To Be or Not to Be Stuck, or Is It a Continuum?
Bibliographic record
Abstract
Players can get stuck in video games, which impedes their process to their goal and results in unfavorable outcomes like negative emotions, impediments of flow, and obstacles for learning. Currently, it is not easily possible to assess if a player is stuck, as no widely accepted definition of "being stuck" in games exists. We conducted 13 expert interviews and a systematic literature review with 104 relevant papers selected from 4022 candidates. We present a definition of "being stuck" that conceptualizes the state as a continuum and contextualize it within related concepts. Our stuck continuum can be applied to regulate the player's stuck level. We propose a taxonomy of measures that are useful for the detection of the level of stuckness and discuss the effectiveness of countermeasures. Our stuck concept is crucial for game developers creating an optimal player experience in games.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.011 |
| Scholarly communication | 0.008 | 0.012 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".