Evaluating the Onboarding Phase of Free-toPlay Mobile Games
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 first few minutes of play, commonly referred to as the onboarding phase, of Free-to-Play mobile games typically display a substantial churn rate among new players. It is therefore vital for designers to effectively evaluate this phase to investigate its satisfaction of player expectations. This paper presents a study utilizing a lab-based mixed-methods approach in providing insights for evaluating the user experience of onboarding phases in mobile games. This includes an investigation into the contribution of physiological measures (Heart-Rate Variability and Galvanic Skin Conductance) as well as a range of self-reported proxy measures including: a) stimulated recall, engagement graphs, b) flow state survey and c) post-game experience questionnaire. These techniques were applied across 28 participants using three mobile Free-to-Play titles from different genres. This paper makes two important contributions to the games user research (GUR) domain: 1) evaluates different research techniques (e.g. physiological measures and experience graphs) in the context of mobile games; 2) provides an empirically based recommendation for design elements that result in high arousal.
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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 | 0.001 | 0.001 |
| 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) | 0.006 | 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