2017
DOI: 10.1080/17538947.2017.1349842
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Toward optimizing the design of virtual environments for route learning: empirically assessing the effects of changing levels of realism on memory

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Cited by 54 publications
(50 citation statements)
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References 58 publications
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“…Mixed levels of realism have been proposed for regular maps used for data exploration purposes (Jenny et al 2012) as well as for VR. In VR, egocentric-view-VR representations with selective photorealism (a mix of abstract and photorealistic representations) have been tested in the context of route learning, memory, and aging and have been shown to benefit users (Lokka et al 2018;Lokka and Çöltekin 2019).…”
Section: User Interaction and Interfacesmentioning
confidence: 99%
See 1 more Smart Citation
“…Mixed levels of realism have been proposed for regular maps used for data exploration purposes (Jenny et al 2012) as well as for VR. In VR, egocentric-view-VR representations with selective photorealism (a mix of abstract and photorealistic representations) have been tested in the context of route learning, memory, and aging and have been shown to benefit users (Lokka et al 2018;Lokka and Çöltekin 2019).…”
Section: User Interaction and Interfacesmentioning
confidence: 99%
“…In some cases, we need to follow the "Goldilocks principle" because too much or too little realism is suboptimal. As Lokka and Çöltekin (2019) demonstrated, if there is too much realism, we may miss important details because we cannot hold all the details in our memory whereas if there is too little, we may find it difficult to learn environments because there are too few 'anchors' for the human memory to link new knowledge of the environment. These issues of how to abstract data and how it can be effectively visualized for end users are growing in the era of big data and Digital Earth.…”
Section: Managing Informationmentioning
confidence: 99%
“…rendering, stylization and interaction 3D geovisualization, especially for urban analysis purposes, is widely explored in geographic information sciences. Most of all, issues of data pre-processing, for instance the Level Of Detail (Biljecki et al, 2014), rendering (Trapp et al, 2011) and stylization (Brasebin et al, 2016) of 3D urban models are often at stake, based on interactive systems offering interaction and navigation, between rendering styles (Semmo et al, 2012, Boér et al, 2013, Semmo and Döllner, 2014 or into the scene (Devaux and Brédif, 2016), favoring visual attention Çöltekin, 2012, Bektas et al, 2015) or usability by final users (Lokka and Çöltekin, 2017). In previous works, we have been specifying a 3D geovisualization pipeline (Brasebin et al, 2016) inspired from the cartographic pipeline designed in (Christophe et al, 2016), based on each of the following main processes of geovisualization: 3D data modeling, rendering, stylization and interaction.…”
Section: D Urban Geovisualization Pipeline: Data Preprocessingmentioning
confidence: 99%
“…Why are there such differences, and can we design the content in a way that benefits everyone? Lokka and Çöltekin (2019) take an interest in this question, from an abstract-and-realism lens in their paper titled 'Toward optimizing the design of virtual environments for route learning: empirically assessing the effects of changing levels of realism on memory'. In this comprehensive controlled experiment, Lokka & Çöltekin compare three levels of realism in the context of route learning, demonstrating that using the photo-textures selectively in a virtual environment meant for route learning is beneficial in terms of short-and long-term recall of routes.…”
mentioning
confidence: 99%