Genre-Based, Show-Specific, and Biome-Specific ARTV Ornamentations: Raw Dataset from a VR-Simulated Passenger Train Study

This dataset contains raw data from a within-subjects laboratory study (N=20) investigating strategies for ARTV Ornamentation in a dramatic television context, using a simulated passenger train environment. This study extended the ARTV Ornamentation concept to a new genre — medieval fantasy drama — to examine how ornamentation design strategies should adapt to content featuring multiple visually distinct settings. The study compared four conditions: a Baseline (floating AR panel, unmodified virtual carriage); Genre-Based Augmentations (GBAs; generic medieval objects and retextured surfaces, static throughout); Show-Specific Augmentations (SSAs; Game of Thrones iconography including house banners, wolf heads, and swords, static throughout); and Biome-Specific Augmentations (BSAs; dynamically changing ornamentations and particle effects — medieval interior, snow, sand — synchronised to the three distinct biomes in the clip). All conditions were simulated using an Oculus Quest 2 headset. Participants watched a continuous 9-minute clip from Season 2, Episode 2 of Game of Thrones spanning three narrative settings: King's Landing, Craster's Keep, and the Red Wastes. All participants were required to have watched at least one season of Game of Thrones prior to taking part. After each condition participants completed the Film Immersive Experience Questionnaire (Film-IEQ), the short-form User Experience Questionnaire (UEQ-S), the short-form User Engagement Scale (UES-SF), and two custom awareness items on a 5-point Likert scale. Following all conditions, participants completed a condition preference ranking and a semi-structured exit interview. Participants ranged in age from 19 to 60 (M=31, SD=10.4; 14 male, 6 female). The dataset comprises anonymised Qualtrics survey responses (CSV), anonymised and manually verified interview transcripts (TXT; originally transcribed using WhisperX), and R analysis scripts. The study was approved by the University of Glasgow Ethics Committee. This dataset supports the findings reported in Chapter 5 of the associated PhD thesis: Balancing Media Immersion and Reality Awareness for Passengers through Augmented Reality TV Ornamentations, University of Glasgow.