Demystifying the First-Time Experience of Mobile Games: The Presence of a Tutorial Has a Positive Impact on Non-Expert Players’ Flow and Continuous-Use Intentions
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 purpose of video game tutorials is to help players easily understand new game mechanics and thereby facilitate chances of early engagement with the main contents of one’s game. The mobile game market (i.e., phones and tablets) faces important retention issues caused by a high number of players who abandon games permanently within 24 h of downloading them. A laboratory experiment with 40 players tested how tutorial presence and player expertise impact on users’ psychophysiological states and continuous-use intentions (CUIs). The results suggest that in a simple game context, tutorials have a positive impact on non-expert players’ perceived state of flow and have no effect on expert players’ perceived flow. The results also suggest that flow has a positive impact on CUIs for both experts and non-experts. The theoretical contributions and managerial implications of these results are discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 |
| 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