Macedonia Manuela, Hammer Florian, Weichselbaum Otto
Information Engineering, Johannes Kepler Universität Linz, Linz, Austria.
Neural Mechanisms of Human Communication, Max-Planck-Institut für Kognitions- und Neurowissenschaften, Leipzig, Germany.
Front Psychol. 2018 Jun 13;9:927. doi: 10.3389/fpsyg.2018.00927. eCollection 2018.
Intelligent tutor systems (ITSs) in mobile devices take us through learning tasks and make learning ubiquitous, autonomous, and at low cost (Nye, 2015). In this paper, we describe guided embodiment as an ITS essential feature for second language learning (L2) and aphasia rehabilitation (ARe) that enhances efficiency in the learning process. In embodiment, cognitive processes, here specifically language (re)learning are grounded in actions and gestures (Pecher and Zwaan, 2005; Fischer and Zwaan, 2008; Dijkstra and Post, 2015). In order to guide users through embodiment, ITSs must track action and gesture, and give corrective feed-back to achieve the users' goals. Therefore, sensor systems are essential to guided embodiment. In the next sections, we describe sensor systems that can be implemented in ITS for guided embodiment.
移动设备中的智能辅导系统(ITSs)引领我们完成学习任务,使学习变得无处不在、自主且成本低廉(Nye,2015)。在本文中,我们将引导式具身描述为智能辅导系统的一个基本特征,它适用于第二语言学习(L2)和失语症康复(ARe),可提高学习过程的效率。在具身中,认知过程,这里具体指语言(再)学习,是以动作和手势为基础的(Pecher和Zwaan,2005;Fischer和Zwaan,2008;Dijkstra和Post,2015)。为了通过具身引导用户,智能辅导系统必须跟踪动作和手势,并提供纠正反馈以实现用户的目标。因此,传感器系统对于引导式具身至关重要。在接下来的部分中,我们将描述可在智能辅导系统中实现用于引导式具身的传感器系统。