We present PizzaText, a circular keyboard layout technique for text entry in virtual reality (VR) environments that uses the dual thumbsticks of a hand-held game controller. Text entry is a common activity in VR environments but remains challenging with existing techniques and keyboard layouts that is largely based on QWERTY. Our technique makes text entry simple, easy, and efficient, even for novice users. The technique uses a hand-held controller because it is still an important input device for users to interact with VR environments. To allow rapid search of characters, PizzaText divides a circle into slices and each slice contains 4 characters. To enable fast selection, the user uses the right thumbstick for traversing the slices, and the left thumbstick for choosing the letters. The design of PizzaText is based on three criteria: efficiency, learnability, and ease-of-use. In our first study, six potential layouts are considered and evaluated. The results lead to a design with 7 slices and 4 letters per slice. The final design is evaluated in a five-day study with 10 participants. The results show that novice users can achieve an average of 8.59 Words per Minute (WPM), while expert users are able to reach 15.85 WPM, with just two hours of training.

In this paper, we present a case for text entry using a circular keyboard layout for mobile head-mounted displays (HMDs) that is dwell-free and does not require users to hold a dedicated input device for letter selection. To support the case, we have implemented RingText whose design is based on a circular layout with two concentric circles. The outer circle is subdivided into regions containing letters. Selection is made by using a virtual cursor controlled by the user's head movements-entering a letter region triggers a selection and moving back into the inner circle resets the selection. The design of RingText follows an iterative process, where we initially conduct one first study to investigate the optimal number of letters per region, inner circle size, and alphabet starting location. We then optimize its design by selecting the most suitable features from the first study: one letter per region, narrowing the trigger area to lower error rates, and creating candidate regions that incorporate two suggested words to appear next to the current letter region (close to the cursor) using a dynamic (rather than fixed) approach. Our second study compares text entry performance of RingText with four other hands-free techniques and the results show that RingText outperforms them. Finally, we run a third study lasting four consecutive days with 10 participants (5 novice users and 5 expert users) doing two daily sessions and the results show that RingText is quite efficient and yields a low error rate. At the end of the eighth session, the novice users can achieve a text entry speed of 11.30 WPM after 60 minutes of training while the expert (more experienced) users can reach an average text entry speed of 13.24 WPM after 90 minutes of training.

Virtual Reality (VR) technology has progressed rapidly and is used in various domains, particularly games. Simulator Sickness (SS) still represents a significant problem for its wider adoption. The most common way to detect SS is using the Simulator Sickness Questionnaire (SSQ). SSQ is a subjective measurement and is inadequate for real-time applications such as VR games. This research aims to develop a model to predict SS in real time using in-game characters’ movement and users’ eye motion data during gameplay in VR games. To achieve this, we designed an experiment to collect such data with three types of games. We trained a Long Short-Term Memory neural network with the eye-tracking and character movement data to predict SS. Our model can predict SS in real time with an accuracy of 83.4% for players who suffer from severe sensitivity to SS. Our results indicate that, in VR games, our model is an accurate and efficient method to predict SS in real time.

This study investigates English language learner (ELL) perceptions of using a prototype virtual reality learning environment (VRLE) designed for teaching and learning writing structure. A mixed-methods approach was used, incorporating pre- and post-participation questionnaires, as well as semi-structured interviews. Participants consisted of 10 ELLs enrolled in first year English for Academic Purposes (EAP) courses at a university in Mainland, China. Results indicate that while the majority of students enjoyed using the VRLE, they maintained varying attitudes regarding the usefulness of the VRLE. Additionally, results from a correlation analysis suggest that learners' attitudes towards the material or content being learned (EAP writing) significantly correlates with learners' attitudes towards using the VRLE for learning writing structure.