22 resultados para real world learning


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Routine computer tasks are often difficult for older adult computer users to learn and remember. People tend to learn new tasks by relating new concepts to existing knowledge. However, even for 'basic' computer tasks there is little, if any, existing knowledge on which older adults can base their learning. This paper investigates a custom file management interface that was designed to aid discovery and learnability by providing interface objects that are familiar to the user. A study was conducted which examined the differences between older and younger computer users when undertaking routine file management tasks using the standard Windows desktop as compared with the custom interface. Results showed that older adult computer users requested help more than ten times as often as younger users when using a standard windows/mouse configuration, made more mistakes and also required significantly more confirmations than younger users. The custom interface showed improvements over standard Windows/mouse, with fewer confirmations and less help being required. Hence, there is potential for an interface that closely mimics the real world to improve computer accessibility for older adults, aiding self-discovery and learnability.

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In this paper we describe how to cope with the delays inherent in a real time control system for a steerable stereo head/eye platform. A purposive and reactive system requires the use of fast vision algorithms to provide the controller with the error signals to drive the platform. The time-critical implementation of these algorithms is necessary, not only to enable short latency reaction to real world events, but also to provide sufficiently high frequency results with small enough delays that controller remain stable. However, even with precise knowledge of that delay, nonlinearities in the plant make modelling of that plant impossible, thus precluding the use of a Smith Regulator. Moreover, the major delay in the system is in the feedback (image capture and vision processing) rather than feed forward (controller) loop. Delays ranging between 40msecs and 80msecs are common for the simple 2D processes, but might extend to several hundred milliseconds for more sophisticated 3D processes. The strategy presented gives precise control over the gaze direction of the cameras despite the lack of a priori knowledge of the delays involved. The resulting controller is shown to have a similar structure to the Smith Regulator, but with essential modifications.

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Teaching mathematics to students in the biological sciences is often fraught with difficulty. Students often discover mathematics to be a very 'dry' subject in which it is difficult to see the motivation of learning it given its often abstract application. In this paper I advocate the use of mathematical modelling as a method for engaging students in understanding the use of mathematics in helping to solve problems in the Biological Sciences. The concept of mathematics as a laboratory tool is introduced and the importance of presenting students with relevant, real-world examples of applying mathematics in the Biological Sciences is discussed.

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Students in the architecture, engineering, and construction disciplines are often challenged with visualizing and understanding the complex spatial and temporal relationships involved in designing and constructing three-dimensional (3D) structures. An evolving body of research traces the use of educational computer simulations to enhance student learning experiences through testing real-world scenarios and the development of student decision-making skills. Ongoing research at Pennsylvania State University aims to improve engineering education in construction through interactive construction project learning applications in an immersive virtual reality environment. This paper describes the first- and second-generation development of the Virtual Construction Simulator (VCS), a tool that enables students to simultaneously create and review construction schedules through 3D model interaction. The educational value and utility of VCS was assessed through surveys, focus group interviews, and a student exercise conducted in a construction management class. Results revealed VCS is a valuable and effective four-dimensional (4D) model creation and schedule review application that fosters collaborative work and greater student task focus. This paper concludes with a discussion of the findings and the future development steps of the VCS educational simulation

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As the fidelity of virtual environments (VE) continues to increase, the possibility of using them as training platforms is becoming increasingly realistic for a variety of application domains, including military and emergency personnel training. In the past, there was much debate on whether the acquisition and subsequent transfer of spatial knowledge from VEs to the real world is possible, or whether the differences in medium during training would essentially be an obstacle to truly learning geometric space. In this paper, the authors present various cognitive and environmental factors that not only contribute to this process, but also interact with each other to a certain degree, leading to a variable exposure time requirement in order for the process of spatial knowledge acquisition (SKA) to occur. The cognitive factors that the authors discuss include a variety of individual user differences such as: knowledge and experience; cognitive gender differences; aptitude and spatial orientation skill; and finally, cognitive styles. Environmental factors discussed include: Size, Spatial layout complexity and landmark distribution. It may seem obvious that since every individual's brain is unique - not only through experience, but also through genetic predisposition that a one size fits all approach to training would be illogical. Furthermore, considering that various cognitive differences may further emerge when a certain stimulus is present (e.g. complex environmental space), it would make even more sense to understand how these factors can impact spatial memory, and to try to adapt the training session by providing visual/auditory cues as well as by changing the exposure time requirements for each individual. The impact of this research domain is important to VE training in general, however within service and military domains, guaranteeing appropriate spatial training is critical in order to ensure that disorientation does not occur in a life or death scenario.

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Autism spectrum conditions (autism) affect ~1% of the population and are characterized by deficits in social communication. Oxytocin has been widely reported to affect social-communicative function and its neural underpinnings. Here we report the first evidence that intranasal oxytocin administration improves a core problem that individuals with autism have in using eye contact appropriately in real-world social settings. A randomized double-blind, placebo-controlled, within-subjects design is used to examine how intranasal administration of 24 IU of oxytocin affects gaze behavior for 32 adult males with autism and 34 controls in a real-time interaction with a researcher. This interactive paradigm bypasses many of the limitations encountered with conventional static or computer-based stimuli. Eye movements are recorded using eye tracking, providing an objective measurement of looking patterns. The measure is shown to be sensitive to the reduced eye contact commonly reported in autism, with the autism group spending less time looking to the eye region of the face than controls. Oxytocin administration selectively enhanced gaze to the eyes in both the autism and control groups (transformed mean eye-fixation difference per second=0.082; 95% CI:0.025–0.14, P=0.006). Within the autism group, oxytocin has the most effect on fixation duration in individuals with impaired levels of eye contact at baseline (Cohen’s d=0.86). These findings demonstrate that the potential benefits of oxytocin in autism extend to a real-time interaction, providing evidence of a therapeutic effect in a key aspect of social communication.

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Subspace clustering groups a set of samples from a union of several linear subspaces into clusters, so that the samples in the same cluster are drawn from the same linear subspace. In the majority of the existing work on subspace clustering, clusters are built based on feature information, while sample correlations in their original spatial structure are simply ignored. Besides, original high-dimensional feature vector contains noisy/redundant information, and the time complexity grows exponentially with the number of dimensions. To address these issues, we propose a tensor low-rank representation (TLRR) and sparse coding-based (TLRRSC) subspace clustering method by simultaneously considering feature information and spatial structures. TLRR seeks the lowest rank representation over original spatial structures along all spatial directions. Sparse coding learns a dictionary along feature spaces, so that each sample can be represented by a few atoms of the learned dictionary. The affinity matrix used for spectral clustering is built from the joint similarities in both spatial and feature spaces. TLRRSC can well capture the global structure and inherent feature information of data, and provide a robust subspace segmentation from corrupted data. Experimental results on both synthetic and real-world data sets show that TLRRSC outperforms several established state-of-the-art methods.