School travel modes and children’s spatial cognition

Urban Studies ◽  
2016 ◽  
Vol 54 (7) ◽  
pp. 1578-1600 ◽  
Author(s):  
Jo-Ting Fang ◽  
Jen-Jia Lin
Keyword(s):  
Spatial Cognition ◽  
Spatial Representation ◽  
Cognitive Mapping ◽  
Home School ◽  
Transportation Modes ◽  
New Knowledge ◽  
Mapping Process ◽  
Children's Travel ◽  
Linear Regressions ◽  
Northern Taiwan

This study broadens understanding of how children’s travel modes influence the development of their spatial cognition, specifically the development of their spatial representation of home–school routes. Data were collected using a questionnaire survey and a cognitive mapping process at an elementary school in northern Taiwan. The sample, which comprised 521 Grades 1–6 children aged 7–12 years, was analysed through linear regressions. Empirical results indicate that the use of independent, active or non-motorised transportation modes improved the children’s spatial cognition regarding their home–school routes. This study not only provides new knowledge about the relationships between travel modes and the spatial cognition of children, but also identifies policy directions in relation to school transportation and the development of spatial cognition in children.

scholarly journals Navigating in a three-dimensional world

2013 ◽  
Vol 36 (5) ◽  
pp. 523-543 ◽  
Author(s):  
Kathryn J. Jeffery ◽  
Aleksandar Jovalekic ◽  
Madeleine Verriotis ◽  
Robin Hayman
Keyword(s):  
Spatial Cognition ◽  
Horizontal Plane ◽  
Spatial Representation ◽  
Three Dimensional ◽  
Three Dimensions ◽  
Complex Topography ◽  
Orthogonal Axis ◽  
Fully Integrated ◽  
Insight Into ◽  
Considerable Insight

AbstractThe study of spatial cognition has provided considerable insight into how animals (including humans) navigate on the horizontal plane. However, the real world is three-dimensional, having a complex topography including both horizontal and vertical features, which presents additional challenges for representation and navigation. The present article reviews the emerging behavioral and neurobiological literature on spatial cognition in non-horizontal environments. We suggest that three-dimensional spaces are represented in a quasi-planar fashion, with space in the plane of locomotion being computed separately and represented differently from space in the orthogonal axis – a representational structure we have termed “bicoded.” We argue that the mammalian spatial representation in surface-travelling animals comprises a mosaic of these locally planar fragments, rather than a fully integrated volumetric map. More generally, this may be true even for species that can move freely in all three dimensions, such as birds and fish. We outline the evidence supporting this view, together with the adaptive advantages of such a scheme.

Landmark stability: studies exploring whether the perceived stability of the environment influences spatial representation.

1996 ◽  
Vol 199 (1) ◽  
pp. 187-193 ◽  
Author(s):  
R Biegler ◽  
R Morris
Keyword(s):  
Spatial Learning ◽  
Spatial Representation ◽  
Cognitive Mapping ◽  
Spatial Relationship ◽  
Relative Advantage ◽  
Learning Theories ◽  
Predictive Relationships ◽  
The Stability ◽  
Context Cues ◽  
Improved Accuracy

To investigate whether spatial learning complies with associative learning theories or with theories of cognitive mapping, rats were trained in three experiments exploring the effect of variations in spatial predictive relationships. In experiment 1, it was found that making one of two landmarks the sole spatial predictor of reward, by varying the spatial relationship between reward and other cues, reduced the control over search exerted by that landmark compared with that observed when the landmark and context cues were both reliable predictors of reward location. This requirement for landmark stability rather than predictive power appears to contradict results obtained in conventional conditioning paradigms. Discrimination learning was unaffected, suggesting a dissociation between discrimination and spatial learning with respect to the influence of geometric stability. Further experiments used arrays of both single and multiple landmarks. Experiment 2 revealed that the stability of a single landmark improved accuracy of search, but also showed that local stability between a pair of landmarks that moved around the arena together was sufficient to support spatial learning. Experiment 3 examined landmark stability using fixed directional cues in the absence of vestibular disorientation. This also revealed a relative advantage of stable landmarks, but animals presented with a landmark that moved from trial to trial did show some evidence of learning. Parametric manipulation of landmark stability offers an intriguing way of influencing the process of spatial representation and thus understanding better the processes through which egocentric representations of perceived space are transformed into allocentric representations of the real world.

scholarly journals CITRA UBUD BALI BERDASARKAN PETA KOGNISI MASYARAKAT

2020 ◽  
Vol 7 (1) ◽  
pp. 25
Author(s):  
Mutiara Anggi ◽  
Diananta Pramitasari ◽  
Syam Rachma Marcillia
Keyword(s):  
Spatial Cognition ◽  
Rural Area ◽  
Research Method ◽  
Cognitive Mapping ◽  
Cognitive Maps ◽  
Cognitive Map ◽  
Urban Density ◽  
Tourist Destinations ◽  
Strong Culture

Berbagai kota maupun wilayah di Indonesia banyak memiliki potensi pariwisata yang menarik sehingga dikunjungi oleh turis dari berbagai macam negara. Salah satunya adalah area Ubud Bali yang memiliki banyak destinasi wisata dan terus berkembang untuk memenuhi kebutuhan pariwisatanya. Perkembangan yang pesat tersebut dikhawatirkan akan menyebabkan kepadatan lingkungan yang tidak terkendali dan berubahnya citra Ubud sebagai kawasan alam dan pedesaan yang tenang. Oleh karena itu, penelitian ini dilakukan untuk mengetahui citra Ubud berdasarkan kognisi spasial yang tergambar melalui peta kognisi (cognitive map) masyarakatnya. Citra Ubud tersebut diharapkan dapat digunakan sebagai pertimbangan untuk perkembangan area Ubud nantinya. Penelitian yang dilakukan di area Ubud, Kabupaten Gianyar, Bali ini menggunakan metode penelitian pemetaan kognisi (cognitive mapping). Melalui metode ini sebelas responden diminta untuk menggambarkan sketsa peta area Ubud dengan menunjukkan lima elemen kota menurut Kevin Lynch, yaitu landmark, node, path, district, dan edge. Dari sebelas cognitive map yang tergambar, didapatkan hasil bahwa Ubud memiliki citra kawasan sebagai kawasan wisata yang masih memegang kuat budayanya. Hal ini ditunjukkan melalui perempatan Ubud dan Monkey Forest sebagai elemen spasial yang tertanam kuat dalam kognisi responden.IMAGE OF UBUD BALI BASED ON COGNITIVE MAP OF THE DWELLERS Various regions in Indonesia have many attractive tourism potentials and are visited by tourists from various countries. One of them is the area of Ubud, Bali, which has many tourist destinations and continues to grow to meet the needs of tourism. This rapidly growing tourism will raise some concerns about uncontrolled urban density and the alteration of Ubud’s image as a peaceful and natural rural area. Therefore, this research was conducted to find out the image of Ubud based on the dwellers’ spatial cognition, which is drawn through their cognitive maps. This image of Ubud is expected to be used as a consideration for the development of the Ubud area. The research was conducted in the area of Ubud, Gianyar, Bali, and used cognitive mapping as the research method. Through this method, eleven respondents were asked to sketch the maps of Ubud area by showing five city’s elements, according to Kevin Lynch. Those elements are landmark, node, path, district, and edge. From eleven cognitive maps drawn, the obtained result is that Ubud has the image of a tourist area that still holds a strong culture. This is shown through the intersection of Ubud and Monkey Forest as spatial elements that are firmly embedded in the respondents’ spatial cognition.

scholarly journals Mice identify subgoal locations through an action-driven mapping process

2021 ◽  
Author(s):  
Philip Shamash ◽  
Tiago Branco
Keyword(s):  
Closed Loop ◽  
Cognitive Mapping ◽  
Planning Process ◽  
Spatial Analyses ◽  
Mental Maps ◽  
Starting Position ◽  
Mapping Process ◽  
Biased Diffusion ◽  
Learning As A Process ◽  
The Relationship

Mammals instinctively explore and form mental maps of their spatial environments. Models of cognitive mapping in neuroscience mostly depict map-learning as a process of random or biased diffusion. In practice, however, animals explore spaces using structured, purposeful, sensory-guided actions. Here we test the hypothesis that executing specific exploratory actions is a key strategy for building a cognitive map. Previous work has shown that in arenas with obstacles and a shelter, mice spontaneously learn efficient multi-step escape routes by memorizing allocentric subgoal locations. We thus used threat-evoked escape to probe the relationship between ethological exploratory behavior and allocentric spatial memory. Using closed-loop neural manipulations to interrupt running movements during exploration, we found that blocking runs targeting an obstacle edge abolished subgoal learning. In contrast, blocking other movements while sparing edge-directed runs had no effect on memorizing subgoals. Finally, spatial analyses suggest that the decision to use a subgoal during escape takes into account the mouse's starting position relative to the layout of the environment. We conclude that mice use an action-driven learning process to identify subgoals and that these subgoals are then integrated into a map-based planning process. We suggest a conceptual framework for spatial learning that is compatible with the successor representation from reinforcement learning and sensorimotor enactivism from cognitive science.

Identifying groups of airborne particles by ordination

1994 ◽  
Vol 52 ◽  
pp. 856-857
Author(s):  
M. Shlepr ◽  
C. M. Vicroy
Keyword(s):  
Elemental Analysis ◽  
Energy Dispersive Spectroscopy ◽  
Manufacturing Process ◽  
Spatial Representation ◽  
Airborne Particles ◽  
Common Source ◽  
Data Set ◽  
Microelectronics Industry ◽  
Induced Changes ◽  
Source Materials

The microelectronics industry is heavily tasked with minimizing contaminates at all steps of the manufacturing process. Particles are generated by physical and/or chemical fragmentation from a mothersource. The tools and macrovolumes of chemicals used for processing, the environment surrounding the process, and the circuits themselves are all potential particle sources. A first step in eliminating these contaminants is to identify their source. Elemental analysis of the particles often proves useful toward this goal, and energy dispersive spectroscopy (EDS) is a commonly used technique. However, the large variety of source materials and process induced changes in the particles often make it difficult to discern if the particles are from a common source.Ordination is commonly used in ecology to understand community relationships. This technique usespair-wise measures of similarity. Separation of the data set is based on discrimination functions. Theend product is a spatial representation of the data with the distance between points equaling the degree of dissimilarity.

Bayesian removal of noise for increased sensitivity in vector pattern recognition lattice imaging of interfaces

1993 ◽  
Vol 51 ◽  
pp. 994-995
Author(s):  
L. Fei ◽  
P. Fraundorf
Keyword(s):  
Pattern Recognition ◽  
Perfect Crystal ◽  
Unit Cell ◽  
Ion Milling ◽  
Beam Radiation ◽  
Major Interest ◽  
Unit Cells ◽  
Mapping Process ◽  
Increased Sensitivity ◽  
Electron Microscopes

Interface structure is of major interest in microscopy. With high resolution transmission electron microscopes (TEMs) and scanning probe microscopes, it is possible to reveal structure of interfaces in unit cells, in some cases with atomic resolution. A. Ourmazd et al. proposed quantifying such observations by using vector pattern recognition to map chemical composition changes across the interface in TEM images with unit cell resolution. The sensitivity of the mapping process, however, is limited by the repeatability of unit cell images of perfect crystal, and hence by the amount of delocalized noise, e.g. due to ion milling or beam radiation damage. Bayesian removal of noise, based on statistical inference, can be used to reduce the amount of non-periodic noise in images after acquisition. The basic principle of Bayesian phase-model background subtraction, according to our previous study, is that the optimum (rms error minimizing strategy) Fourier phases of the noise can be obtained provided the amplitudes of the noise is given, while the noise amplitude can often be estimated from the image itself.

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