Using a Cognitive Model of Web-Navigation to Generate Support for 3D Virtual Navigation

AbstractThough the cognitive processes controlling user navigation in virtual environments as well as in websites are similar, cognitive models of web-navigation have never been used for generating support in virtual environment navigation. We created a simulated 3D building of a hospital and presented users various navigation tasks under two conditions: a control condition and a model-generated support condition. Participants with model-generated support participants took significantly less time to reach their destination and were significantly less disoriented. The impact of model-generated support on disorientation was especially higher for users with low spatial ability

A STUDY ON THE ROLE OF NON-HYPERLINK TEXT ON WEB NAVIGATION

Cognitive models of web navigation have been used for evaluating websitesand predicting user navigation behavior. Currently they predict the correcthyperlink by using information from the hyperlink text alone and ignore allother textual information on a webpage. The validity of this assumption isexamined by investigating the role of non-hyperlink text on user navigationbehavior. In the first experiment, we created two versions of a website byremoving the non-hyperlink text from it. We found that there was no significanteffect of non-hyperlink text on the user navigation behavior. Participants wereequally accurate, selected the same set of pages to visit and spent the sameamount of time on that common set with or without non-hyperlink text. Thisresult validates the assumptions of those models of user-navigation behaviorthat consider information from the hyperlink text only. However, in a followupexperiment, we included high-relevance and low-relevance pictures on thewebsite, and repeated the experiment with and without non-hyperlink text.We found that participants were more accurate in the presence of non-hyperlinktext than without it. This result suggests that the presence of pictures mightprime the users to pay attention to non-hyperlink text, which increases the taskaccuracy

A study on the role of non-hyperlink text on web navigation

Tyt. z nagłówka.Bibliogr. s. 21-22.Cognitive models of web navigation have been used for evaluating websites and predicting user navigation behavior. Currently they predict the correct hyperlink by using information from the hyperlink text alone and ignore all other textual information on a webpage. The validity of this assumption is examined by investigating the role of non-hyperlink text on user navigation behavior. In the first experiment, we created two versions of a website by removing the non-hyperlink text from it. We found that there was no significant effect of non-hyperlink text on the user navigation behavior. Participants were equally accurate, selected the same set of pages to visit and spent the same amount of time on that common set with or without non-hyperlink text. This result validates the assumptions of those models of user-navigation behavior that consider information from the hyperlink text only. However, in a follow-up experiment, we included high-relevance and low-relevance pictures on the website, and repeated the experiment with and without non-hyperlink text. We found that participants were more accurate in the presence of non-hyperlink text than without it. This result suggests that the presence of pictures might prime the users to pay attention to non-hyperlink text, which increases the task accuracy.Dostępny również w formie drukowanej.KEYWORDS: web-navigation, main-content, text, semantics

Effect of Task Presentation on the Performance of Crowd Workers — A Cognitive Study

We present our ongoing research on improving the task presentation using cognitively inspired features to optimize the performance of crowd workers. For the task of extracting text from scanned images, we generated three task-presentation designs by modifying two features of the task - visual saliency of target fields and working memory requirements. Our experiments conducted on Amazon Mechanical Turk (AMT) indicate that modifying visual saliency results in better performance