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Determining the User Profile for an Adaptable Training Platform

机译:确定适应性训练平台的用户简档

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Adaptive computer-based training systems aim to enhance the learning experience by personalising the presentation and content delivery according to the preferences of each particular user. The complexity of humans - the many factors influencing learning, from learning styles to physical abilities; and the proliferation of human-computer interface modalities - proves difficult for a system to fully determine when modelling diverse user profiles. Therefore most research has only focussed on the user's learning preferences and training via the "normal" auditory-visual channels. In this paper it is shown how a user model can be determined that includes the learning style, learning preference, abilities and the various available computing modalities. The model further incorporates how each of the elements influence each other. Such a model can be trained and expanded to allow for different training paradigms.
机译:自适应计算机的培训系统旨在通过根据每个特定用户的偏好来个性化演示和内容交付来提高学习体验。人类的复杂性 - 影响学习的许多因素,从学习方式到身体能力;和人计算机接口模态的扩散 - 证明系统难以在建模各种用户配置文件时完全确定。因此,大多数研究才专注于用户通过“正常”听觉视渠道的学习偏好和培训。本文示出了如何确定用户模型,包括学习风格,学习偏好,能力和各种可用的计算模式。该模型还包括每个元素如何彼此影响。可以训练这种模型并扩展以允许不同的训练范例。

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