to prepare a presentation on a given topic. We examined aspects of their search behavior.FindingsWe found that information search Goldilocks ranges can be identified for a length of a search session, number of relevant results, number of queries submitted and number of search engine results pages (SERPs) visited. This preliminary study has resulted in indicating the following dominant ranges: Number of relevant documents found: 5–8; Time spent searching: 21–35 min; Number of queries submitted: 3–7; Number of SERPs viewed: 1–3.Originality/valueTill now, no one has studied Goldilocks ranges in information retrieval. The Goldilocks ranges have some practical implications for improving the effectiveness of web searching.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Kyoungsik Na

PurposeThis study explores the effects of cognitive load on the propensity to reformulate queries during information seeking on the web.Design/methodology/approachThis study employs an experimental design to analyze the effect of manipulations of cognitive load on the propensity for query reformulation between experimental and control groups. In total, three affective components that contribute to cognitive load were manipulated: mental demand, temporal demand and frustration.FindingsA significant difference in the propensity of query reformulation behavior was found between searchers exposed to cognitive load manipulations and searchers who were not exposed. Those exposed to cognitive load manipulations made half as many search query reformulations as searchers not exposed. Furthermore, the National Aeronautical and Space Administration Task Load Index (NASA-TLX) cognitive load scores of searchers who were exposed to the three cognitive load manipulations were higher than those of searchers who were not exposed indicating that the manipulation was effective. Query reformulation behavior did not differ across task types.Originality/valueThe findings suggest that a dual-task method and NASA-TLX assessment serve as good indicators of cognitive load. Because the findings show that cognitive load hinders a searcher's interaction with information search tools, this study provides empirical support for reducing cognitive load when designing information systems or user interfaces.


2015 ◽  
Vol 105 (1) ◽  
pp. 157-166
Author(s):  
Francisco López-Orozco ◽  
Luis D. Rodríguez-Vega

Author(s):  
Hyun Woong (Daniel) Chang ◽  
Steven Kaszak ◽  
Peter C. Kipp ◽  
Jesse C. Robertson

Following the SEC’s mandate for Inline XBRL (iXBRL) formatted financial filings, we experimentally investigate the effects of iXBRL filings and tag type (matching or non-matching) on managers’ decisions. iXBRL filings facilitate information search and information match by allowing users to view XBRL data in HTML filings, while XBRL filings facilitate information search only because they do not include this integration with human-readable HTML filings. Matching tags consistently tag data across firms and disclosures, which should facilitate inter-firm comparisons and improve decision making relative to non-matching tags. Drawing on cognitive load theory, we find that managers make more (less) effective decisions when presented with financial information formatted in iXBRL (XBRL) and when tags match (do not match). Mediation analysis reveals that managers’ cognitive load mediates the relationship between iXBRL disclosure format and decision effectiveness, but only for non-matching tags, consistent with moderated-mediation. We offer implications for practice and research suggestions.


2011 ◽  
Vol 10 (03) ◽  
pp. 209-224 ◽  
Author(s):  
Barbara Bazzanella ◽  
Heiko Stoermer ◽  
Paolo Bouquet

Searching for information about individual entities such as persons, locations, events, is an important activity in Internet search today, and is in its core a very semantic-oriented task. Several ways for accessing such information exist, but for locating entity-specific information, search engines are the most commonly used approach. In this context, keyword queries are the primary means of retrieving information about a specific entity. We believe that an important first step of performing such a task is to understand what type of entity the user is looking for. We call this process Entity Type Disambiguation. In this paper, we present a Naive Bayesian Model for entity type disambiguation that explores our assumption that an entity type can be inferred from the attributes a user specifies in a search query. The model has been applied to queries provided by a large sample of participants in an experiment performing an entity search task. The beneficial impact of this approach for the development of new search systems is discussed.


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