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A logogram is a type of writing system in which each character represents a word. Compared to segmental scripts where the alphabets reflect sounds, learning logograms are disengaging, since each character is not linked to its pronunciation. This paper presents Logogram VR, a virtual reality edutainment game that uses a treadmill and controllers to teach Hanja, which uses logograms. Hanja is a traditional Korean language writing system comprising over 8000 Chinese characters. The system leverages the logogram’s feature that each letter stands for each vocabulary item, as an embodied learning strategy. Specifically, it incorporates each character’s meaning into the VR learning environment, accompanied by gamified actions using a treadmill and VR controllers. We evaluated the system with 33 participants to test its overall usability, while determining the desirable playtime and number of characters for the further enhancement of it. We demonstrated and assessed the system with 125 visitors at an exhibition to disseminate it and verify the results with a wider population sample. The user studies revealed that the system provides a playful experience for learning Hanja without severe motion sickness. The differences in age groups showed that the embodiment approach utilizing meanings and actions in VR may be an effective logogram edutainment strategy, particularly among adolescents.

Autonomous vehicles (AVs) enable drivers to devote their primary attention to non-driving-related tasks (NDRTs). Consequently, AVs must provide intelligibility services appropriate to drivers’ in-situ states and in-car activities to ensure driver safety, and accounting for the type of NDRT being performed can result in higher intelligibility. We discovered that sleeping is drivers’ most preferred NDRT, and this could also result in a critical scenario when a take-over request (TOR) occurs. In this study, we designed TOR situations where drivers are woken from sleep in a high-fidelity AV simulator with motion systems, aiming to examine how drivers react to a TOR provided with our experimental conditions. We investigated how driving performance, perceived task workload, AV acceptance, and physiological responses in a TOR vary according to two factors: (1) feedforward timings and (2) presentation modalities. The results showed that when awakened by a TOR alert delivered >10 s prior to an event, drivers were more focused on the driving context and were unlikely to be influenced by TOR modality, whereas TOR alerts delivered <5 s prior needed a visual accompaniment to quickly inform drivers of on-road situations. This study furthers understanding of how a driver’s cognitive and physical demands interact with TOR situations at the moment of waking from sleep and designs effective interventions for intelligibility services to best comply with safety and driver experience in AVs.