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Record W3203530699 · doi:10.1145/3474656

To Be or Not to Be Stuck, or Is It a Continuum?

2021· article· en· W3203530699 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueProceedings of the ACM on Human-Computer Interaction · 2021
Typearticle
Languageen
FieldPsychology
TopicEducational Games and Gamification
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsComputer scienceProcess (computing)Artificial intelligenceProgramming language

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.125
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.177
GPT teacher head0.438
Teacher spread0.261 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it