More than a feeling: Measurement of sonic user experience and psychophysiology in a first-person shooter game
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The combination of psychophysiological and psychometric methods provides reliable measurements of affective user experience (UX). Understanding the nature of affective UX in interactive entertainment, especially with a focus on sonic stimuli, is an ongoing research challenge. In the empirical study reported here, participants played a fast-paced, immersive first-person shooter (FPS) game modification, in which sound (on/off) and music (on/off) were manipulated, while psychophysiological recordings of electrodermal activity (EDA) and facial muscle activity (EMG) were recorded in addition to a Game Experience Questionnaire (GEQ). Results indicate no main or interaction effects of sound or music on EMG and EDA. However, a significant main effect of sound on all GEQ dimensions (immersion, tension, competence, flow, negative affect, positive affect, and challenge) was found. In addition, an interaction effect of sound and music on GEQ dimension tension and flow indicates an important relationship of sound and music for gameplay experience. Additionally, we report the results of a correlation between GEQ dimensions and EMG/EDA activity. We conclude subjective measures could advance our understanding of sonic UX in digital games, while affective tonic (i.e., long-term psychophysiological) measures of sonic UX in digital games did not yield statistically significant results. One approach for future affective psychophysiological measures of sonic UX could be experiments investigating phasic (i.e., event-related) psychophysiological measures of sonic gameplay elements in digital games. This could improve our general understanding of sonic UX beyond affective gaming evaluation.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it