2023
DOI: 10.1186/s41235-023-00506-w
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Investigating the different domains of environmental knowledge acquired from virtual navigation and their relationship to cognitive factors and wayfinding inclinations

Veronica Muffato,
Laura Miola,
Marilina Pellegrini
et al.

Abstract: When learning an environment from virtual navigation people gain knowledge about landmarks, their locations, and the paths that connect them. The present study newly aimed to investigate all these domains of knowledge and how cognitive factors such as visuospatial abilities and wayfinding inclinations might support virtual passive navigation. A total of 270 participants (145 women) were tested online. They: (i) completed visuospatial tasks and answered questionnaires on their wayfinding inclinations; and (ii) … Show more

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Cited by 4 publications
(2 citation statements)
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“…The best way to avoid data loss is to make the experience agreeable for participants so that they feel valued (for example, by being informed of requirements, their progress and level of performance). Because of past exploitation (participants paid almost nothing for demanding tasks), it seems that some online platforms are better avoided for test evaluation because participants are no longer motivated to answer honestly or because answers are provided by bots (Eyal et al, 2022 ; Hays et al, 2015 ; Moss et al, 2023 ; Muraki et al, 2023 ). Additional data cleaning procedures may involve examining correlations between participants (particularly effective for performance tests where items differ in difficulty), assessing response times, and identifying recurring patterns of responding that disregard the actual content being presented.…”
Section: The Basics Of Individual Differences Testingmentioning
confidence: 99%
“…The best way to avoid data loss is to make the experience agreeable for participants so that they feel valued (for example, by being informed of requirements, their progress and level of performance). Because of past exploitation (participants paid almost nothing for demanding tasks), it seems that some online platforms are better avoided for test evaluation because participants are no longer motivated to answer honestly or because answers are provided by bots (Eyal et al, 2022 ; Hays et al, 2015 ; Moss et al, 2023 ; Muraki et al, 2023 ). Additional data cleaning procedures may involve examining correlations between participants (particularly effective for performance tests where items differ in difficulty), assessing response times, and identifying recurring patterns of responding that disregard the actual content being presented.…”
Section: The Basics Of Individual Differences Testingmentioning
confidence: 99%
“…While such diversity need not be a bad thing for research, it is important to know how well the different scales converge, especially if they are used for clinical diagnosis and have real-life implications. Similarly, we may wonder to what extent different measures of working memory or executive function converge on the traits they claim to measure (Miyake et al, 2000;Muffato et al, 2023;Rey-Mermet et al, 2018;Snyder et al, 2021).…”
Section: Evaluating and Strengthening Existing Testsmentioning
confidence: 99%