This study introduces the Eye-tracking Translation Software (ETS), a system that leverages eye-tracking data and real-time translation to enhance reading flow for non-native language users in complex, technical texts. By measuring the fixation duration, we can detect moments of cognitive load, ETS selectively provides translations, maintaining reading flow and engagement without undermining language learning. The key technological components include a desktop eye-tracker integrated with a custom Python-based application. Through a user-centered design, ETS dynamically adapts to individual reading needs, reducing cognitive strain by offering word-level translations when needed. A study involving 53 participants assessed ETS’s impact on reading speed, fixation duration, and user experience, with findings indicating improved comprehension and reading efficiency. Results demonstrated that gaze-based adaptations significantly improved their reading experience and reduced cognitive load. Participants positively rated ETS’s usability and were noted through preferences for customization, such as pop-up placement and sentence-level translations. Future work will integrate AI-driven adaptations, allowing the system to adjust based on user proficiency and reading behavior. The study contributes to the growing evidence of eye-tracking’s potential in educational and professional applications, offering a flexible, personalized approach to reading assistance that balances language exposure with real-time support.

This paper presents a comprehensive examination of eye-tracking technologies aimed at enhancing multimodal interactions within aviation environments. By reviewing and comparing various eye-tracking approaches, we provide valuable insights into their strengths, limitations, and prospective applications. Eye tracking synergizes with human–machine interfaces to optimize cockpit operations improve safety and elevate user experience. Beyond cockpit interactions, these technologies hold substantial promises in training and simulation environments, offering detailed insights into pilots’ visual attention and decision-making processes. This data-driven approach enhances pilot training programs, contributing to more effective and targeted instruction. The integration of eye-tracking data with other physiological and performance metrics fosters a deeper understanding of pilot behavior, paving the way for innovations in interface design and operational protocols. Finally, this paper discusses the diversity of current eye-tracking technologies in aviation, emphasizing their practical usability in gaze-tracking systems and multimodal interaction frameworks.

This paper examines the impact of 3D Virtual World Learning Environments (VWLEs) on students’ environmental awareness, with a focus on the design, implementation, and evaluation of the GUESS platform. The platform employs gamification and immersive scenarios to replicate real-world ecological challenges, fostering experiential and collaborative learning. A mixed-methods evaluation was conducted through expert reviews, semi-structured interviews, and large-scale student testing across four European countries. Results from questionnaires and behavioral metrics indicate that the majority of participants reported an increased understanding of sustainability concepts, high levels of engagement, and strong motivation to adopt pro-environmental behaviors. Students highlighted the effectiveness of authentic problem-solving tasks and immediate feedback mechanisms, as well as the importance of collaborative interactions within the virtual world. While overall responses were highly positive, suggested refinements include improvements to the visual design and adjustments to scenario pacing. The findings demonstrate that 3D virtual worlds can serve as powerful tools for enhancing environmental competence, promoting critical reflection, and shaping sustainable attitudes among university students.

Modern flight decks incorporate advanced automation and real-time data systems to improve safety and efficiency. However, maintaining situational awareness under a high workload remains a critical challenge, particularly when attentional resources are stretched. This study investigates how adaptive interfaces, using real-time eye-tracking data, can help pilots maintain their concentration and stay aware of all indications on large-area displays. To this end, we developed a gaze-responsive display that monitors whether the pilot has visually focused on objects displayed on a moving map. When the system detects that the pilot has not noticed an object on the map, it automatically adjusts the interface, highlighting the missed object, thus helping to prevent critical information from being overlooked. The interface was evaluated in a controlled simulation study with 34 participants. By capturing pilots’ gaze behaviour, the system reveals how attention shifts under workload and how adaptive visual cues can complement natural scanning patterns. Participant feedback indicated that adaptive behaviour provided supportive guidance without imposing additional cognitive load. Overall, the study highlights the potential of adaptive gaze-based interfaces to enhance attention strategies and contribute to more resilient situational awareness in aviation.