miniPXI: Development and Validation of an Eleven-Item Measure of the Player Experience Inventory
Why this work is in the frame
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Bibliographic record
Abstract
Questionnaires are vital in games user research (GUR) to assess player experience (PX). However, having too many questions in surveys prevents wider uptake among GUR professionals because of games' rapid production cycles. To address this issue, we present the miniPXI---an eleven-item measure of the popular Player Experience Inventory (PXI)---providing single items for each of its eleven constructs. To develop the scale and examine its reliability and validity, we present three studies, conducted with 15 experts and 628 digital game players across continents. In the first survey study (n=366, 15 experts), single items were selected. In a second survey study (n=232), we explored reliability and validity of the single-item scale. Participants completed both full and single-item (SI) variants in three days. In the last study (n=30), we established the validity and sensitivity via an experimental evaluation of two games. The results are nuanced; SI reliability estimates for PXI constructs range from .51 to .83 with an average of .68, we could confirm the validity for nine constructs. We conclude that the miniPXI can be a valuable tool for PX evaluations where a longer measure is not feasible, and provide practical considerations for its use.
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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 | 0.001 | 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