The Linguist

Chartered Institute of Linguists SUMMER 2026 The Linguist 17 FEATURES The first pilot, run with second‑year Spanish students in a speaking and listening module, focused on a job interview scenario. The overwhelmingly positive response led the department to expand the pilot in its second year to include French and first‑year cohorts, reaching 142 students across five modules from A1 to B2 level. The sessions were held in Lancaster's Data Immersion Suite, a state- of-the-art space with a wraparound projection wall and surround sound. Many students had used apps like Duolingo, and some had tried VR gaming, but few had experienced VR in an educational setting. From scenario to feedback Some fear that technology could one day replace human educators. In reality, VR‑enhanced, AI‑supported learning depends on the expertise of teachers working hand‑in‑hand with technologists to shape meaningful pedagogical experiences aligned with learning outcomes. Educators play a crucial role in preparing materials, introducing communicative goals and guiding students through immersive tasks. Far from reducing the need for teachers, this model places them at the centre of the experience. The initiative unfolds in three stages: scenario creation, material curation and immersive deployment. First of all, teachers and developers work together to design realistic simulations aligned to CEFR levels A1 to C2. Each scenario has multiple variants to allow both beginners and advanced learners to engage meaningfully at their own pace. The scenarios are then built using the game development software Unity. Each one features AI‑driven characters, which are programmed with role conditions and linguistic goals, ensuring that every interaction feels purposeful. This allows students to experiment and access a situation that would normally require travel. This system combines three technologies: OpenAI Whisper for speech-to‑text allows the system to recognise students' speech in real time; GPT‑4o generates dialogue, analyses grammar and vocabulary, and produces AI-generated feedback aligned to CEFR descriptors; and AWS Polly produces clear, natural-sounding speech from the AI characters. Students can also rehearse the same scenario on a web-based version before class, so they arrive better prepared, freeing classroom time for deeper practice and reflection. Students become active agents, as per constructivist and cognitive pedagogical approaches. They can also access curated preparatory materials in advance, including sample conversations, dialogues, learning objectives and key vocabulary. The pedagogical design takes into account learner variability, offering multiple ways to engage with content and reducing cognitive load for those who benefit from additional scaffolding. In class, culturally rich images projected across the Data Immersion Suite provide visual anchors that enhance immersion. Peer‑review rubrics are used during the session, reinforcing collaborative learning and giving students a structured way to evaluate each other's performance. Each session involves groups of no more than eight students to ensure the VR activity can be cast onto surrounding screens. Students help each other with vocabulary and grammar, which creates a shared experience and strengthens the learning community. For many, this collaborative element reduces anxiety and makes entering the virtual environment less intimidating. What students gain Feedback has been overwhelmingly positive. Students have described the experience as less pressured, more enjoyable and surprisingly empowering. The sessions contributed to reduced anxiety by giving students a psychologically safe space in which to speak freely and make mistakes without judgement, encouraging greater linguistic risk‑taking. The personalised approach was enhanced by AI-generated reports, which provide a full transcript of each performance and highlight patterns in vocabulary, structure and interaction. Students receive a new report after each scenario, which allows them to monitor their progress over time, recognise linguistic patterns and target specific areas for improvement. The multisensory nature of VR, combining visual, auditory and kinaesthetic cues, enhances comprehension, especially for those who typically struggle with listening tasks, as students have captions too. These trends offer promising early evidence of the pedagogical value of immersive VR‑supported practice. Research into how this pedagogy shapes learners' affective experiences, confidence and willingness to communicate is ongoing. In the meantime, the project was recognised externally as a shortlisted candidate for the Immersive Experiential Learning Award at the QS Reimagine Education Awards 2025. Challenges and future directions Despite strong outcomes, the project has not been without difficulties. Setting up VR headsets requires technical support and smaller group sizes increase staff workload. A few students also experienced minor glitches with slow responsiveness. A key ethical concern lies in the interpretation of AI- generated analysis: while potentially informative, such feedback lacks human contextual judgement and may be misleading if treated as an objective or affective truth, rather than as descriptive support for reflection. Funding remains a major hurdle as scaling development, and maintaining and improving scenarios, requires sustained investment, which is difficult in the current climate. Nonetheless, we are committed to continuing these sessions. The project provides a valuable foundation for broader integration of VR and AI into UK language learning, which lags behind places such as China, where technology‑enhanced language learning, particularly in English, is rapidly advancing with governmental support.

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