Experiential learning (ExL) is the process of learning through experience or more specifically "learning through reflection on doing". In this paper, we propose a simulation of these experiences, in Augmented Reality (AR), addressing the problem of language learning. Such systems provide an excellent setting to support "adaptive guidance", in a digital form, within a real environment. Adaptive guidance allows the instructions and learning content to be customised for the individual learner, thus creating a unique learning experience. We developed an adaptive guidance AR system for language learning, we call Arigat\=o (Augmented Reality Instructional Guidance & Tailored Omniverse), which offers immediate assistance, resources specific to the learner's needs, manipulation of these resources, and relevant feedback. Considering guidance, we employ this prototype to investigate the effect of the amount of guidance (fixed vs. adaptive-amount) and the type of guidance (fixed vs. adaptive-associations) on the engagement and consequently the learning outcomes of language learning in an AR environment. The results for the amount of guidance show that compared to the adaptive-amount, the fixed-amount of guidance group scored better in the immediate and delayed (after 7 days) recall tests. However, this group also invested a significantly higher mental effort to complete the task. The results for the type of guidance show that the adaptive-associations group outperforms the fixed-associations group in the immediate, delayed (after 7 days) recall tests, and learning efficiency. The adaptive-associations group also showed significantly lower mental effort and spent less time to complete the task.
翻译:(ExL) 通过经验或更具体地说,“通过思考思考来学习”学习过程。在本文中,我们建议模拟这些经验,在《增强现实》(AR)中,解决语言学习问题。这些系统提供了一个极佳的环境,以数字形式支持“适应性指导”,在现实环境中,以数字形式提供。适应性指导允许为个人学习者定制教学和学习内容,从而创造独特的学习经验。我们为语言学习开发了一个适应性指导AR系统,我们叫Arigaat ⁇ o(增强现实性教学指南和定制Omniverse),提供即时援助、针对学习者需要的资源及相关反馈。考虑到指导,我们使用这个模型来调查指导数量(固定对适应性指导)和指南类型(组合对适应性影响)的影响,从而创造独特的学习经验。我们称为Arigat ⁇ (增强现实性现实性指导与适应性指导相比,在适应性测试后7天中完成更高级的调整性测试。